(gentle music) >> Hello everyone. Welcome to this CUBE conversation here in Palo Alto, California. I'm John Furrier, host of theCUBE. We got a great remote guest coming in. Joseph Nelson, co-founder and CEO of RoboFlow hot startup in AI, computer vision. Really interesting topic in this wave of AI next gen hitting. Joseph, thanks for coming on this CUBE conversation. >> Thanks for having me. >> Yeah, I love the startup tsunami that's happening here in this wave. RoboFlow, you're in the middle of it. Exciting opportunities, you guys are in the cutting edge. I think computer vision's been talked about more as just as much as the large language models and these foundational models are merging. You're in the middle of it. What's it like right now as a startup and growing in this new wave hitting? >> It's kind of funny, it's, you know, I kind of describe it like sometimes you're in a garden of gnomes. It's like we feel like we've got this giant headstart with hundreds of thousands of people building with computer vision, training their own models, but that's a fraction of what it's going to be in six months, 12 months, 24 months. So, as you described it, a wave is a good way to think about it. And the wave is still building before it gets to its full size. So it's a ton of fun. >> Yeah, I think it's one of the most exciting areas in computer science. I wish I was in my twenties again, because I would be all over this. It's the intersection, there's so many disciplines, right? It's not just tech computer science, it's computer science, it's systems, it's software, it's data. There's so much aperture of things going on around your world. So, I mean, you got to be batting all the students away kind of trying to get hired in there, probably. I can only imagine you're hiring regiment. I'll ask that later, but first talk about what the company is that you're doing. How it's positioned, what's the market you're going after, and what's the origination story? How did you guys get here? How did you just say, hey, want to do this? What was the origination story? What do you do and how did you start the company? >> Yeah, yeah. I'll give you the what we do today and then I'll shift into the origin. RoboFlow builds tools for making the world programmable. Like anything that you see should be read write access if you think about it with a programmer's mind or legible. And computer vision is a technology that enables software to be added to these real world objects that we see. And so any sort of interface, any sort of object, any sort of scene, we can interact with it, we can make it more efficient, we can make it more entertaining by adding the ability for the tools that we use and the software that we write to understand those objects. And at RoboFlow, we've empowered a little over a hundred thousand developers, including those in half the Fortune 100 so far in that mission. Whether that's Walmart understanding the retail in their stores, Cardinal Health understanding the ways that they're helping their patients, or even electric vehicle manufacturers ensuring that they're making the right stuff at the right time. As you mentioned, it's early. Like I think maybe computer vision has touched one, maybe 2% of the whole economy and it'll be like everything in a very short period of time. And so we're focused on enabling that transformation. I think it's it, as far as I think about it, I've been fortunate to start companies before, start, sell these sorts of things. This is the last company I ever wanted to start and I think it will be, should we do it right, the world's largest in riding the wave of bringing together the disparate pieces of that technology. >> What was the motivating point of the formation? Was it, you know, you guys were hanging around? Was there some catalyst? What was the moment where it all kind of came together for you? >> You know what's funny is my co-founder, Brad and I, we were making computer vision apps for making board games more fun to play. So in 2017, Apple released AR kit, augmented reality kit for building augmented reality applications. And Brad and I are both sort of like hacker persona types. We feel like we don't really understand the technology until we build something with it and so we decided that we should make an app that if you point your phone at a Sudoku puzzle, it understands the state of the board and then it kind of magically fills in that experience with all the digits in real time, which totally ruins the game of Sudoku to be clear. But it also just creates this like aha moment of like, oh wow, like the ability for our pocket devices to understand and see the world as good or better than we can is possible. And so, you know, we actually did that as I mentioned in 2017, and the app went viral. It was, you know, top of some subreddits, top of Injure, Reddit, the hacker community as well as Product Hunt really liked it. So it actually won Product Hunt AR app of the year, which was the same year that the Tesla model three won the product of the year. So we joked that we share an award with Elon our shared (indistinct) But frankly, so that was 2017. RoboFlow wasn't incorporated as a business until 2019. And so, you know, when we made Magic Sudoku, I was running a different company at the time, Brad was running a different company at the time, and we kind of just put it out there and were excited by how many people liked it. And we assumed that other curious developers would see this inevitable future of, oh wow, you know. This is much more than just a pedestrian point your phone at a board game. This is everything can be seen and understood and rewritten in a different way. Things like, you know, maybe your fridge. Knowing what ingredients you have and suggesting recipes or auto ordering for you, or we were talking about some retail use cases of automated checkout. Like anything can be seen and observed and we presume that that would kick off a Cambrian explosion of applications. It didn't. So you fast forward to 2019, we said, well we might as well be the guys to start to tackle this sort of problem. And because of our success with board games before, we returned to making more board game solving applications. So we made one that solves Boggle, you know, the four by four word game, we made one that solves chess, you point your phone at a chess board and it understands the state of the board and then can make move recommendations. And each additional board game that we added, we realized that the tooling was really immature. The process of collecting images, knowing which images are actually going to be useful for improving model performance, training those models, deploying those models. And if we really wanted to make the world programmable, developers waiting for us to make an app for their thing of interest is a lot less efficient, less impactful than taking our tool chain and releasing that externally. And so, that's what RoboFlow became. RoboFlow became the internal tools that we used to make these game changing applications readily available. And as you know, when you give developers new tools, they create new billion dollar industries, let alone all sorts of fun hobbyist projects along the way. >> I love that story. Curious, inventive, little radical. Let's break the rules, see how we can push the envelope on the board games. That's how companies get started. It's a great story. I got to ask you, okay, what happens next? Now, okay, you realize this new tooling, but this is like how companies get built. Like they solve their own problem that they had 'cause they realized there's one, but then there has to be a market for it. So you actually guys knew that this was coming around the corner. So okay, you got your hacker mentality, you did that thing, you got the award and now you're like, okay, wow. Were you guys conscious of the wave coming? Was it one of those things where you said, look, if we do this, we solve our own problem, this will be big for everybody. Did you have that moment? Was that in 2019 or was that more of like, it kind of was obvious to you guys? >> Absolutely. I mean Brad puts this pretty effectively where he describes how we lived through the initial internet revolution, but we were kind of too young to really recognize and comprehend what was happening at the time. And then mobile happened and we were working on different companies that were not in the mobile space. And computer vision feels like the wave that we've caught. Like, this is a technology and capability that rewrites how we interact with the world, how everyone will interact with the world. And so we feel we've been kind of lucky this time, right place, right time of every enterprise will have the ability to improve their operations with computer vision. And so we've been very cognizant of the fact that computer vision is one of those groundbreaking technologies that every company will have as a part of their products and services and offerings, and we can provide the tooling to accelerate that future. >> Yeah, and the developer angle, by the way, I love that because I think, you know, as we've been saying in theCUBE all the time, developer's the new defacto standard bodies because what they adopt is pure, you know, meritocracy. And they pick the best. If it's sell service and it's good and it's got open source community around it, its all in. And they'll vote. They'll vote with their code and that is clear. Now I got to ask you, as you look at the market, we were just having this conversation on theCUBE in Barcelona at recent Mobile World Congress, now called MWC, around 5G versus wifi. And the debate was specifically computer vision, like facial recognition. We were talking about how the Cleveland Browns were using facial recognition for people coming into the stadium they were using it for ships in international ports. So the question was 5G versus wifi. My question is what infrastructure or what are the areas that need to be in place to make computer vision work? If you have developers building apps, apps got to run on stuff. So how do you sort that out in your mind? What's your reaction to that? >> A lot of the times when we see applications that need to run in real time and on video, they'll actually run at the edge without internet. And so a lot of our users will actually take their models and run it in a fully offline environment. Now to act on that information, you'll often need to have internet signal at some point 'cause you'll need to know how many people were in the stadium or what shipping crates are in my port at this point in time. You'll need to relay that information somewhere else, which will require connectivity. But actually using the model and creating the insights at the edge does not require internet. I mean we have users that deploy models on underwater submarines just as much as in outer space actually. And those are not very friendly environments to internet, let alone 5g. And so what you do is you use an edge device, like an Nvidia Jetson is common, mobile devices are common. Intel has some strong edge devices, the Movidius family of chips for example. And you use that compute that runs completely offline in real time to process those signals. Now again, what you do with those signals may require connectivity and that becomes a question of the problem you're solving of how soon you need to relay that information to another place. >> So, that's an architectural issue on the infrastructure. If you're a tactical edge war fighter for instance, you might want to have highly available and maybe high availability. I mean, these are words that mean something. You got storage, but it's not at the edge in real time. But you can trickle it back and pull it down. That's management. So that's more of a business by business decision or environment, right? >> That's right, that's right. Yeah. So I mean we can talk through some specifics. So for example, the RoboFlow actually powers the broadcaster that does the tennis ball tracking at Wimbledon. That runs completely at the edge in real time in, you know, technically to track the tennis ball and point the camera, you actually don't need internet. Now they do have internet of course to do the broadcasting and relay the signal and feeds and these sorts of things. And so that's a case where you have both edge deployment of running the model and high availability act on that model. We have other instances where customers will run their models on drones and the drone will go and do a flight and it'll say, you know, this many residential homes are in this given area, or this many cargo containers are in this given shipping yard. Or maybe we saw these environmental considerations of soil erosion along this riverbank. The model in that case can run on the drone during flight without internet, but then you only need internet once the drone lands and you're going to act on that information because for example, if you're doing like a study of soil erosion, you don't need to be real time. You just need to be able to process and make use of that information once the drone finishes its flight. >> Well I can imagine a zillion use cases. I heard of a use case interview at a company that does computer vision to help people see if anyone's jumping the fence on their company. Like, they know what a body looks like climbing a fence and they can spot it. Pretty easy use case compared to probably some of the other things, but this is the horizontal use cases, its so many use cases. So how do you guys talk to the marketplace when you say, hey, we have generative AI for commuter vision. You might know language models that's completely different animal because vision's like the world, right? So you got a lot more to do. What's the difference? How do you explain that to customers? What can I build and what's their reaction? >> Because we're such a developer centric company, developers are usually creative and show you the ways that they want to take advantage of new technologies. I mean, we've had people use things for identifying conveyor belt debris, doing gas leak detection, measuring the size of fish, airplane maintenance. We even had someone that like a hobby use case where they did like a specific sushi identifier. I dunno if you know this, but there's a specific type of whitefish that if you grew up in the western hemisphere and you eat it in the eastern hemisphere, you get very sick. And so there was someone that made an app that tells you if you happen to have that fish in the sushi that you're eating. But security camera analysis, transportation flows, plant disease detection, really, you know, smarter cities. We have people that are doing curb management identifying, and a lot of these use cases, the fantastic thing about building tools for developers is they're a creative bunch and they have these ideas that if you and I sat down for 15 minutes and said, let's guess every way computer vision can be used, we would need weeks to list all the example use cases. >> We'd miss everything. >> And we'd miss. And so having the community show us the ways that they're using computer vision is impactful. Now that said, there are of course commercial industries that have discovered the value and been able to be out of the gate. And that's where we have the Fortune 100 customers, like we do. Like the retail customers in the Walmart sector, healthcare providers like Medtronic, or vehicle manufacturers like Rivian who all have very difficult either supply chain, quality assurance, in stock, out of stock, anti-theft protection considerations that require successfully making sense of the real world. >> Let me ask you a question. This is maybe a little bit in the weeds, but it's more developer focused. What are some of the developer profiles that you're seeing right now in terms of low-hanging fruit applications? And can you talk about the academic impact? Because I imagine if I was in school right now, I'd be all over it. Are you seeing Master's thesis' being worked on with some of your stuff? Is the uptake in both areas of younger pre-graduates? And then inside the workforce, What are some of the devs like? Can you share just either what their makeup is, what they work on, give a little insight into the devs you're working with. >> Leading developers that want to be on state-of-the-art technology build with RoboFlow because they know they can use the best in class open source. They know that they can get the most out of their data. They know that they can deploy extremely quickly. That's true among students as you mentioned, just as much as as industries. So we welcome students and I mean, we have research grants that will regularly support for people to publish. I mean we actually have a channel inside our internal slack where every day, more student publications that cite building with RoboFlow pop up. And so, that helps inspire some of the use cases. Now what's interesting is that the use case is relatively, you know, useful or applicable for the business or the student. In other words, if a student does a thesis on how to do, we'll say like shingle damage detection from satellite imagery and they're just doing that as a master's thesis, in fact most insurance businesses would be interested in that sort of application. So, that's kind of how we see uptick and adoption both among researchers who want to be on the cutting edge and publish, both with RoboFlow and making use of open source tools in tandem with the tool that we provide, just as much as industry. And you know, I'm a big believer in the philosophy that kind of like what the hackers are doing nights and weekends, the Fortune 500 are doing in a pretty short order period of time and we're experiencing that transition. Computer vision used to be, you know, kind of like a PhD, multi-year investment endeavor. And now with some of the tooling that we're working on in open source technologies and the compute that's available, these science fiction ideas are possible in an afternoon. And so you have this idea of maybe doing asset management or the aerial observation of your shingles or things like this. You have a few hundred images and you can de-risk whether that's possible for your business today. So there's pretty broad-based adoption among both researchers that want to be on the state of the art, as much as companies that want to reduce the time to value. >> You know, Joseph, you guys and your partner have got a great front row seat, ground floor, presented creation wave here. I'm seeing a pattern emerging from all my conversations on theCUBE with founders that are successful, like yourselves, that there's two kind of real things going on. You got the enterprises grabbing the products and retrofitting into their legacy and rebuilding their business. And then you have startups coming out of the woodwork. Young, seeing greenfield or pick a specific niche or focus and making that the signature lever to move the market. >> That's right. >> So can you share your thoughts on the startup scene, other founders out there and talk about that? And then I have a couple questions for like the enterprises, the old school, the existing legacy. Little slower, but the startups are moving fast. What are some of the things you're seeing as startups are emerging in this field? >> I think you make a great point that independent of RoboFlow, very successful, especially developer focused businesses, kind of have three customer types. You have the startups and maybe like series A, series B startups that you're building a product as fast as you can to keep up with them, and they're really moving just as fast as as you are and pulling the product out at you for things that they need. The second segment that you have might be, call it SMB but not enterprise, who are able to purchase and aren't, you know, as fast of moving, but are stable and getting value and able to get to production. And then the third type is enterprise, and that's where you have typically larger contract value sizes, slower moving in terms of adoption and feedback for your product. And I think what you see is that successful companies balance having those three customer personas because you have the small startups, small fast moving upstarts that are discerning buyers who know the market and elect to build on tooling that is best in class. And so you basically kind of pass the smell test of companies who are quite discerning in their purchases, plus are moving so quick they're pulling their product out of you. Concurrently, you have a product that's enterprise ready to service the scalability, availability, and trust of enterprise buyers. And that's ultimately where a lot of companies will see tremendous commercial success. I mean I remember seeing the Twilio IPO, Uber being like a full 20% of their revenue, right? And so there's this very common pattern where you have the ability to find some of those upstarts that you make bets on, like the next Ubers of the world, the smaller companies that continue to get developed with the product and then the enterprise whom allows you to really fund the commercial success of the business, and validate the size of the opportunity in market that's being creative. >> It's interesting, there's so many things happening there. It's like, in a way it's a new category, but it's not a new category. It becomes a new category because of the capabilities, right? So, it's really interesting, 'cause that's what you're talking about is a category, creating. >> I think developer tools. So people often talk about B to B and B to C businesses. I think developer tools are in some ways a third way. I mean ultimately they're B to B, you're selling to other businesses and that's where your revenue's coming from. However, you look kind of like a B to C company in the ways that you measure product adoption and kind of go to market. In other words, you know, we're often tracking the leading indicators of commercial success in the form of usage, adoption, retention. Really consumer app, traditionally based metrics of how to know you're building the right stuff, and that's what product led growth companies do. And then you ultimately have commercial traction in a B to B way. And I think that that actually kind of looks like a third thing, right? Like you can do these sort of funny zany marketing examples that you might see historically from consumer businesses, but yet you ultimately make your money from the enterprise who has these de-risked high value problems you can solve for them. And I selfishly think that that's the best of both worlds because I don't have to be like Evan Spiegel, guessing the next consumer trend or maybe creating the next consumer trend and catching lightning in a bottle over and over again on the consumer side. But I still get to have fun in our marketing and make sort of fun, like we're launching the world's largest game of rock paper scissors being played with computer vision, right? Like that's sort of like a fun thing you can do, but then you can concurrently have the commercial validation and customers telling you the things that they need to be built for them next to solve commercial pain points for them. So I really do think that you're right by calling this a new category and it really is the best of both worlds. >> It's a great call out, it's a great call out. In fact, I always juggle with the VC. I'm like, it's so easy. Your job is so easy to pick the winners. What are you talking about its so easy? I go, just watch what the developers jump on. And it's not about who started, it could be someone in the dorm room to the boardroom person. You don't know because that B to C, the C, it's B to D you know? You know it's developer 'cause that's a human right? That's a consumer of the tool which influences the business that never was there before. So I think this direct business model evolution, whether it's media going direct or going direct to the developers rather than going to a gatekeeper, this is the reality. >> That's right. >> Well I got to ask you while we got some time left to describe, I want to get into this topic of multi-modality, okay? And can you describe what that means in computer vision? And what's the state of the growth of that portion of this piece? >> Multi modality refers to using multiple traditionally siloed problem types, meaning text, image, video, audio. So you could treat an audio problem as only processing audio signal. That is not multimodal, but you could use the audio signal at the same time as a video feed. Now you're talking about multi modality. In computer vision, multi modality is predominantly happening with images and text. And one of the biggest releases in this space is actually two years old now, was clip, contrastive language image pre-training, which took 400 million image text pairs and basically instead of previously when you do classification, you basically map every single image to a single class, right? Like here's a bunch of images of chairs, here's a bunch of images of dogs. What clip did is used, you can think about it like, the class for an image being the Instagram caption for the image. So it's not one single thing. And by training on understanding the corpora, you basically see which words, which concepts are associated with which pixels. And this opens up the aperture for the types of problems and generalizability of models. So what does this mean? This means that you can get to value more quickly from an existing trained model, or at least validate that what you want to tackle with a computer vision, you can get there more quickly. It also opens up the, I mean. Clip has been the bedrock of some of the generative image techniques that have come to bear, just as much as some of the LLMs. And increasingly we're going to see more and more of multi modality being a theme simply because at its core, you're including more context into what you're trying to understand about the world. I mean, in its most basic sense, you could ask yourself, if I have an image, can I know more about that image with just the pixels? Or if I have the image and the sound of when that image was captured or it had someone describe what they see in that image when the image was captured, which one's going to be able to get you more signal? And so multi modality helps expand the ability for us to understand signal processing. >> Awesome. And can you just real quick, define clip for the folks that don't know what that means? >> Yeah. Clip is a model architecture, it's an acronym for contrastive language image pre-training and like, you know, model architectures that have come before it captures the almost like, models are kind of like brands. So I guess it's a brand of a model where you've done these 400 million image text pairs to match up which visual concepts are associated with which text concepts. And there have been new releases of clip, just at bigger sizes of bigger encoding's, of longer strings of texture, or larger image windows. But it's been a really exciting advancement that OpenAI released in January, 2021. >> All right, well great stuff. We got a couple minutes left. Just I want to get into more of a company-specific question around culture. All startups have, you know, some sort of cultural vibe. You know, Intel has Moore's law doubles every whatever, six months. What's your culture like at RoboFlow? I mean, if you had to describe that culture, obviously love the hacking story, you and your partner with the games going number one on Product Hunt next to Elon and Tesla and then hey, we should start a company two years later. That's kind of like a curious, inventing, building, hard charging, but laid back. That's my take. How would you describe the culture? >> I think that you're right. The culture that we have is one of shipping, making things. So every week each team shares what they did for our customers on a weekly basis. And we have such a strong emphasis on being better week over week that those sorts of things compound. So one big emphasis in our culture is getting things done, shipping, doing things for our customers. The second is we're an incredibly transparent place to work. For example, how we think about giving decisions, where we're progressing against our goals, what problems are biggest and most important for the company is all open information for those that are inside the company to know and progress against. The third thing that I'd use to describe our culture is one that thrives with autonomy. So RoboFlow has a number of individuals who have founded companies before, some of which have sold their businesses for a hundred million plus upon exit. And the way that we've been able to attract talent like that is because the problems that we're tackling are so immense, yet individuals are able to charge at it with the way that they think is best. And this is what pairs well with transparency. If you have a strong sense of what the company's goals are, how we're progressing against it, and you have this ownership mentality of what can I do to change or drive progress against that given outcome, then you create a really healthy pairing of, okay cool, here's where the company's progressing. Here's where things are going really well, here's the places that we most need to improve and work on. And if you're inside that company as someone who has a preponderance to be a self-starter and even a history of building entire functions or companies yourself, then you're going to be a place where you can really thrive. You have the inputs of the things where we need to work on to progress the company's goals. And you have the background of someone that is just necessarily a fast moving and ambitious type of individual. So I think the best way to describe it is a transparent place with autonomy and an emphasis on getting things done. >> Getting shit done as they say. Getting stuff done. Great stuff. Hey, final question. Put a plug out there for the company. What are you going to hire? What's your pipeline look like for people? What jobs are open? I'm sure you got hiring all around. Give a quick plug for the company what you're looking for. >> I appreciate you asking. Basically you're either building the product or helping customers be successful with the product. So in the building product category, we have platform engineering roles, machine learning engineering roles, and we're solving some of the hardest and most impactful problems of bringing such a groundbreaking technology to the masses. And so it's a great place to be where you can kind of be your own user as an engineer. And then if you're enabling people to be successful with the products, I mean you're working in a place where there's already such a strong community around it and you can help shape, foster, cultivate, activate, and drive commercial success in that community. So those are roles that tend themselves to being those that build the product for developer advocacy, those that are account executives that are enabling our customers to realize commercial success, and even hybrid roles like we call it field engineering, where you are a technical resource to drive success within customer accounts. And so all this is listed on roboflow.com/careers. And one thing that I actually kind of want to mention John that's kind of novel about the thing that's working at RoboFlow. So there's been a lot of discussion around remote companies and there's been a lot of discussion around in-person companies and do you need to be in the office? And one thing that we've kind of recognized is you can actually chart a third way. You can create a third way which we call satellite, which basically means people can work from where they most like to work and there's clusters of people, regular onsite's. And at RoboFlow everyone gets, for example, $2,500 a year that they can use to spend on visiting coworkers. And so what's sort of organically happened is team numbers have started to pull together these resources and rent out like, lavish Airbnbs for like a week and then everyone kind of like descends in and works together for a week and makes and creates things. And we call this lighthouses because you know, a lighthouse kind of brings ships into harbor and we have an emphasis on shipping. >> Yeah, quality people that are creative and doers and builders. You give 'em some cash and let the self-governing begin, you know? And like, creativity goes through the roof. It's a great story. I think that sums up the culture right there, Joseph. Thanks for sharing that and thanks for this great conversation. I really appreciate it and it's very inspiring. Thanks for coming on. >> Yeah, thanks for having me, John. >> Joseph Nelson, co-founder and CEO of RoboFlow. Hot company, great culture in the right place in a hot area, computer vision. This is going to explode in value. The edge is exploding. More use cases, more development, and developers are driving the change. Check out RoboFlow. This is theCUBE. I'm John Furrier, your host. Thanks for watching. (gentle music)

>> From theCUBE Studios in Palo Alto in Boston, bringing you data-driven insights from theCUBE and ETR. This is Breaking Analysis with Dave Vellante. >> OpenAI The company, and ChatGPT have taken the world by storm. Microsoft reportedly is investing an additional 10 billion dollars into the company. But in our view, while the hype around ChatGPT is justified, we don't believe OpenAI will lock up the market with its first mover advantage. Rather, we believe that success in this market will be directly proportional to the quality and quantity of data that a technology company has at its disposal, and the compute power that it could deploy to run its system. Hello and welcome to this week's Wikibon CUBE insights, powered by ETR. In this Breaking Analysis, we unpack the excitement around ChatGPT, and debate the premise that the company's early entry into the space may not confer winner take all advantage to OpenAI. And to do so, we welcome CUBE collaborator, alum, Sarbjeet Johal, (chuckles) and John Furrier, co-host of the Cube. Great to see you Sarbjeet, John. Really appreciate you guys coming to the program. >> Great to be on. >> Okay, so what is ChatGPT? Well, actually we asked ChatGPT, what is ChatGPT? So here's what it said. ChatGPT is a state-of-the-art language model developed by OpenAI that can generate human-like text. It could be fine tuned for a variety of language tasks, such as conversation, summarization, and language translation. So I asked it, give it to me in 50 words or less. How did it do? Anything to add? >> Yeah, think it did good. It's large language model, like previous models, but it started applying the transformers sort of mechanism to focus on what prompt you have given it to itself. And then also the what answer it gave you in the first, sort of, one sentence or two sentences, and then introspect on itself, like what I have already said to you. And so just work on that. So it it's self sort of focus if you will. It does, the transformers help the large language models to do that. >> So to your point, it's a large language model, and GPT stands for generative pre-trained transformer. >> And if you put the definition back up there again, if you put it back up on the screen, let's see it back up. Okay, it actually missed the large, word large. So one of the problems with ChatGPT, it's not always accurate. It's actually a large language model, and it says state of the art language model. And if you look at Google, Google has dominated AI for many times and they're well known as being the best at this. And apparently Google has their own large language model, LLM, in play and have been holding it back to release because of backlash on the accuracy. Like just in that example you showed is a great point. They got almost right, but they missed the key word. >> You know what's funny about that John, is I had previously asked it in my prompt to give me it in less than a hundred words, and it was too long, I said I was too long for Breaking Analysis, and there it went into the fact that it's a large language model. So it largely, it gave me a really different answer the, for both times. So, but it's still pretty amazing for those of you who haven't played with it yet. And one of the best examples that I saw was Ben Charrington from This Week In ML AI podcast. And I stumbled on this thanks to Brian Gracely, who was listening to one of his Cloudcasts. Basically what Ben did is he took, he prompted ChatGPT to interview ChatGPT, and he simply gave the system the prompts, and then he ran the questions and answers into this avatar builder and sped it up 2X so it didn't sound like a machine. And voila, it was amazing. So John is ChatGPT going to take over as a cube host? >> Well, I was thinking, we get the questions in advance sometimes from PR people. We should actually just plug it in ChatGPT, add it to our notes, and saying, "Is this good enough for you? Let's ask the real question." So I think, you know, I think there's a lot of heavy lifting that gets done. I think the ChatGPT is a phenomenal revolution. I think it highlights the use case. Like that example we showed earlier. It gets most of it right. So it's directionally correct and it feels like it's an answer, but it's not a hundred percent accurate. And I think that's where people are seeing value in it. Writing marketing, copy, brainstorming, guest list, gift list for somebody. Write me some lyrics to a song. Give me a thesis about healthcare policy in the United States. It'll do a bang up job, and then you got to go in and you can massage it. So we're going to do three quarters of the work. That's why plagiarism and schools are kind of freaking out. And that's why Microsoft put 10 billion in, because why wouldn't this be a feature of Word, or the OS to help it do stuff on behalf of the user. So linguistically it's a beautiful thing. You can input a string and get a good answer. It's not a search result. >> And we're going to get your take on on Microsoft and, but it kind of levels the playing- but ChatGPT writes better than I do, Sarbjeet, and I know you have some good examples too. You mentioned the Reed Hastings example. >> Yeah, I was listening to Reed Hastings fireside chat with ChatGPT, and the answers were coming as sort of voice, in the voice format. And it was amazing what, he was having very sort of philosophy kind of talk with the ChatGPT, the longer sentences, like he was going on, like, just like we are talking, he was talking for like almost two minutes and then ChatGPT was answering. It was not one sentence question, and then a lot of answers from ChatGPT and yeah, you're right. I, this is our ability. I've been thinking deep about this since yesterday, we talked about, like, we want to do this segment. The data is fed into the data model. It can be the current data as well, but I think that, like, models like ChatGPT, other companies will have those too. They can, they're democratizing the intelligence, but they're not creating intelligence yet, definitely yet I can say that. They will give you all the finite answers. Like, okay, how do you do this for loop in Java, versus, you know, C sharp, and as a programmer you can do that, in, but they can't tell you that, how to write a new algorithm or write a new search algorithm for you. They cannot create a secretive code for you to- >> Not yet. >> Have competitive advantage. >> Not yet, not yet. >> but you- >> Can Google do that today? >> No one really can. The reasoning side of the data is, we talked about at our Supercloud event, with Zhamak Dehghani who's was CEO of, now of Nextdata. This next wave of data intelligence is going to come from entrepreneurs that are probably cross discipline, computer science and some other discipline. But they're going to be new things, for example, data, metadata, and data. It's hard to do reasoning like a human being, so that needs more data to train itself. So I think the first gen of this training module for the large language model they have is a corpus of text. Lot of that's why blog posts are, but the facts are wrong and sometimes out of context, because that contextual reasoning takes time, it takes intelligence. So machines need to become intelligent, and so therefore they need to be trained. So you're going to start to see, I think, a lot of acceleration on training the data sets. And again, it's only as good as the data you can get. And again, proprietary data sets will be a huge winner. Anyone who's got a large corpus of content, proprietary content like theCUBE or SiliconANGLE as a publisher will benefit from this. Large FinTech companies, anyone with large proprietary data will probably be a big winner on this generative AI wave, because it just, it will eat that up, and turn that back into something better. So I think there's going to be a lot of interesting things to look at here. And certainly productivity's going to be off the charts for vanilla and the internet is going to get swarmed with vanilla content. So if you're in the content business, and you're an original content producer of any kind, you're going to be not vanilla, so you're going to be better. So I think there's so much at play Dave (indistinct). >> I think the playing field has been risen, so we- >> Risen and leveled? >> Yeah, and leveled to certain extent. So it's now like that few people as consumers, as consumers of AI, we will have a advantage and others cannot have that advantage. So it will be democratized. That's, I'm sure about that. But if you take the example of calculator, when the calculator came in, and a lot of people are, "Oh, people can't do math anymore because calculator is there." right? So it's a similar sort of moment, just like a calculator for the next level. But, again- >> I see it more like open source, Sarbjeet, because like if you think about what ChatGPT's doing, you do a query and it comes from somewhere the value of a post from ChatGPT is just a reuse of AI. The original content accent will be come from a human. So if I lay out a paragraph from ChatGPT, did some heavy lifting on some facts, I check the facts, save me about maybe- >> Yeah, it's productive. >> An hour writing, and then I write a killer two, three sentences of, like, sharp original thinking or critical analysis. I then took that body of work, open source content, and then laid something on top of it. >> And Sarbjeet's example is a good one, because like if the calculator kids don't do math as well anymore, the slide rule, remember we had slide rules as kids, remember we first started using Waze, you know, we were this minority and you had an advantage over other drivers. Now Waze is like, you know, social traffic, you know, navigation, everybody had, you know- >> All the back roads are crowded. >> They're car crowded. (group laughs) Exactly. All right, let's, let's move on. What about this notion that futurist Ray Amara put forth and really Amara's Law that we're showing here, it's, the law is we, you know, "We tend to overestimate the effect of technology in the short run and underestimate it in the long run." Is that the case, do you think, with ChatGPT? What do you think Sarbjeet? >> I think that's true actually. There's a lot of, >> We don't debate this. >> There's a lot of awe, like when people see the results from ChatGPT, they say what, what the heck? Like, it can do this? But then if you use it more and more and more, and I ask the set of similar question, not the same question, and it gives you like same answer. It's like reading from the same bucket of text in, the interior read (indistinct) where the ChatGPT, you will see that in some couple of segments. It's very, it sounds so boring that the ChatGPT is coming out the same two sentences every time. So it is kind of good, but it's not as good as people think it is right now. But we will have, go through this, you know, hype sort of cycle and get realistic with it. And then in the long term, I think it's a great thing in the short term, it's not something which will (indistinct) >> What's your counter point? You're saying it's not. >> I, no I think the question was, it's hyped up in the short term and not it's underestimated long term. That's what I think what he said, quote. >> Yes, yeah. That's what he said. >> Okay, I think that's wrong with this, because this is a unique, ChatGPT is a unique kind of impact and it's very generational. People have been comparing it, I have been comparing to the internet, like the web, web browser Mosaic and Netscape, right, Navigator. I mean, I clearly still remember the days seeing Navigator for the first time, wow. And there weren't not many sites you could go to, everyone typed in, you know, cars.com, you know. >> That (indistinct) wasn't that overestimated, the overhyped at the beginning and underestimated. >> No, it was, it was underestimated long run, people thought. >> But that Amara's law. >> That's what is. >> No, they said overestimated? >> Overestimated near term underestimated- overhyped near term, underestimated long term. I got, right I mean? >> Well, I, yeah okay, so I would then agree, okay then- >> We were off the charts about the internet in the early days, and it actually exceeded our expectations. >> Well there were people who were, like, poo-pooing it early on. So when the browser came out, people were like, "Oh, the web's a toy for kids." I mean, in 1995 the web was a joke, right? So '96, you had online populations growing, so you had structural changes going on around the browser, internet population. And then that replaced other things, direct mail, other business activities that were once analog then went to the web, kind of read only as you, as we always talk about. So I think that's a moment where the hype long term, the smart money, and the smart industry experts all get the long term. And in this case, there's more poo-pooing in the short term. "Ah, it's not a big deal, it's just AI." I've heard many people poo-pooing ChatGPT, and a lot of smart people saying, "No this is next gen, this is different and it's only going to get better." So I think people are estimating a big long game on this one. >> So you're saying it's bifurcated. There's those who say- >> Yes. >> Okay, all right, let's get to the heart of the premise, and possibly the debate for today's episode. Will OpenAI's early entry into the market confer sustainable competitive advantage for the company. And if you look at the history of tech, the technology industry, it's kind of littered with first mover failures. Altair, IBM, Tandy, Commodore, they and Apple even, they were really early in the PC game. They took a backseat to Dell who came in the scene years later with a better business model. Netscape, you were just talking about, was all the rage in Silicon Valley, with the first browser, drove up all the housing prices out here. AltaVista was the first search engine to really, you know, index full text. >> Owned by Dell, I mean DEC. >> Owned by Digital. >> Yeah, Digital Equipment >> Compaq bought it. And of course as an aside, Digital, they wanted to showcase their hardware, right? Their super computer stuff. And then so Friendster and MySpace, they came before Facebook. The iPhone certainly wasn't the first mobile device. So lots of failed examples, but there are some recent successes like AWS and cloud. >> You could say smartphone. So I mean. >> Well I know, and you can, we can parse this so we'll debate it. Now Twitter, you could argue, had first mover advantage. You kind of gave me that one John. Bitcoin and crypto clearly had first mover advantage, and sustaining that. Guys, will OpenAI make it to the list on the right with ChatGPT, what do you think? >> I think categorically as a company, it probably won't, but as a category, I think what they're doing will, so OpenAI as a company, they get funding, there's power dynamics involved. Microsoft put a billion dollars in early on, then they just pony it up. Now they're reporting 10 billion more. So, like, if the browsers, Microsoft had competitive advantage over Netscape, and used monopoly power, and convicted by the Department of Justice for killing Netscape with their monopoly, Netscape should have had won that battle, but Microsoft killed it. In this case, Microsoft's not killing it, they're buying into it. So I think the embrace extend Microsoft power here makes OpenAI vulnerable for that one vendor solution. So the AI as a company might not make the list, but the category of what this is, large language model AI, is probably will be on the right hand side. >> Okay, we're going to come back to the government intervention and maybe do some comparisons, but what are your thoughts on this premise here? That, it will basically set- put forth the premise that it, that ChatGPT, its early entry into the market will not confer competitive advantage to >> For OpenAI. >> To Open- Yeah, do you agree with that? >> I agree with that actually. It, because Google has been at it, and they have been holding back, as John said because of the scrutiny from the Fed, right, so- >> And privacy too. >> And the privacy and the accuracy as well. But I think Sam Altman and the company on those guys, right? They have put this in a hasty way out there, you know, because it makes mistakes, and there are a lot of questions around the, sort of, where the content is coming from. You saw that as your example, it just stole the content, and without your permission, you know? >> Yeah. So as quick this aside- >> And it codes on people's behalf and the, those codes are wrong. So there's a lot of, sort of, false information it's putting out there. So it's a very vulnerable thing to do what Sam Altman- >> So even though it'll get better, others will compete. >> So look, just side note, a term which Reid Hoffman used a little bit. Like he said, it's experimental launch, like, you know, it's- >> It's pretty damn good. >> It is clever because according to Sam- >> It's more than clever. It's good. >> It's awesome, if you haven't used it. I mean you write- you read what it writes and you go, "This thing writes so well, it writes so much better than you." >> The human emotion drives that too. I think that's a big thing. But- >> I Want to add one more- >> Make your last point. >> Last one. Okay. So, but he's still holding back. He's conducting quite a few interviews. If you want to get the gist of it, there's an interview with StrictlyVC interview from yesterday with Sam Altman. Listen to that one it's an eye opening what they want- where they want to take it. But my last one I want to make it on this point is that Satya Nadella yesterday did an interview with Wall Street Journal. I think he was doing- >> You were not impressed. >> I was not impressed because he was pushing it too much. So Sam Altman's holding back so there's less backlash. >> Got 10 billion reasons to push. >> I think he's almost- >> Microsoft just laid off 10000 people. Hey ChatGPT, find me a job. You know like. (group laughs) >> He's overselling it to an extent that I think it will backfire on Microsoft. And he's over promising a lot of stuff right now, I think. I don't know why he's very jittery about all these things. And he did the same thing during Ignite as well. So he said, "Oh, this AI will write code for you and this and that." Like you called him out- >> The hyperbole- >> During your- >> from Satya Nadella, he's got a lot of hyperbole. (group talks over each other) >> All right, Let's, go ahead. >> Well, can I weigh in on the whole- >> Yeah, sure. >> Microsoft thing on whether OpenAI, here's the take on this. I think it's more like the browser moment to me, because I could relate to that experience with ChatG, personally, emotionally, when I saw that, and I remember vividly- >> You mean that aha moment (indistinct). >> Like this is obviously the future. Anything else in the old world is dead, website's going to be everywhere. It was just instant dot connection for me. And a lot of other smart people who saw this. Lot of people by the way, didn't see it. Someone said the web's a toy. At the company I was worked for at the time, Hewlett Packard, they like, they could have been in, they had invented HTML, and so like all this stuff was, like, they just passed, the web was just being passed over. But at that time, the browser got better, more websites came on board. So the structural advantage there was online web usage was growing, online user population. So that was growing exponentially with the rise of the Netscape browser. So OpenAI could stay on the right side of your list as durable, if they leverage the category that they're creating, can get the scale. And if they can get the scale, just like Twitter, that failed so many times that they still hung around. So it was a product that was always successful, right? So I mean, it should have- >> You're right, it was terrible, we kept coming back. >> The fail whale, but it still grew. So OpenAI has that moment. They could do it if Microsoft doesn't meddle too much with too much power as a vendor. They could be the Netscape Navigator, without the anti-competitive behavior of somebody else. So to me, they have the pole position. So they have an opportunity. So if not, if they don't execute, then there's opportunity. There's not a lot of barriers to entry, vis-a-vis say the CapEx of say a cloud company like AWS. You can't replicate that, Many have tried, but I think you can replicate OpenAI. >> And we're going to talk about that. Okay, so real quick, I want to bring in some ETR data. This isn't an ETR heavy segment, only because this so new, you know, they haven't coverage yet, but they do cover AI. So basically what we're seeing here is a slide on the vertical axis's net score, which is a measure of spending momentum, and in the horizontal axis's is presence in the dataset. Think of it as, like, market presence. And in the insert right there, you can see how the dots are plotted, the two columns. And so, but the key point here that we want to make, there's a bunch of companies on the left, is he like, you know, DataRobot and C3 AI and some others, but the big whales, Google, AWS, Microsoft, are really dominant in this market. So that's really the key takeaway that, can we- >> I notice IBM is way low. >> Yeah, IBM's low, and actually bring that back up and you, but then you see Oracle who actually is injecting. So I guess that's the other point is, you're not necessarily going to go buy AI, and you know, build your own AI, you're going to, it's going to be there and, it, Salesforce is going to embed it into its platform, the SaaS companies, and you're going to purchase AI. You're not necessarily going to build it. But some companies obviously are. >> I mean to quote IBM's general manager Rob Thomas, "You can't have AI with IA." information architecture and David Flynn- >> You can't Have AI without IA >> without, you can't have AI without IA. You can't have, if you have an Information Architecture, you then can power AI. Yesterday David Flynn, with Hammersmith, was on our Supercloud. He was pointing out that the relationship of storage, where you store things, also impacts the data and stressablity, and Zhamak from Nextdata, she was pointing out that same thing. So the data problem factors into all this too, Dave. >> So you got the big cloud and internet giants, they're all poised to go after this opportunity. Microsoft is investing up to 10 billion. Google's code red, which was, you know, the headline in the New York Times. Of course Apple is there and several alternatives in the market today. Guys like Chinchilla, Bloom, and there's a company Jasper and several others, and then Lena Khan looms large and the government's around the world, EU, US, China, all taking notice before the market really is coalesced around a single player. You know, John, you mentioned Netscape, they kind of really, the US government was way late to that game. It was kind of game over. And Netscape, I remember Barksdale was like, "Eh, we're going to be selling software in the enterprise anyway." and then, pshew, the company just dissipated. So, but it looks like the US government, especially with Lena Khan, they're changing the definition of antitrust and what the cause is to go after people, and they're really much more aggressive. It's only what, two years ago that (indistinct). >> Yeah, the problem I have with the federal oversight is this, they're always like late to the game, and they're slow to catch up. So in other words, they're working on stuff that should have been solved a year and a half, two years ago around some of the social networks hiding behind some of the rules around open web back in the days, and I think- >> But they're like 15 years late to that. >> Yeah, and now they got this new thing on top of it. So like, I just worry about them getting their fingers. >> But there's only two years, you know, OpenAI. >> No, but the thing (indistinct). >> No, they're still fighting other battles. But the problem with government is that they're going to label Big Tech as like a evil thing like Pharma, it's like smoke- >> You know Lena Khan wants to kill Big Tech, there's no question. >> So I think Big Tech is getting a very seriously bad rap. And I think anything that the government does that shades darkness on tech, is politically motivated in most cases. You can almost look at everything, and my 80 20 rule is in play here. 80% of the government activity around tech is bullshit, it's politically motivated, and the 20% is probably relevant, but off the mark and not organized. >> Well market forces have always been the determining factor of success. The governments, you know, have been pretty much failed. I mean you look at IBM's antitrust, that, what did that do? The market ultimately beat them. You look at Microsoft back in the day, right? Windows 95 was peaking, the government came in. But you know, like you said, they missed the web, right, and >> so they were hanging on- >> There's nobody in government >> to Windows. >> that actually knows- >> And so, you, I think you're right. It's market forces that are going to determine this. But Sarbjeet, what do you make of Microsoft's big bet here, you weren't impressed with with Nadella. How do you think, where are they going to apply it? Is this going to be a Hail Mary for Bing, or is it going to be applied elsewhere? What do you think. >> They are saying that they will, sort of, weave this into their products, office products, productivity and also to write code as well, developer productivity as well. That's a big play for them. But coming back to your antitrust sort of comments, right? I believe the, your comment was like, oh, fed was late 10 years or 15 years earlier, but now they're two years. But things are moving very fast now as compared to they used to move. >> So two years is like 10 Years. >> Yeah, two years is like 10 years. Just want to make that point. (Dave laughs) This thing is going like wildfire. Any new tech which comes in that I think they're going against distribution channels. Lina Khan has commented time and again that the marketplace model is that she wants to have some grip on. Cloud marketplaces are a kind of monopolistic kind of way. >> I don't, I don't see this, I don't see a Chat AI. >> You told me it's not Bing, you had an interesting comment. >> No, no. First of all, this is great from Microsoft. If you're Microsoft- >> Why? >> Because Microsoft doesn't have the AI chops that Google has, right? Google is got so much core competency on how they run their search, how they run their backends, their cloud, even though they don't get a lot of cloud market share in the enterprise, they got a kick ass cloud cause they needed one. >> Totally. >> They've invented SRE. I mean Google's development and engineering chops are off the scales, right? Amazon's got some good chops, but Google's got like 10 times more chops than AWS in my opinion. Cloud's a whole different story. Microsoft gets AI, they get a playbook, they get a product they can render into, the not only Bing, productivity software, helping people write papers, PowerPoint, also don't forget the cloud AI can super help. We had this conversation on our Supercloud event, where AI's going to do a lot of the heavy lifting around understanding observability and managing service meshes, to managing microservices, to turning on and off applications, and or maybe writing code in real time. So there's a plethora of use cases for Microsoft to deploy this. combined with their R and D budgets, they can then turbocharge more research, build on it. So I think this gives them a car in the game, Google may have pole position with AI, but this puts Microsoft right in the game, and they already have a lot of stuff going on. But this just, I mean everything gets lifted up. Security, cloud, productivity suite, everything. >> What's under the hood at Google, and why aren't they talking about it? I mean they got to be freaked out about this. No? Or do they have kind of a magic bullet? >> I think they have the, they have the chops definitely. Magic bullet, I don't know where they are, as compared to the ChatGPT 3 or 4 models. Like they, but if you look at the online sort of activity and the videos put out there from Google folks, Google technology folks, that's account you should look at if you are looking there, they have put all these distinctions what ChatGPT 3 has used, they have been talking about for a while as well. So it's not like it's a secret thing that you cannot replicate. As you said earlier, like in the beginning of this segment, that anybody who has more data and the capacity to process that data, which Google has both, I think they will win this. >> Obviously living in Palo Alto where the Google founders are, and Google's headquarters next town over we have- >> We're so close to them. We have inside information on some of the thinking and that hasn't been reported by any outlet yet. And that is, is that, from what I'm hearing from my sources, is Google has it, they don't want to release it for many reasons. One is it might screw up their search monopoly, one, two, they're worried about the accuracy, 'cause Google will get sued. 'Cause a lot of people are jamming on this ChatGPT as, "Oh it does everything for me." when it's clearly not a hundred percent accurate all the time. >> So Lina Kahn is looming, and so Google's like be careful. >> Yeah so Google's just like, this is the third, could be a third rail. >> But the first thing you said is a concern. >> Well no. >> The disruptive (indistinct) >> What they will do is do a Waymo kind of thing, where they spin out a separate company. >> They're doing that. >> The discussions happening, they're going to spin out the separate company and put it over there, and saying, "This is AI, got search over there, don't touch that search, 'cause that's where all the revenue is." (chuckles) >> So, okay, so that's how they deal with the Clay Christensen dilemma. What's the business model here? I mean it's not advertising, right? Is it to charge you for a query? What, how do you make money at this? >> It's a good question, I mean my thinking is, first of all, it's cool to type stuff in and see a paper get written, or write a blog post, or gimme a marketing slogan for this or that or write some code. I think the API side of the business will be critical. And I think Howie Xu, I know you're going to reference some of his comments yesterday on Supercloud, I think this brings a whole 'nother user interface into technology consumption. I think the business model, not yet clear, but it will probably be some sort of either API and developer environment or just a straight up free consumer product, with some sort of freemium backend thing for business. >> And he was saying too, it's natural language is the way in which you're going to interact with these systems. >> I think it's APIs, it's APIs, APIs, APIs, because these people who are cooking up these models, and it takes a lot of compute power to train these and to, for inference as well. Somebody did the analysis on the how many cents a Google search costs to Google, and how many cents the ChatGPT query costs. It's, you know, 100x or something on that. You can take a look at that. >> A 100x on which side? >> You're saying two orders of magnitude more expensive for ChatGPT >> Much more, yeah. >> Than for Google. >> It's very expensive. >> So Google's got the data, they got the infrastructure and they got, you're saying they got the cost (indistinct) >> No actually it's a simple query as well, but they are trying to put together the answers, and they're going through a lot more data versus index data already, you know. >> Let me clarify, you're saying that Google's version of ChatGPT is more efficient? >> No, I'm, I'm saying Google search results. >> Ah, search results. >> What are used to today, but cheaper. >> But that, does that, is that going to confer advantage to Google's large language (indistinct)? >> It will, because there were deep science (indistinct). >> Google, I don't think Google search is doing a large language model on their search, it's keyword search. You know, what's the weather in Santa Cruz? Or how, what's the weather going to be? Or you know, how do I find this? Now they have done a smart job of doing some things with those queries, auto complete, re direct navigation. But it's, it's not entity. It's not like, "Hey, what's Dave Vellante thinking this week in Breaking Analysis?" ChatGPT might get that, because it'll get your Breaking Analysis, it'll synthesize it. There'll be some, maybe some clips. It'll be like, you know, I mean. >> Well I got to tell you, I asked ChatGPT to, like, I said, I'm going to enter a transcript of a discussion I had with Nir Zuk, the CTO of Palo Alto Networks, And I want you to write a 750 word blog. I never input the transcript. It wrote a 750 word blog. It attributed quotes to him, and it just pulled a bunch of stuff that, and said, okay, here it is. It talked about Supercloud, it defined Supercloud. >> It's made, it makes you- >> Wow, But it was a big lie. It was fraudulent, but still, blew me away. >> Again, vanilla content and non accurate content. So we are going to see a surge of misinformation on steroids, but I call it the vanilla content. Wow, that's just so boring, (indistinct). >> There's so many dangers. >> Make your point, cause we got to, almost out of time. >> Okay, so the consumption, like how do you consume this thing. As humans, we are consuming it and we are, like, getting a nicely, like, surprisingly shocked, you know, wow, that's cool. It's going to increase productivity and all that stuff, right? And on the danger side as well, the bad actors can take hold of it and create fake content and we have the fake sort of intelligence, if you go out there. So that's one thing. The second thing is, we are as humans are consuming this as language. Like we read that, we listen to it, whatever format we consume that is, but the ultimate usage of that will be when the machines can take that output from likes of ChatGPT, and do actions based on that. The robots can work, the robot can paint your house, we were talking about, right? Right now we can't do that. >> Data apps. >> So the data has to be ingested by the machines. It has to be digestible by the machines. And the machines cannot digest unorganized data right now, we will get better on the ingestion side as well. So we are getting better. >> Data, reasoning, insights, and action. >> I like that mall, paint my house. >> So, okay- >> By the way, that means drones that'll come in. Spray painting your house. >> Hey, it wasn't too long ago that robots couldn't climb stairs, as I like to point out. Okay, and of course it's no surprise the venture capitalists are lining up to eat at the trough, as I'd like to say. Let's hear, you'd referenced this earlier, John, let's hear what AI expert Howie Xu said at the Supercloud event, about what it takes to clone ChatGPT. Please, play the clip. >> So one of the VCs actually asked me the other day, right? "Hey, how much money do I need to spend, invest to get a, you know, another shot to the openAI sort of the level." You know, I did a (indistinct) >> Line up. >> A hundred million dollar is the order of magnitude that I came up with, right? You know, not a billion, not 10 million, right? So a hundred- >> Guys a hundred million dollars, that's an astoundingly low figure. What do you make of it? >> I was in an interview with, I was interviewing, I think he said hundred million or so, but in the hundreds of millions, not a billion right? >> You were trying to get him up, you were like "Hundreds of millions." >> Well I think, I- >> He's like, eh, not 10, not a billion. >> Well first of all, Howie Xu's an expert machine learning. He's at Zscaler, he's a machine learning AI guy. But he comes from VMware, he's got his technology pedigrees really off the chart. Great friend of theCUBE and kind of like a CUBE analyst for us. And he's smart. He's right. I think the barriers to entry from a dollar standpoint are lower than say the CapEx required to compete with AWS. Clearly, the CapEx spending to build all the tech for the run a cloud. >> And you don't need a huge sales force. >> And in some case apps too, it's the same thing. But I think it's not that hard. >> But am I right about that? You don't need a huge sales force either. It's, what, you know >> If the product's good, it will sell, this is a new era. The better mouse trap will win. This is the new economics in software, right? So- >> Because you look at the amount of money Lacework, and Snyk, Snowflake, Databrooks. Look at the amount of money they've raised. I mean it's like a billion dollars before they get to IPO or more. 'Cause they need promotion, they need go to market. You don't need (indistinct) >> OpenAI's been working on this for multiple five years plus it's, hasn't, wasn't born yesterday. Took a lot of years to get going. And Sam is depositioning all the success, because he's trying to manage expectations, To your point Sarbjeet, earlier. It's like, yeah, he's trying to "Whoa, whoa, settle down everybody, (Dave laughs) it's not that great." because he doesn't want to fall into that, you know, hero and then get taken down, so. >> It may take a 100 million or 150 or 200 million to train the model. But to, for the inference to, yeah to for the inference machine, It will take a lot more, I believe. >> Give it, so imagine, >> Because- >> Go ahead, sorry. >> Go ahead. But because it consumes a lot more compute cycles and it's certain level of storage and everything, right, which they already have. So I think to compute is different. To frame the model is a different cost. But to run the business is different, because I think 100 million can go into just fighting the Fed. >> Well there's a flywheel too. >> Oh that's (indistinct) >> (indistinct) >> We are running the business, right? >> It's an interesting number, but it's also kind of, like, context to it. So here, a hundred million spend it, you get there, but you got to factor in the fact that the ways companies win these days is critical mass scale, hitting a flywheel. If they can keep that flywheel of the value that they got going on and get better, you can almost imagine a marketplace where, hey, we have proprietary data, we're SiliconANGLE in theCUBE. We have proprietary content, CUBE videos, transcripts. Well wouldn't it be great if someone in a marketplace could sell a module for us, right? We buy that, Amazon's thing and things like that. So if they can get a marketplace going where you can apply to data sets that may be proprietary, you can start to see this become bigger. And so I think the key barriers to entry is going to be success. I'll give you an example, Reddit. Reddit is successful and it's hard to copy, not because of the software. >> They built the moat. >> Because you can, buy Reddit open source software and try To compete. >> They built the moat with their community. >> Their community, their scale, their user expectation. Twitter, we referenced earlier, that thing should have gone under the first two years, but there was such a great emotional product. People would tolerate the fail whale. And then, you know, well that was a whole 'nother thing. >> Then a plane landed in (John laughs) the Hudson and it was over. >> I think verticals, a lot of verticals will build applications using these models like for lawyers, for doctors, for scientists, for content creators, for- >> So you'll have many hundreds of millions of dollars investments that are going to be seeping out. If, all right, we got to wrap, if you had to put odds on it that that OpenAI is going to be the leader, maybe not a winner take all leader, but like you look at like Amazon and cloud, they're not winner take all, these aren't necessarily winner take all markets. It's not necessarily a zero sum game, but let's call it winner take most. What odds would you give that open AI 10 years from now will be in that position. >> If I'm 0 to 10 kind of thing? >> Yeah, it's like horse race, 3 to 1, 2 to 1, even money, 10 to 1, 50 to 1. >> Maybe 2 to 1, >> 2 to 1, that's pretty low odds. That's basically saying they're the favorite, they're the front runner. Would you agree with that? >> I'd say 4 to 1. >> Yeah, I was going to say I'm like a 5 to 1, 7 to 1 type of person, 'cause I'm a skeptic with, you know, there's so much competition, but- >> I think they're definitely the leader. I mean you got to say, I mean. >> Oh there's no question. There's no question about it. >> The question is can they execute? >> They're not Friendster, is what you're saying. >> They're not Friendster and they're more like Twitter and Reddit where they have momentum. If they can execute on the product side, and if they don't stumble on that, they will continue to have the lead. >> If they say stay neutral, as Sam is, has been saying, that, hey, Microsoft is one of our partners, if you look at their company model, how they have structured the company, then they're going to pay back to the investors, like Microsoft is the biggest one, up to certain, like by certain number of years, they're going to pay back from all the money they make, and after that, they're going to give the money back to the public, to the, I don't know who they give it to, like non-profit or something. (indistinct) >> Okay, the odds are dropping. (group talks over each other) That's a good point though >> Actually they might have done that to fend off the criticism of this. But it's really interesting to see the model they have adopted. >> The wildcard in all this, My last word on this is that, if there's a developer shift in how developers and data can come together again, we have conferences around the future of data, Supercloud and meshs versus, you know, how the data world, coding with data, how that evolves will also dictate, 'cause a wild card could be a shift in the landscape around how developers are using either machine learning or AI like techniques to code into their apps, so. >> That's fantastic insight. I can't thank you enough for your time, on the heels of Supercloud 2, really appreciate it. All right, thanks to John and Sarbjeet for the outstanding conversation today. Special thanks to the Palo Alto studio team. My goodness, Anderson, this great backdrop. You guys got it all out here, I'm jealous. And Noah, really appreciate it, Chuck, Andrew Frick and Cameron, Andrew Frick switching, Cameron on the video lake, great job. And Alex Myerson, he's on production, manages the podcast for us, Ken Schiffman as well. Kristen Martin and Cheryl Knight help get the word out on social media and our newsletters. Rob Hof is our editor-in-chief over at SiliconANGLE, does some great editing, thanks to all. Remember, all these episodes are available as podcasts. All you got to do is search Breaking Analysis podcast, wherever you listen. Publish each week on wikibon.com and siliconangle.com. Want to get in touch, email me directly, david.vellante@siliconangle.com or DM me at dvellante, or comment on our LinkedIn post. And by all means, check out etr.ai. They got really great survey data in the enterprise tech business. This is Dave Vellante for theCUBE Insights powered by ETR. Thanks for watching, We'll see you next time on Breaking Analysis. (electronic music)

(soft joyful music) >> Welcome back everyone to the live CUBE coverage here in San Francisco for VMware Explore '22. I'm John Furrier with my host Dave Vellante. Three days of wall to wall live coverage. Two sets here at the CUBE, here on the ground floor in Moscone, and we got VMware and HPE back on the CUBE. Paul Turner, VP of products at vSphere and cloud infrastructure at VMware. Great to see you. And Mark Nickerson, Director of Go to Mark for Compute Solutions at Hewlett-Packard Enterprise. Great to see you guys. Thanks for coming on. >> Yeah. >> Thank you for having us. >> So we, we are seeing a lot of traction with GreenLake, congratulations over there at HPE. The customers changing their business model consumption, starting to see that accelerate. You guys have the deep partnership, we've had you guys on earlier yesterday. Talked about the technology partnership. Now, on the business side, where's the action at with the HP and you guys with the customer? Because, now as they go cloud native, third phase of the inflection point, >> Yep. >> Multi-cloud, hybrid-cloud, steady state. Where's the action at? >> So I think the action comes in a couple of places. Um, one, we see increased scrutiny around, kind of not only the cost model and the reasons for moving to GreenLake that we've all talked about there, but it's really the operational efficiencies as well. And, this is an area where the long term partnership with VMware has really been a huge benefit. We've actually done a lot of joint engineering over the years, continuing to do that co-development as we bring products like Project Monterey, or next generations of VCF solutions, to live in a GreenLake environment. That's an area where customers not only see the benefits of GreenLake from a business standpoint, um, on a consumption model, but also around the efficiency operationally as well. >> Paul, I want to, I want to bring up something that we always talk about on the CUBE, which is experience in the enterprise. Usually it's around, you know, technology strategy, making the right product market fit, but HPE and VMware, I mean, have exceptional depth and experience in the enterprise. You guys have a huge customer base, doesn't churn much, steady state there, you got vSphere, killer product, with a new release coming out, HP, unprecedented, great sales force. Everyone knows that you guys have great experience serving customers. And, it seems like now the fog is clearing, we're seeing clear line of sight into value proposition, you know, what it's worth, how do you make money with it, how do partners make money? So, it seems like the puzzle's coming together right now with consumption, self-service, developer focus. It just seems to be clicking. What's your take on all this because... >> Oh, absolutely. >> you got that engine there at VMware. >> Yeah. I think what customers are looking for, customers want that cloud kind of experience, but they want it on their terms. So, the work that we're actually doing with the GreenLake offerings that we've done, we've released, of course, our subscription offerings that go along with that. But, so, customers can now get cloud on their terms. They can get systems services. They know that they've got the confidence that we have integrated those services really well. We look at something like vSphere 8, we just released it, right? Well, immediately, day zero, we come out, we've got trusted integrated servers from HPE, Mark and his team have done a phenomenal job. We make sure that it's not just the vSphere releases but VSAN and we get VSAN ready nodes available. So, the customers get that trusted side of things. And, you know, just think about it. We've... 200,000 joined customers. >> Yeah, that's a lot. >> We've a hundred thousand kind of enabled partners out there. We've an enormous kind of install base of customers. But also, those customers want us to modernize. And, you know, the fact that we can do that with GreenLake, and then of course with our new features, and our new releases. >> Yeah. And it's nice that the products market fits going well on both sides. But can you guys share, both of you share, the cadence of the relationship? I mean, we're talking about vSphere, every two years, a major release. Now since 6, vSphere 6, you guys are doing three months' releases, which is amazing. So you guys got your act together there, doing great. But, you guys, so many joint customers, what's the cadence? As stuff comes out, how do you guys put that together? How tightly integrated? Can you share a quick... insight into that dynamic? >> Yeah, sure. So, I mean Mark can and add to this too, but the teams actually work very closely, where it's every release that we do is jointly qualified. So that's a really, really important thing. But it's more interesting is this... the innovation side of things. Right? If you just think about it, 'cause it's no use to just qualify. That's not that interesting. But, like I said, we've released with vSphere 8 you know... the new enhanced storage architecture. All right? The new, next generation of vSphere. We've got that immediately qualified, ready on HPE equipment. We built out new AI servers, actually with Invidia and with HPE. And, we're able to actually push the extremes of... AI and intelligence... on systems. So that's kind of work. And then, of course, our Project Monterey work. Project Monterey Distributed Services Engine. That's something we're really excited about, because we're not just building a new server anymore, we're actually going to change the way servers are built. Monterey gives us a new platform to build from that we're actually jointly working. >> So double click on that, and then to explain how HPE is taking advantage of it. I mean, obvious you have more diversity of XPU's, you've got isolation, you've got now better security, and confidential computing, all that stuff. Explain that in some detail, and how does HPE take advantage of that? >> Yeah, definitely. So, if you think about vSphere 8, vSphere 8 I can now virtualize anything. I can virtualize your CPU's, your GPU's, and now what we call DPU's, or data processing units. A data processing unit, it's... think of it as we're running, actually, effectively another version of ESX, sitting down on this processor. But, that gives us an ability to run applications, and some of the virtualization services, actually down on that DPU. It's separated away from where you run your application. So, all your applications get to consume all your CPU. It's all available to you. Your DPU is used for that virtualization and virtualization services. And that's what we've done. We've been working with HPE and HPE and Pensando. Maybe you can talk some of the new systems that we've built around this too. >> Yeah. So, I mean, that's one of the... you talked about the cadence and that... back to the cadence question real briefly. Paul hit on it. Yeah, there's a certain element of, "Let's make sure that we're certified, we're qualified, we're there day zero." But, that cadence goes a lot beyond it. And, I think Project Monterey is a great example of where that cadence expands into really understanding the solutioning that goes into what the customer's expecting from us. So, to Paul's point, yeah, we could have just qualified the ESX version to go run on a DPU and put that in the market and said, "Okay, great. Customers, We know that it works." We've actually worked very tightly with VMware to really understand the use case, what the customer needs out of that operating environment, and then provide, in the first instantiation, three very discrete product solutions aimed at different use cases, whether that's a more robust use case for customers who are looking at data intensive, analytic intensive, environments, other customers might be looking at VDI or even edge applications. And so, we've worked really closely with VMware to engineer solutions specific to those use cases, not just to a qualification of an operating environment, not just a qualification of certain software stack, but really into an understanding of the use case, the customer solution, and how we take that to market with a very distinct point of view alongside our partners. >> And you can configure the processors based on that workload. Is that right? And match the workload characteristics with the infrastructure is that what I'm getting? >> You do, and actually, well, you've got the same flexibility that we've actually built in why you love virtualization, why people love it, right? You've got the ability to kind of bring harness hardware towards your application needs in a very dynamic way. Right? So if you even think about what we built in vSphere 8 from an AI point of view, we're able to scale. We built the ability to actually take network device cards, and GPU cards, you're to able to build those into a kind of composed device. And, you're able to provision those as you're provisioning out VM's. And, the cool thing about that, is you want to be able to get extreme IO performance when you're doing deep learning applications, and you can now do that, and you can do it very dynamically, as part of the provisioning. So, that's the kind of stuff. You've got to really think, like, what's the use case? What's the applications? How do we build it? And, for the DPU side of things, yes, we've looked at how do we take some of our security services, some of our networking services, and we push those services down onto the SmartNIC. It frees up processors. I think the most interesting thing, that you probably saw on the keynote, was we did benchmarks with Reddit databases. We were seeing 20 plus, I'm sure the exact number, I think it was 27%, I have to get exact number, but a 27% latency improvement, to me... I came from the database background, latency's everything. Latency's king. It's not just... >> Well it's... it's number one conversation. >> I mean, we talk about multi-cloud, and as you start getting into hybrid. >> Right. >> Latency, data movement, efficiency, I mean, this is all in the workload mindset that the workhorses that you guys have been working at HPE with the compute, vSphere, this is heart center of the discussion. I mean, it is under the hood, and we're talking about the engine here, right? >> Sure. >> And people care about this stuff, Mark. This is like... Kubernetes only helps this better with containers. I mean, it's all kind of coming together. Where's that developer piece? 'Cause remember, infrastructure is code, what everybody wants. That's the reality. >> Right. Well, I think if you take a look at... at where the Genesis of the desire to have this capability came from, it came directly out of the fact that you take a look at the big cloud providers, and sure, the ability to have a part of that operating environment, separated out of the CPU, free up as much processing as you possibly can, but it was all in this very lockdown proprietary, can't touch it, can't develop on it. The big cloud guys owned it. VMware has come along and said, "Okay, we're going to democratize that. We're going to make this available for the masses. We're opening this up so that developers can optimize workloads, can optimize applications to run in this kind of environment." And so, really it's about bringing that cloud experience, that demand that customers have for that simplicity, that flexibility, that efficiency, and then marrying it with the agility and security of having your on premises or hybrid cloud environment. And VMware is kind of helping with that... >> That's resonating with the customer, I got to imagine. >> Yeah. >> What's the feedback you're hearing? When you talk to customers about that, the like, "Wait a minute, we'd have to like... How long is that going to take? 'Cause that sounds like a one off." >> Yeah. I'll tell you what... >> Everything is a one off now. You could do a one off. It scales. >> What I hear is give me more. We love where we're going in the first instantiation of what we can do with the Distributed Services Engine. We love what we're seeing. How do we do more? How do we drive more workloads in here? How do we get more efficiency? How can we take more of the overhead out of the CPU, free up more cores. And so, it's a tremendously positive response. And then, it's a response that's resonating with, "Love it. Give me more." >> Oh, if you're democratizing, I love that word because it means democratization, but someone's being democratized. Who's... What's... Something when... that means good things are happening, which means someone's not going to be winning out. Who's that? What... >> Well it, it's not necessarily that someone's not winning out. (laughs) What you read, it comes down to... Democratizing means you've got to look at it, making it widely available. It's available to all. And these things... >> No silos. No gatekeepers. Kind of that kind of thing. >> It's a little operationally difficult to use. You've got... Think about the DPU market. It was a divergent market with different vendors going into that market with different kind of operating systems, and that doesn't work. Right? You've got to actually go and virtualize those DPU's. So then, we can actually bring application innovation onto those DPU's. We can actually start using them in smart ways. We did the same thing with GPU's. We made them incredibly easy to use. We virtualized those GPU's, we're able to, you know, you can provision them in a very simple way. And, we did the same thing with Kubernetes. You mentioned about container based applications and modern apps in the one platform now, you can just set a cluster and you can just say, "Hey I want that as a modern apps enabled cluster." And boom. It's done. And, all of the configurations, set up, Kubernetes, it's done for you. >> But the thing that just GreenLake too, the democratization aspect of how that changed the business model unleashes... >> Right. >> ...efficiency and just simplicity. >> Oh yeah, absolutely. >> But the other thing was the 20% savings on the Reddit's benchmark, with no change required at the application level, correct? >> No change at the application level. In the vCenter, you have to set a little flag. >> Okay. You got to tick a box. >> You got to tick a little box... >> So I can live with that. But the point I'm making is that traditionally, we've had... We have an increasing amount of waste to do offloads, and now you're doing them much more efficiently, right? >> Yes. >> Instead of using the traditional x86 way of doing stuff, you're now doing purpose built, applying that to be much more efficient >> Totally agree. And I think it's becoming, it's going to become even more important. Look at, we are... our run times for our applications, We've got to move to a world where we're building completely confidential applications at all time. And that means that they are secured, encrypted, all traffic is encrypted, whether it's storage traffic, whether it's IO traffic, we've got to make sure we've got complete route of trust of the applications. And so, to do all of that is actually a... compute intensive. It just is. And so, I think as we move forward and people build much more complete, confidential, compute secured environments, you're going to be encrypting all traffic all the time. You're going to be doing micro-zoning and firewalling down at the VM level so that you've got the protection. You can take a VM, you can move it up to the cloud, it will inherit all of its policies, will move with it. All of that will take compute capacity. >> Yup. >> The great thing is that the DPU's give us this ability to offload and to use some of that spare compute capacity. >> And isolate so the application chance can't just tunnel in and get access to that >> You guys got so much going on. You can have your own CUBE show, just on the updating, what's going on between the two companies, and then the innovation. We got one minute left. Just quickly, what's the goal in the partnership? What's next? You guys going to be in the field together, doing joint customer work? Is there bigger plans? Is there events out there? What are some of your plans together in the marketplace? >> That's you. >> Yup. So, I think, Paul kind of alluded to it. Talk about the fact that you've got a hundred thousand partners in common. The venn diagram of looking at the HPE channel and the VMware channel, clearly there's an opportunity there to continue to drive a joint, go to market message, through both of our sales organizations, and through our shared channel. We have a 25,000 strong... solution architect... force that we can leverage. So as we get these exciting things to talk about, I mean, you talk about Project Monterey, the Distributed Services Engine. That's big news. There's big news around vSphere 8. And so, having those great things to go talk about with that strong sales team, with that strong channel organization, I think you're going to see a lot stronger partnership between VMware and HPE as we continue to do this joint development and joint selling >> Lots to get enthused about, pretty much there. >> Oh yeah! >> Yeah, I would just add in that we're actually in a very interesting point as well, where Intel's just coming out with Next Rev systems, we're building the next gen of these systems. I think this is a great time for customers to look at that aging infrastructure that they have in place. Now is a time we can look at upgrading it, but when they're moving it, they can move it also to a cloud subscription based model, you know can modernize not just what you have in terms of the capabilities and densify and get much better efficiency, but you can also modernize the way you buy from us and actually move to... >> Real positive change transformation. Checks the boxes there. And put some position for... >> You got it. >> ... cloud native development. >> Absolutely. >> Guys, thanks for coming on the CUBE. Really appreciate you coming out of that busy schedule and coming on and give us the up... But again, we can do a whole show some... all the moving parts and innovation going on with you guys. So thanks for coming on. Appreciate it. Thank you. I'm John Dave Vellante we're back with more live coverage day two, two sets, three days of wall to wall coverage. This is the CUBE at VMware Explorer. We'll be right back.

[Music] hello everyone welcome back to the live coverage here in monaco for the monaco crypto summit i'm john furrier host of thecube uh we have a great great guest lineup here already in nine interviews small gathering of the influencers and the people making it happen powered by digital bits sponsored by digital bits presented by digital bits of course a lot happening around decentralization web 3 the metaverse we've got a a powerhouse influencer on the qb ryan gills the founder of openmeta been in the issue for a while ryan great to see you thanks for coming on great to be here thank you you know one of the things that we were observing earlier conversations is you have young and old coming together the best and brightest right now in the front line it's been there for a couple years you know get some hype cycles going on but that's normal in these early growth markets but still true north star is in play that is democratize remove the intermediaries create immutable power to the people the same kind of theme has been drum beating on now come the metaverse wave which is the nfts now the meta verses you know at the beginning of this next wave yeah this is where we're at right now what are you working on tell us what's what's open meta working on yeah i mean so there is a reason for all of this right i think we go through all these different cycles and there's an economic incentive engine and it's designed in because people really like making money but there's a deeper reason for it all and the words the buzzwords the terms they change based off of different cycles this one is a metaverse i just saw it a little early you know so i recognized the importance of an open metaverse probably in 2017 and really decided to dedicate 10 years to that um so we're very early into that decade and we're starting to see more of a movement building and uh you know i've catalyzed a lot of that from from the beginning and making sure that while everything moves to a closed corporate side of things there's also an equal bottom-up approach which i think is just more important and more interesting well first of all i want to give you a lot of props for seeing it early and recognizing the impact and potential collateral damage of not not having open and i was joking earlier about the facebook little snafu with the the exercise app and ftc getting involved and you know i kind of common new york times guy comment online like hey i remember aol wanted to monopolize dial up internet and look the open web obviously changed all that they went to sign an extinction not the same comparable here but you know everyone wants to have their own little walled guard and they feel comfortable first-party data the data business so balancing the benefit of data and all the ip that could come into whether it's a visualization or platform it has to be open without open then you're going to have fragmentation you're going to have all kinds of perverse incentives how does the metaverse continue with such big players like meta themselves x that new name for facebook you know big bully tons of cash you know looking to you know get their sins forgiven um so to speak i mean you got google probably will come in apple's right around the corner amazon you get the whales out there how do is it proprietary is walled garden the new proprietary how do you view all that because it's it's still early and so there's a lot of change can happen well it's an interesting story that's really playing out in three acts right we had the first act which was really truly open right there was this idea that the internet is for the end user this is all just networking and then web 2 came and we got a lot of really great business models from it and it got closed up you know and now as we enter this sort of third act we have the opportunity to learn from both of those right and so i think web 3 needs to go back to the values of web one with the lessons in hindsight of web 2. and all of the winners from web 2 are clearly going to want to keep winning in web 3. so you can probably guess every single company and corporation on earth will move into this i think most governments will move into it as well and um but they're not the ones that are leading it the ones that are leading it are are just it's a culture of people it's a movement that's building and accumulating over time you know it's weird it's uh the whole web 2 thing is the history is interesting because you know when i started my podcasting company in 2004 there's only like three of us you know the dave weiner me evan williams and jack dorsey and we thought and the blogging just was getting going and the dream was democratization at the time mainstream media was the enemy and then now blogs are media so and then all sudden it like maybe it was the 2008 area with the that recession it stopped and then like facebook came in obviously twitter was formed from the death of odio podcasting company so the moment in time in history was a glimmic glimmer of hope well we went under my company went under we all went under but then that ended and then you had the era of twitter facebook linkedin reddit was still around so it kind of stopped where did it where did it pick up was it the ethereum bitcoin and ethereum brought that back where'd the open come back well it's a generational thing if you if you go back to like you know apple as a startup they were trying to take down ibm right it was always there's always the bigger thing that was that we we're trying to sort of unbundle or unpackage because they have too much power they have too much influence and now you know facebook and apple and these big tech companies they are that on on the planet and they're doing it bigger than it's ever been done but when they were startups they existed to try to take that from a bigger company so i think you know it's not an it's not a fact that like facebook or zuckerberg is is the villain here it's just the fact that we're reaching peak centralization anything past this point it becomes more and more unhealthy right and an open metaverse is just a way to build a solution instead of more of a problem and i think if we do just allow corporations to build and own them on the metaverse these problems will get bigger and larger more significant they will touch more people on earth and we know what that looks like so why not try something different so what's the playbook what's the current architecture of the open meta verse that you see and how do people get involved is there protocols to be developed is there new things that are needed how does the architecture layout take us through that your mindset vision on that and then how can people get involved yeah so the the entity structure of what i do is a company called crucible out of the uk um but i i found out very quickly that just a purely for-profit closed company a commercial company won't achieve this objective there's limitations to that so i run a dao as well out of switzerland it's called open meta we actually we named it this six months before facebook changed their name and so this is just the track we're on right and what we develop is a protocol uh we believe that the internet built by game developers is how you define the metaverse and that protocol is in the dao it is in the dow it's that's crucial crucible protocol open meta okay you can think of crucible as labs okay no we're building we're building everything so incubator kind of r d kind of thing exactly yeah and i'm making the choice to develop things and open them up create public goods out of them harness things that are more of a bottom-up approach you know and what we're developing is the emergence protocol which is basically defining the interface between the wallets and the game engines right so you have unity and unreal which all the game developers are sort of building with and we have built software that drops into those game engines to map ownership between the wallet and the experience in the game so integration layer basically between the wallet kind of how stripe is viewed from a software developer's campaign exactly but done on open rails and being done for a skill set of world building that is coming and game developers are the best suited for this world building and i like to own what i built yeah i don't like other people to own what i build and i think there's an entire generation that's that's really how do you feel about the owning and sharing component is that where you see the scale coming into play here i can own it and scale it through the relationship of the open rails yeah i mean i think the truth is that the open metaverse will be a smaller network than even one corporate virtual world for a while because these companies have billions of people right yeah every room you've ever been in on earth people are using two or three of facebook's products right they just have that adoption but they don't have trust they don't have passion they don't have the movement that you see in web3 they don't have the talent the level of creative talent those people care about owning what they create on the on what can someone get involved with question is that developer is that a sponsor what do people do to get involved with do you and your team and to make it bigger i mean it shouldn't be too small so if this tracks you can assume it gets bigger if you care about an open metaverse you have a seat at the table if you become a member of the dao you have a voice at the table you can make decisions with us we are building developing technology that can be used openly so if you're a game developer and you use unity or unreal we will open the beta this month later and then we move directly into what's called a game jam so a global hackathon for game developers where we just go through a giant exploration of what is possible i mean you think about gaming i always said the early adopters of all technology and the old web one was porn and that was because they were they were agnostic of vendor pitches or whatever is it made money they've worked we don't tell them we've always been first we don't tolerate vaporware gaming is now the new area where it is so the audience doesn't want vapor they want it to work they want technology to be solid they want community so it's now the new arbiter so gaming is the pretext to metaverse clearly gaming is swallowing all of media and probably most of the world and this game mechanics under the hood and all kinds of underlying stuff now how does that shape the developer community so like take the classic software developer may not be a game developer how do they translate over you seeing crossover from the software developers that are out there to be game developers what's your take on that it's an interesting question because i come to a lot of these events and the entire web 3 movement is web developers it's in the name yeah right and we have a whole wave of exploration and nfts being sold of people who really love games they're they're players they're gamers and they're fans of games but they are not in the skill set of game development this is a whole discipline yeah it's a whole expertise right you have to understand ik retargeting rigging bone meshes and mapping of all of that stuff and environment building and rendering and all these things it's it's a stacked skill set and we haven't gone through any exploration yet with them that is the next cycle that we're going to and that's what i've spent the last three or four years preparing for yeah and getting the low code is going to be good i was saying earlier to the young gun we had on his name was um oscar belly he's argo versus he's 25 years old he's like he made a quote i'm too old to get into esports like 22 old 25 come on i'd love to be in esports i was commenting that there could be someone sitting next to us in the metaverse here on tv on our digital tv program in the future that's going to be possible the first party citizenship between physical experience absolutely and meta versus these cameras all are a layer in which you can blend the two yeah so that that's that's going to be coming sooner and it's really more of the innovation around these engines to make it look real and have someone actually moving their body not like a stick figure yes or a lego block this is where most people have overlooked because what you have is you have two worlds you have web 3 web developers who see this opportunity and are really going for it and then you have game developers who are resistant to it for the most part they have not acclimated to this but the game developers are more of the keys to it because they understand how to build worlds yeah they do they understand how to build they know what success looks like they know what success looks like if you if you talk about the metaverse with anyone the most you'll hear is ready player one yeah maybe snow crash but those things feel like games yeah right so the metaverse and gaming are so why are game developers um like holding back is because they're like ah it's too not ready yet i'm two more elite or is it more this is you know this is an episode on its own yeah um i'm actually a part of a documentary if you go to youtube and you say why gamers hate nfts there's a two-part documentary about an hour long that robin schmidt from the defiant did and it's really a very good deep dive into this but i think we're just in a moment in time right now if you remember henry ford when he he produced the car everybody wanted faster horses yeah they didn't understand the cultural shift that was happening they just wanted an incremental improvement right and you can't say that right now because it sounds arrogant but i do believe that this is a moment in time and i think once we get through this cultural shift it will be much more clear why it's important it's not pure speculation yeah it's not clout it's not purely money there's something happening that's important for humanity yeah and if we don't do it openly it will be more of a problem yeah i totally agree with you on that silent impact is number one and people some people just don't see it because it's around the corner visionaries do like yourselves we do my objective over the next say three to six months is to identify which game developers see the value in web 3 and are leaning into it because we've built technology that solves interoperability between engines mapping ownership from wallets all the sort of blueprints that are needed in order for a game developer to build this way we've developed that we just need to identify where are they right because the loudest voices are the ones that are pushing back against this yeah and if you're not on twitter you don't see how many people really see this opportunity and i talked to epic and unity and nvidia and they all agree that this is where the future is going but the one question mark is who wants it where are they you know it's interesting i talked to lauren besel earlier she's from the music background we were talking about open source and how music i found that is not open it's proprietary i was talking about when i was in college i used to deal software you'd be like what do you mean deal well at t source code was proprietary and that started the linux movement in the 80s that became a systems revolution and then open source then just started to accelerate now people like it's free software is like not a big deal everyone knows it's what it was never proprietary but we were fighting the big proprietary code bases you mentioned that earlier is there a proprietary thing for music well not really because it's licensed rights right so in the metaverse who's the proprietary is it the walled garden is the is it is it the gamers so is it the consoles is it the investment that these gaming companies have in the software itself so i find that that open source vibe is very much circulating around your world actually open maps in the word open but open source software has a trajectory you know foundations contributors community building same kind of mindset music not so much because no one's it's not direct comparable but i think here it's interesting the gaming culture could be that that proprietary ibm the the state the playstation the xbox you know if you dive into the modding community right the modding community has sort of been this like gray area of of gaming and they will modify games that already exist but they do it with the values of open source they do it with composability and there's been a few breakthroughs counter-strike is a mod right some of the largest games of all time came from mods of other games look at quake had a comeback i played first multiplayer doom when it came out in the 90s and that was all mod based exactly yeah quake and quake was better but you know i remember the first time on a 1.5 cable mode and playing with my friends remember vividly now the graphics weren't that good but that was mod it's mod so then you go i mean and then you go into these other subcultures like dungeons and dragons which was considered to be such a nerdy thing but it's just a deeply human thing it's a narrative building collective experience like these are all the bottom-up type approaches modding uh world building so you're going to connect so i'm just kind of thinking out loud here you're going to connect the open concept of source with open meta bring game developers and software drills together create a fabric of a baseline somewhat somewhat collected platform tooling and components and let it just sell form see what happens better self form that's your imposing composability is much faster yeah than a closed system and you got what are your current building blocks you have now you have the wallet and you have so we built an sdk on both unity and unreal okay as a part of a system that is a protocol that plugs into those two engines and we have an inventory service we have an avatar system we basically kind of leaned into this idea of a persona being the next step after a pfp so so folks that are out there girls and boys who are sitting there playing games they could build their own game on this thing absolutely this is the opportunity for them entrepreneurs to circumvent the system and go directly with open meta and build their own open environment like i said before i i like to own the things i built i've had that entrepreneurial lesson but i don't think in the future you should be so okay with other companies or other intermediaries owning you and what you build i think i mean opportunity to build value yeah and i think i think your point the mod culture is not so much going to be the answer it's what that was like the the the the dynamic of modding yes is developing yes and then therefore you get the benefit of sovereign identity yeah you get the benefit of unbanking that's not the way we market this but those are benefits that come along with it and it allows you to live a different life and may the better product win yeah i mean that's what you're enabling yeah ryan thanks so much for coming on real final question what's going on here why are we here in monaco what's going on this is the inaugural event presented by digital bits why are we here monaco crypto summit i'm here uh some friends of mine brittany kaiser and and lauren bissell invited me here yeah i've known al for for a number of years and i'm just here to support awesome congratulations and uh we'll keep in touch we'll follow up on the open meta great story we love it thanks for coming on okay cube coverage continues here live in monaco i'm john furrier and all the action here on the monaco crypto summit love the dame come back next year it'll be great back with more coverage to wrap up here on the ground then the yacht club event we're going to go right there as well that's in a few hours so we're going to be right back [Music] you

(upbeat music) >> Hello, everyone. Welcome to the theCUBE's presentation of the AWS Startup Showcase. The theme, this showcase is MarTech, the emerging cloud scale customer experiences. Season two of episode three, the ongoing series covering the startups, the hot startups, talking about analytics, data, all things MarTech. I'm your host, John Furrier, here joined by Christian Wiklund, founder and CEO of unitQ here, talk about harnessing the power of user feedback to empower marketing. Thanks for joining us today. >> Thank you so much, John. Happy to be here. >> In these new shifts in the market, when you got cloud scale, open source software is completely changing the software business. We know that. There's no longer a software category. It's cloud, integration, data. That's the new normal. That's the new category, right? So as companies are building their products, and want to do a good job, it used to be, you send out surveys, you try to get the product market fit. And if you were smart, you got it right the third, fourth, 10th time. If you were lucky, like some companies, you get it right the first time. But the holy grail is to get it right the first time. And now, this new data acquisition opportunities that you guys in the middle of that can tap customers or prospects or end users to get data before things are shipped, or built, or to iterate on products. This is the customer feedback loop or data, voice of the customer journey. It's a gold mine. And it's you guys, it's your secret weapon. Take us through what this is about now. I mean, it's not just surveys. What's different? >> So yeah, if we go back to why are we building unitQ? Which is we want to build a quality company. Which is basically, how do we enable other companies to build higher quality experiences by tapping into all of the existing data assets? And the one we are in particularly excited about is user feedback. So me and my co-founder, Nik, and we're doing now the second company together. We spent 14 years. So we're like an old married couple. We accept each other, and we don't fight anymore, which is great. We did a consumer company called Skout, which was sold five years ago. And Skout was kind of early in the whole mobile first. I guess, we were actually mobile first company. And when we launched this one, we immediately had the entire world as our marketplace, right? Like any modern company. We launch a product, we have support for many languages. It's multiple platforms. We have Android, iOS, web, big screens, small screens, and that brings some complexities as it relates to staying on top of the quality of the experience because how do I test everything? >> John: Yeah. >> Pre-production. How do I make sure that our Polish Android users are having a good day? And we found at Skout, personally, like I could discover million dollar bugs by just drinking coffee and reading feedback. And we're like, "Well, there's got to be a better way to actually harness the end user feedback. That they are leaving in so many different places." So, you know what, what unitQ does is that we basically aggregate all different sources of user feedback, which can be app store reviews, Reddit posts, Tweets, comments on your Facebook ads. It can be better Business Bureau Reports. We don't like to get to many of those, of course. But really, anything on the public domain that mentions or refers to your product, we want to ingest that data in this machine, and then all the private sources. So you probably have a support system deployed, a Zendesk, or an Intercom. You might have a chatbot like an Ada, or and so forth. And your end user is going to leave a lot of feedback there as well. So we take all of these channels, plug it into the machine, and then we're able to take this qualitative data. Which and I actually think like, when an end user leaves a piece of feedback, it's an act of love. They took time out of the day, and they're going to tell you, "Hey, this is not working for me," or, "Hey, this is working for me," and they're giving you feedback. But how do we package these very messy, multi-channel, multiple languages, all over the place data? How can we distill it into something that's quantifiable? Because I want to be able to monitor these different signals. So I want to turn user feedback into time series. 'Cause with time series, I can now treat this the same way as Datadog treats machine logs. I want to be able to see anomalies, and I want to know when something breaks. So what we do here is that we break down your data in something called quality monitors, which is basically machine learning models that can aggregate the same type of feedback data in this very fine grained and discrete buckets. And we deploy up to a thousand of these quality monitors per product. And so we can get down to the root cause. Let's say, passive reset link is not working. And it's in that root cause, the granularity that we see that companies take action on the data. And I think historically, there has been like the workflow between marketing and support, and engineering and product has been a bit broken. They've been siloed from a data perspective. They've been siloed from a workflow perspective, where support will get a bunch of tickets around some issue in production. And they're trained to copy and paste some examples, and throw it over the wall, file a Jira ticket, and then they don't know what happens. So what we see with the platform we built is that these teams are able to rally around the single source of troop or like, yes, passive recent link seems to have broken. This is not a user error. It's not a fix later, or I can't reproduce. We're looking at the data, and yes, something broke. We need to fix it. >> I mean, the data silos a huge issue. Different channels, omnichannel. Now, there's more and more channels that people are talking in. So that's huge. I want to get to that. But also, you said that it's a labor of love to leave a comment or a feedback. But also, I remember from my early days, breaking into the business at IBM and Hewlett-Packard, where I worked. People who complain are the most loyal customers, if you service them. So it's complaints. >> Christian: Yeah. >> It's leaving feedback. And then, there's also reading between the lines with app errors or potentially what's going on under the covers that people may not be complaining about, but they're leaving maybe gesture data or some sort of digital trail. >> Yeah. >> So this is the confluence of the multitude of data sources. And then you got the siloed locations. >> Siloed locations. >> It's complicated problem. >> It's very complicated. And when you think about, so I started, I came to Bay Area in 2005. My dream was to be a quant analyst on Wall Street, and I ended up in QA at VMware. So I started at VMware in Palo Alto, and didn't have a driver's license. I had to bike around, which was super exciting. And we were shipping box software, right? This was literally a box with a DVD that's been burned, and if that DVD had bugs in it, guess what it'll be very costly to then have to ship out, and everything. So I love the VMware example because the test cycles were long and brutal. It was like a six month deal to get through all these different cases, and they couldn't be any bugs. But then as the industry moved into the cloud, CI/CD, ship at will. And if you look at the modern company, you'll have at least 20 plus integrations into your product. Analytics, add that's the case, authentication, that's the case, and so forth. And these integrations, they morph, and they break. And you have connectivity issues. Is your product working as well on Caltrain, when you're driving up and down, versus wifi? You have language specific bugs that happen. Android is also quite a fragmented market. The binary may not perform as well on that device, or is that device. So how do we make sure that we test everything before we ship? The answer is, we can't. There's no company today that can test everything before the ship. In particular, in consumer. And the epiphany we had at our last company, Skout, was that, "Hey, wait a minute. The end user, they're testing every configuration." They're sitting on the latest device, the oldest device. They're sitting on Japanese language, on Swedish language. >> John: Yeah. >> They are in different code paths because our product executed differently, depending on if you were a paid user, or a freemium user, or if you were certain demographical data. There's so many ways that you would have to test. And PagerDuty actually had a study they came out with recently, where they said 51% of all end user impacting issues are discovered first by the end user, when they serve with a bunch of customers. And again, like the cool part is, they will tell you what's not working. So now, how do we tap into that? >> Yeah. >> So what I'd like to say is, "Hey, your end user is like your ultimate test group, and unitQ is the layer that converts them into your extended test team." Now, the signals they're producing, it's making it through to the different teams in the organization. >> I think that's the script that you guys are flipping. If I could just interject. Because to me, when I hear you talking, I hear, "Okay, you're letting the customers be an input into the product development process." And there's many different pipelines of that development. And that could be whether you're iterating, or geography, releases, all kinds of different pipelines to get to the market. But in the old days, it was like just customer satisfaction. Complain in a call center. >> Christian: Yeah. >> Or I'm complaining, how do I get support? Nothing made itself into the product improvement, except for slow moving, waterfall-based processes. And then, maybe six months later, a small tweak could be improved. >> Yes. >> Here, you're taking direct input from collective intelligence. Okay. >> Is that have input and on timing is very important here, right? So how do you know if the product is working as it should in all these different flavors and configurations right now? How do you know if it's working well? And how do you know if you're improving or not improving over time? And I think the industry, what can we look at, as far as when it relates to quality? So I can look at star ratings, right? So what's the star rating in the app store? Well, star ratings, that's an average over time. So that's something that you may have a lot of issues in production today, and you're going to get dinged on star ratings over the next few months. And then, it brings down the score. NPS is another one, where we're not going to run NPS surveys every day. We're going to run it once a quarter, maybe once a month, if we're really, really aggressive. That's also a snapshot in time. And we need to have the finger on the pulse of product quality today. I need to know if this release is good or not good. I need to know if anything broke. And I think that real time aspect, what we see as stuff sort of bubbles up the stack, and not into production, we see up to a 50% reduction in time to fix these end user impacting issues. And I think, we also need to appreciate when someone takes time out of the day to write an app review, or email support, or write that Reddit post, it's pretty serious. It's not going to be like, "Oh, I don't like the shade of blue on this button." It's going to be something like, "I got double billed," or "Hey, someone took over my account," or, "I can't reset my password anymore. The CAPTCHA, I'm solving it, but I can't get through to the next phase." And we see a lot of these trajectory impacting bugs and quality issues in these work, these flows in the product that you're not testing every day. So if you work at Snapchat, your employees probably going to use Snapchat every day. Are they going to sign up every day? No. Are they going to do passive reset every day? No. And these things are very hard to instrument, lower in the stack. >> Yeah, I think this is, and again, back to these big problems. It's smoke before fire, and you're essentially seeing it early with your process. Can you give an example of how this new focus or new mindset of user feedback data can help customers increase their experience? Can you give some examples, 'cause folks watching and be like, "Okay, I love this value. Sell me on this idea, I'm sold. Okay, I want to tap into my prospects, and my customers, my end users to help me improve my product." 'Cause again, we can measure everything now with data. >> Yeah. We can measure everything. we can even measure quality these days. So when we started this company, I went out to talk to a bunch of friends, who are entrepreneurs, and VCs, and board members, and I asked them this very simple question. So in your board meetings, or on all hands, how do you talk about quality of the product? Do you have a metric? And everyone said, no. Okay. So are you data driven company? Yes, we're very data driven. >> John: Yeah. Go data driven. >> But you're not really sure if quality, how do you compare against competition? Are you doing as good as them, worse, better? Are you improving over time, and how do you measure it? And they're like, "Well, it's kind of like a blind spot of the company." And then you ask, "Well, do you think quality of experience is important?" And they say, "Yeah." "Well, why?" "Well, top of fund and growth. Higher quality products going to spread faster organically, we're going to make better store ratings. We're going to have the storefronts going to look better." And of course, more importantly, they said the different conversion cycles in the product box itself. That if you have bugs and friction, or an interface that's hard to use, then the inputs, the signups, it's not going to convert as well. So you're going to get dinged on retention, engagement, conversion to paid, and so forth. And that's what we've seen with the companies we work with. It is that poor quality acts as a filter function for the entire business, if you're a product led company. So if you think about product led company, where the product is really the centerpiece. And if it performs really, really well, then it allows you to hire more engineers, you can spend more on marketing. Everything is fed by this product at them in the middle, and then quality can make that thing perform worse or better. And we developed a metric actually called the unitQ Score. So if you go to our website, unitq.com, we have indexed the 5,000 largest apps in the world. And we're able to then, on a daily basis, update the score. Because the score is not something you do once a month or once a quarter. It's something that changes continuously. So now, you can get a score between zero and 100. If you get the score 100, that means that our AI doesn't find any quality issues reported in that data set. And if your score is 90, that means that 10% will be a quality issue. So now you can do a lot of fun stuff. You can start benchmarking against competition. So you can see, "Well, I'm Spotify. How do I rank against Deezer, or SoundCloud, or others in my space?" And what we've seen is that as the score goes up, we see this real big impact on KPI, such as conversion, organic growth, retention, ultimately, revenue, right? And so that was very satisfying for us, when we launched it. quality actually still really, really matters. >> Yeah. >> And I think we all agree at test, but how do we make a science out of it? And that's so what we've done. And when we were very lucky early on to get some incredible brands that we work with. So Pinterest is a big customer of ours. We have Spotify. We just signed new bank, Chime. So like we even signed BetterHelp recently, and the world's largest Bible app. So when you look at the types of businesses that we work with, it's truly a universal, very broad field, where if you have a digital exhaust or feedback, I can guarantee you, there are insights in there that are being neglected. >> John: So Chris, I got to. >> So these manual workflows. Yeah, please go ahead. >> I got to ask you, because this is a really great example of this new shift, right? The new shift of leveraging data, flipping the script. Everything's flipping the script here, right? >> Yeah. >> So you're talking about, what the value proposition is? "Hey, board example's a good one. How do you measure quality? There's no KPI for that." So it's almost category creating in its own way. In that, this net new things, it's okay to be new, it's just new. So the question is, if I'm a customer, I buy it. I can see my product teams engaging with this. I can see how it can changes my marketing, and customer experience teams. How do I operationalize this? Okay. So what do I do? So do I reorganize my marketing team? So take me through the impact to the customer that you're seeing. What are they resonating towards? Obviously, getting that data is key, and that's holy gray, we all know that. But what do I got to do to change my environment? What's my operationalization piece of it? >> Yeah, and that's one of the coolest parts I think, and that is, let's start with your user base. We're not going to ask your users to ask your users to do something differently. They're already producing this data every day. They are tweeting about it. They're putting in app produce. They're emailing support. They're engaging with your support chatbot. They're already doing it. And every day that you're not leveraging that data, the data that was produced today is less valuable tomorrow. And in 30 days, I would argue, it's probably useless. >> John: Unless it's same guy commenting. >> Yeah. (Christian and John laughing) The first, we need to make everyone understand. Well, yeah, the data is there, and we don't need to do anything differently with the end user. And then, what we do is we ask the customer to tell us, "Where should we listen in the public domain? So do you want the Reddit post, the Trustpilot? What channels should we listen to?" And then, our machine basically starts ingesting that data. So we have integration with all these different sites. And then, to get access to private data, it'll be, if you're on Zendesk, you have to issue a Zendesk token, right? So you don't need any engineering hours, except your IT person will have to grant us access to the data source. And then, when we go live. We basically build up this taxonomy with the customers. So we don't we don't want to try and impose our view of the world, of how do you describe the product with these buckets, these quality monitors? So we work with the company to then build out this taxonomy. So it's almost like a bespoke solution that we can bootstrap with previous work we've done, where you don't have these very, very fine buckets of where stuff could go wrong. And then what we do is there are different ways to hook this into the workflow. So one is just to use our products. It's a SaaS product as anything else. So you log in, and you can then get this overview of how is quality trending in different markets, on different platforms, different languages, and what is impacting them? What is driving this unitQ Score that's not good enough? And all of these different signals, we can then hook into Jira for instance. We have a Jira integration. We have a PagerDuty integration. We can wake up engineers if certain things break. We also tag tickets in your support system, which is actually quite cool. Where, let's say, you have 200 people, who wrote into support, saying, "I got double billed on Android." It turns out, there are some bugs that double billed them. Well, now we can tag all of these users in Zendesk, and then the support team can then reach out to that segment of users and say, "Hey, we heard that you had this bug with double billing. We're so sorry. We're working on it." And then when we push fix, we can then email the same group again, and maybe give them a little gift card or something, for the thank you. So you can have, even big companies can have that small company experience. So, so it's groups that use us, like at Pinterest, we have 800 accounts. So it's really through marketing has vested interest because they want to know what is impacting the end user. Because brand and product, the lines are basically gone, right? >> John: Yeah. >> So if the product is not working, then my spend into this machine is going to be less efficient. The reputation of our company is going to be worse. And the challenge for marketers before unitQ was, how do I engage with engineering and product? I'm dealing with anecdotal data, and my own experience of like, "Hey, I've never seen these type of complaints before. I think something is going on." >> John: Yeah. >> And then engineering will be like, "Ah, you know, well, I have 5,000 bugs in Jira. Why does this one matter? When did it start? Is this a growing issue?" >> John: You have to replicate the problem, right? >> Replicate it then. >> And then it goes on and on and on. >> And a lot of times, reproducing bugs, it's really hard because it works on my device. Because you don't sit on that device that it happened on. >> Yup. >> So now, when marketing can come with indisputable data, and say, "Hey, something broke here." And we see the same with support. Product engineering, of course, for them, we talk about, "Hey, listen, you you've invested a lot in observability of your stack, haven't you?" "Yeah, yeah, yeah." "So you have a Datadog in the bottom?" "Absolutely." "And you have an APP D on the client?" "Absolutely." "Well, what about the last mile? How the product manifests itself? Shouldn't you monitor that as well using machines?" They're like, "Yeah, that'd be really cool." (John laughs) And we see this. There's no way to instrument everything, lowering the stack to capture these bugs that leak out. So it resonates really well there. And even for the engineers who's going to fix it. >> Yeah. >> I call it like empathy data. >> Yup. >> Where I get assigned a bug to fix. Well, now, I can read all the feedback. I can actually see, and I can see the feedback coming in. >> Yeah. >> Oh, there's users out there, suffering from this bug. And then when I fix it and I deploy the fix, and I see the trend go down to zero, and then I can celebrate it. So that whole feedback loop is (indistinct). >> And that's real time. It's usually missed too. This is the power of user feedback. You guys got a great product, unitQ. Great to have you on. Founder and CEO, Christian Wiklund. Thanks for coming on and sharing, and showcase. >> Thank you, John. For the last 30 seconds, the minute we have left, put a plug in for the company. What are you guys looking for? Give a quick pitch for the company, real quick, for the folks out there. Looking for more people, funding status, number of employees. Give a quick plug. >> Yes. So we raised our A Round from Google, and then we raised our B from Excel that we closed late last year. So we're not raising money. We are hiring across go-to-markets, engineering. And we love to work with people, who are passionate about quality and data. We're always, of course, looking for customers, who are interested in upping their game. And hey, listen, competing with features is really hard because you can copy features very quickly. Competing with content. Content is commodity. You're going to get the same movies more or less on all these different providers. And competing on price, we're not willing to do. You're going to pay 10 bucks a month for music. So how do you compete today? And if your competitor has a better fine tuned piano than your competitor will have better efficiencies, and they're going to retain customers and users better. And you don't want to lose on quality because it is actually a deterministic and fixable problem. So yeah, come talk to us if you want to up the game there. >> Great stuff. The iteration lean startup model, some say took craft out of building the product. But this is now bringing the craftsmanship into the product cycle, when you can get that data from customers and users. >> Yeah. >> Who are going to be happy that you fixed it, that you're listening. >> Yeah. >> And that the product got better. So it's a flywheel of loyalty, quality, brand, all off you can figure it out. It's the holy grail. >> I think it is. It's a gold mine. And every day you're not leveraging this assets, your use of feedback that's there, is a missed opportunity. >> Christian, thanks so much for coming on. Congratulations to you and your startup. You guys back together. The band is back together, up into the right, doing well. >> Yeah. We we'll check in with you later. Thanks for coming on this showcase. Appreciate it. >> Thank you, John. Appreciate it very much. >> Okay. AWS Startup Showcase. This is season two, episode three, the ongoing series. This one's about MarTech, cloud experiences are scaling. I'm John Furrier, your host. Thanks for watching. (upbeat music)

>>Hello, everyone. Welcome to the cubes presentation of the 80 startup showcase marketing technology, emerging cloud scale customer experiences. This is season two, episode three of the ongoing series covering the exciting startups from the, a AWS ecosystem to talk about all the top trends and also featuring the key customers. I'm your host, John ER, today we're joined by Louis Fernando, Denise vice president of peak pay social and John Kim, the CEO of Sandberg to learn about the future of what's going on in fostering deeper customer relationships. Gentlemen, thanks for joining us in the cube showcase, >>Excited to be here. >>So John talk about Sendbird real quick set the table for us. What you guys do, you got a customer here to highlight some of the key things you're doing with customers, the value proposition what's Sendbird and what's the showcase about, >>Yeah, I'm really excited to be here. Uh, I'm John founder, C of Sandberg. So Sandberg is the worst leading conversations platform for mobile applications. We can power user to user conversations in mobile applications, as well as the brand to user conversations such as marketing sales and support. So, uh, today we power over quarter billion users on a monthly basis. Uh, we have, you know, through over 300 employees across seven different countries around the world, we work with some of the world's leading, uh, uh, customers such as big pay that we are going to showcase today, along with other, uh, wonderful customers like DoorDash, Reddit, <inaudible> sports and so forth. We have collectively raised over 200 million in funding. Um, so that's kind of where we are today. >>Well, it's always great to have, uh, one great success. Uh, good funding, more important is the customers. And I love showcases where the customers do the talking, because that means you've got some success stories. Louise, talk about, um, are you happy customer? What's it like working with Sandberg? Give us the, give us the scoop. >>So sandbar is being a great partner with us. So pick pay is a Brazilian payment app. We're at a FinTech here with more than 30 million active users using everyday pick pay to pay everything. So the, the, the majority of the payments are between peers, between people. So sandbar is, is helping us to improve a lot this journey to make it more pleasant between every everyone who are using big, big. So we are here, let's talk and it's a >>Pleasure. Yeah, it's awesome. Well, I great to have you guys on great, great relationship. And one of the things we've been talking about on the cube, if the folks watching that know our audience, no we've been banging the, the drum hard on this new world and this new patterns of user expectations and building relationships in this new digital world is not about the old way, the old MarTech way. There are new new use cases, new expectations by the consumers, John, that are, that are bringing up new opportunities, but also expectations. It's not about, I mean, I mean, if someone's using discord, for example, cuz they're gamers, they're done discord. If they want to communicate with, with slack, they, I do slack, SMS, kind of old hat. You got WhatsApp, you've got all these now peer to peer organic connections, multiple channels. This is all the new world. What's your vision on this new relationship building digital communication world. >>Yeah. So I, I think you brought a really good point there. One of the most frequently used applications in the world today are messaging applications across any countries, any region, any culture, if you look at the most frequently used and most longest used applications are usually some form of a, a messaging application. Now the end users or the customers in the world are so used to using, uh, uh, such a, you know, frictionless ver very responsive, modern experience on those messaging applications. What we want to help with the business around the world, the 99.9% of the business around the world don't have those really te knowledge or user experience expertise in messaging. So we want to help our businesses, help our customers be able to harness the power of modern messaging capabilities and then be able to embed it in their own business so that they can retain their users on their platform, engage with them in the con context that their, uh, what their business is about so that they can not only, uh, control or provide a better user experience, but also be able to, uh, understand their users better, uh, understand what they're doing on their businesses, be able to own and, uh, control the data in a more secure and safe way. >>So really it's uh, we're like the Robin hood of the world trying to keep superpower yeah. Back to the businesses. >>Yeah. Deal from the rich idea, the messaging scale. Bring that to everybody else. I love that. Uh, and you got kind of this double int Robin hood kind of new for the new generation finance. This is about taking the advantage of scalable platforms, monopolies, right. And giving the entrepreneur an opportunity to have that same capability feature, rich Louise PPE. You guys used Sendbird together. You have to level up, you gotta compete with those big monopolies to pride, scalable conversations. Okay. How did you engage this? What was your success path look? What was it look like? >>Yeah. When we look to this majority, the bigger chat apps that we have nowadays in the market, we are looking to them and then Brazilians are using for their daily course, but Brazilians are paying every day millions and millions of payments. And these chat apps are not, uh, able to, to, to deal with these payments. So what we are doing here is that, uh, providing a solution where every conversation that are going to happen before, during, or after a payment between the, the people, they would, uh, uh, have a nice platform that could afford all, all of their emotions and discussions that they have to do before or after the payment. So we are putting together the chat platform and we with the payment platform. So that's, that's what we are doing now. >>Okay. So just so I get this right. You're using Sandberg essentially integrated your mobile payment experience. Okay. Which is your app you're Sandberg to bring that scalability into the, into the social app application into the app itself. Is that right? >>Yes. Perfect. Integrated with the payment journey. So everybody who is going to pay, they need to find the one, the, the one they want to pay and then they can chat and conclude the payment through the platform. Yeah. I >>Mean, why not have it right there at point of, uh, transaction. Right. Um, why did you, um, decide to, um, to use conversations in your mobile wallet? Just curious. >>So it's important to say that we were born social. We born in 2012. So when our main main product was peer to peer payments, so everybody were sending money to a friend requesting or charging their family. So a service provider. And once we, we started as a social platform in that period. In that moment, we are just focusing in likes comments and like public interactions and the word become more private. And as soon we under understood this situation, we decided to move from a public feed to a private, to a private interaction. So that's, uh, that then the, the conversational space was the solution for that moving from a public interaction to a private interaction. So between the peers, which are involved in the, the transaction. So that's why we are providing the chat solution integrated with payments. >>That's a great call. John, just give some context here, again, for the folks watching this is now expected, this integrated experience. What's your, how would you talk to folks out there? I mean, first of all, I, I, I see it clearly, you've got an app, you gotta have all this integration and you need it scaling to reach features. Talk about your view on that. Is that the, is that what's happening here? What's, what's the real dynamic here. What's the, the big trend. >>Yeah. One thing that's, uh, super interesting about, uh, uh, like messaging experience in general, if you think about any kind of conversations that's happening, uh, digitally between human beings, more and more conversations, just like what Louis mentioned earlier are happening between in a private setting, even on applications, whether it be slack or other forms of communication, uh, more hap uh, more conversations happen through either one-on-one conversations or in a private small group settings. And because people feel more secure, uh, safe to have, uh, more intimate conversations. So even when you're making transactions is more, you know, there's a higher trust and, uh, people tend to engage, uh, far better on platforms through these kind of private conversations. That's where we kind of come in, whether it be, you want to set a one-on-one conversations or with a group conversation. And then ultimately if you want to take it public in a large group setting, you can also support, you know, thousands, if not, you know, hundreds of thousands of people, uh, engaging a public forum as well. So all of those capabilities can be implemented using something Ember, but again, the world is, uh, right now the businesses and how the user are, are interacting with this with each other is all happening through digital conversations. And we're seeing more and more of that happening, uh, throughout the life cycle of our company. >>Yeah, just as a sidebar, I was just talking to a venture in San Francisco the other day, and we're talking about the future of security and SAS and cloud scale. And, you know, the conversation went to more of, is it SAS? Is it platform as a service Louis? I wanna get your thoughts because, you know, you're seeing more and more needs for customization, low code, no code. You're seeing these trends. You gotta built in security. So, you know, the different, the old SAS model was softwares a service, but now that's everything in the cloud is softwares a service. So, but you need to have that platform kind of vibe for scale customization, maybe some developer integration, cuz apps are becoming the, the touchpoint. So can you walk us through what your vision was when you decided to integrate, chat into your app and how did you see that chat, changing the customer experience for payments and across your user journey? Cause, I mean, it's obvious now looking at it, but it might not have been for some. What was your, what was your vision? And when you had to do that, >>When you looked to Brazilian reality, we can see those in, uh, payment apps. All of them are focused on the transactional moment. And as soon as we started to think, how could be, how could our journey be better, more pleased than the others and make people want to be here and to use and to open our app every day is just about making the interaction with the peers easier, even with a merchant or even with my friend. So the main point that our first step was just to connect all, all the users between themselves to payments. The second step we are providing now is using the chat platform, the send bird platform as a platform for peak pay. So we are going to provide more best information. We're going to provide a better customer experience through the support and everything. So, um, this, this, this interaction or this connection, this partnership with Sandberg are going to unlock a new level of service for our users. And at the same time, a much more pleasant or a more pleasant journey for them while they are using the, the app for a, a simple payment, or if they are going to look for a group objective or maybe a crowdfund in the future or a group to decide, or just to pay something. So we are then locking a new level of interaction between the peers between the people and the users that are, that are involved into this, this payment or this simple transaction, we are making it more conversational. >>Yeah. You're making the application more valuable. We're gonna get to that in the next segment about, you know, the future of apps one and done, you see a lot of sports apps, oh, this big tournament, you know, and then you use it and then you never use it again until next year. You know, you have very time specific apps, but now you guys are smart to kind of build this in, but I gotta ask you a question because a lot of developers and companies out there always have this buy versus build decision. Why did you decide to use Sendbird versus building it in house? It's always kind of like the big trade off. >>Yeah. First of all, it will take a long, long time for us to achieve a major platform as Sandberg. And we are not a chat platform. So we are going to use this social interaction to improve the payment platform that we have. So when we look to the market and we found Sandberg, then we thought, okay, this guys, they are a real platform. And through the conversations, we are seeing that they are roadmap working in synergy with our roadmap. And then we can, we could start to deliver value to our, to our users in a fastest way. Could you imagine it spending 2, 3, 4 years to develop something like sand? And even when we achieve this point, probably our solution will be, would be weaker than, than Sandberg. So it was like no brainer to do that. Yeah. Because we want to improve the payment journey, not to do a chat, only a chat platform. So that's why we are working together to prove it's >>Really, you start to see these plugins, these, you know, look at Stripe for payments, for instance, right. And here in the success they've had, you know, people want to plug in for services. So John, I gotta ask you about, um, about the, the complexity that goes into it. The trust required that they have for you, you have to do this heavy lifting, you gotta provide the confidence that your service is gonna have to scale the compliance. Talk about that. What do you guys do under the covers that make this easy again, great business model, heavy lifting done by you. Seamless integration provide that value. That's why business is good, but there's a lot going on share what's happening under the, under the covers. >>Yeah. Um, before going to like the technical, like intricacy of what we do just to provide a little bit of background context on why we even started this business is we, uh, this is my second startup. My first company was a gaming company. We had built like chat three, four times just for our own game. So we were basically, we felt like we were reinventing the wheel. And then we actually went on a buyer's journey when we were building a social application, uh, uh, for, for, uh, uh, building our own community. We tried to actually be a buyer to see if we can actually find a solution. We want to use turns out that there weren't a lot of like sophisticated, you know, top notch, modern, uh, uh, chat experience that we can build using some other third party solutions. So we had to build all of that ourselves, which became the foundation for se today. >>And what we realized is that for most companies like using a building, the most sophisticated chat is probably not going to be their highest priority in case a pick pay will be, you know, financial transactions and all the other business that can be built on and hosted by platform like pick pay. But, you know, building the most topnotch chat experience would be a priority for a company like let's say WhatsApp or, or telegram, but it will probably not be the priority for, you know, major gaming companies, food delivery companies, finance companies, chat is not the highest priority. That's kind of where we come in, cuz chat is the highest priority for us. And we also have a privilege of working with some of the other, uh, world industry, uh, industry leaders. So by, uh, having this collective experience, working with the industry leaders, we get, uh, uh, technological superiority, being able to, uh, scale to, you know, hundreds of millions of users on a monthly basis. Also the security and the compliances by working with some of the largest commercial banks on some of the largest FinTech applications across the globe. So we have, you know, security, compliances, all the industry, best practices that are built in and all the new topnotch user experience that we are, uh, building with other customers can be also be, uh, utilized by a customer like pick pay. So you get this collective almost like evolutionary benefit. Yeah. By, uh, working with a company like us, >>You get a lot of economies of scale. Could you mind just sharing the URL for the company? So folks watching can go get, do a deep dive. Cause I'm you guys got a lot of, lot of, um, certifications under the covers, a lot of things you guys do. So you mind just sharing URL real quick. >>Yeah. So our company, uh, you can find everything about our company on sandberg.com like carrot pigeon. So, uh, you're sending a bird to send a message. So, uh, yeah. send.com >>All so let's get it to the application, cuz this is really interesting cuz Chad is table stakes now, but things are evolving beyond Chad. You gotta integrate that user experience. It's data. Now you gotta have scale. I mean, you know, people who wanna roll their own chat will find out there's a lot of client side and backend scale issues. Right. You can have a tsunami river like on Twitch, you know, you chat. I mean that, could you got client side issues, data scale. <laugh> right. You got backend. Um, Louis, talk about that dynamic because you know, as you start to scale, you want to rely on that. Talk about this dynamic, how apps now are integrating all these new features. So is it, are apps gonna go like more multifunctional? Do you see apps one and done? What's the, how do you guys see this app world playing out and where does, does the Sendbird fit in? And >>Just, just let me know better John, about the performance or about the, just, just let me >>Oh, slow with performance. Uh, performance is huge, right? You gotta have no one wants to have lag on, on chat. >>Okay. So, um, big pay when we look to the payments have millions, thousands of, of, of payments happen happening every second. So what we are doing now is moving all the payments through a conversation. So it always happened inside the conversation. So since from the first moment, um, every second counts to convert this client. And since from the first moment we never saw in, on Sandberg, any issue about that. And even when we have a question or something that we need to improve the team we're working together. So that that's, those are the points that are making us to work together and to make things going pretty fast. When we look to the users who are going to use chat, they are, their intention is three times better than the users who are not using payments through the chat. They are average. Average spent is three times higher too. >>So they, they are making more connections. They are chatting with their friends. They are friends are here. So the network effect is stronger. So if they're going to pay and they need to wait one more second, two seconds to conclude the payment, probably they will not go into choose paying through the, again, they will use only the wallet, only the code, only the Alliance of the user. So that's is so important for us to perform really, really fast. And then this is what we are finding. And this is what is happening with the integration with Sandberg. >>And what's interesting is, is that the by build chat with conversation, we just had a minute ago kind of plays in here. You get the benefits of Sandberg, but now your transactional fidelity is in the chat <laugh> that you don't build that you rely on them on. So again, that's an interesting dynamic. This is the future of apps, John, this is where it matters. The engagement. This is what you talk about is the new, the new digital experience who would've thought that five, 10 years ago. I mean, chat was just like, Hey, what's going around direct message. Now it's integral part of the app. What's your reading. >>Yeah. I mean, we're seeing that across, uh, uh, to Lewis's point, not just transactions, but like marketing messages are now being sent through chat. So the marketing is no longer just about like giving discount calls, but you can actually reengage with the brand. Uh, also support is becoming more real time through chat. So you're actually building a relationship. The support agents have a better context about the previous conversations and the transactions, the sales conversations, even like building, uh, building alerts, notification, all those things are now, uh, happening through conversations. And that's a better way for customers to engage with the brand cuz you actually, you're actually building a better relationship and also, uh, being able to trust the brand more because there is a channel for you to communicate and, and, and be seen and be heard, uh, by the brand. So we do believe that that's the future of the business and how more and more, uh, brands will be building relationships with their customers. >>Yeah. I love, I love your business model. I think it's really critical. And I think that stickiness is a real, uh, call out point there and the brand, the co-branding and the branding capability, but also really quickly in the last minute we have John and Luis, if you don't mind talking about security, I mean, I can't go a day now without getting an SMS scam, uh, text, uh, you seeing it now on WhatsApp. I mean, I don't even use telegram anymore. I mean, come on. So like, like this is now a problem. The old way has been infiltrated with spam and security issues. Security has to be there. The trust and security real quick, John, we'll start with you and we all Louis go, go ahead. >>No, no. Just, just to, to say how important is that we are not only a chatting platform. We are a payment platform, so we have money now, the transaction. So here in Brazil, we have all this safe, the, the, the layers, the security layers that we have in, on our app. And then we have the security layers provided from Sandburg. So, and when we look to the features, Sandberg are providing to us a lot of features that help users to feel safer like per refined profiles, like announcements, where it's a profile from peak pay, where the users can recognize. So this is peak pay talking with me. It's not a user trying to pass, trying to use big Bay's name to talk with me. So these issues is something that we are really, really, we really care about here because we are not only a chat platform. As I said before, we are a payment platform. We are a FinTech, we're at a digital bank. So we need to take care a lot and we don't have any complaint about it because Sandberg understood it. And then they, they, they are providing since the first moment with the perfect solutions and the user interface to make it simpler for the users to recognize that we speak, pay who is chatting with them, not a user with, with bad, bad intentions. >>Great, great insight, Louis. Thanks for sharing that, John really appreciate you guys coming on. Great showcase. Real final word. John will give you the final word folks watching out there. How do they engage with Sendbird? I want to integrate, I want to use your chat service. What do I do? Do I have to connect in as it managed service is the line of code. What do I do to get Sendbird? >>Yeah. So if you're a developer building a mobile application, simply come visit our website, we have a open documentation and SDK you can download and simply plug into your application. You can have a chat experience up and running matter of minutes, if not ours using our UI kit. So we want to make it as easy as possible for all the builders in the world to be able to harness the superpower of digital conversations. >>All right, great. Congratulations, John, on your success and all the growth and Louis, thanks for coming in, sharing the customer perspective and great insight. Thanks for coming on the showcase. Really appreciate it. Thanks for your time. >>Yeah. Thank you for having me. >>Okay. The a of us startup showcase season two, episode three here I'm John for your host. Thanks for watching.

(upbeat music) >> Hello, everyone, welcome to theCUBE's presentation of the AWS Startup Showcase. We're in Season two, Episode three, and this is the topic of MarTech and the Emerging Cloud-Scale Customer Experiences, the ongoing coverage of AWS's ecosystem of large scale growth and new companies and growing companies. I'm your host, John Furrier. We're excited to have Tim Barnes, Global Director, General Manager of Advertiser and Marketing at AWS here doing the keynote cloud-scale customer experience. Tim, thanks for coming on. >> Oh, great to be here and thank you for having me. >> You've seen many cycles of innovation, certainly in the ad tech platform space around data, serving consumers and a lot of big, big scale advertisers over the years as the Web 1.0, 2.0, now 3.0 coming, cloud-scale, roll of data, all big conversations changing the game. We see things like cookies going away. What does this all mean? Silos, walled gardens, a lot of new things are impacting the applications and expectations of consumers, which is also impacting the folks trying to reach the consumers. And this is kind of creating a kind of a current situation, which is challenging, but also an opportunity. Can you share your perspective of what this current situation is, as the emerging MarTech landscape emerges? >> Yeah, sure, John, it's funny in this industry, the only constant has changed and it's an ever-changing industry and never more so than right now. I mean, we're seeing with whether it's the rise of privacy legislation or just breach of security of data or changes in how the top tech providers and browser controllers are changing their process for reaching customers. This is an inflection point in the history of both ad tech and MarTech. You hit the nail on the head with cookie deprecation, with Apple removing IDFA, changes to browsers, et cetera, we're at an interesting point. And by the way, we're also seeing an explosion of content sources and ability to reach customers that's unmatched in the history of advertising. So those two things are somewhat at odds. So whether we see the rise of connected television or digital out of home, you mentioned Web 3.0 and the opportunities that may present in metaverse, et cetera, it's an explosion of opportunity, but how do we continue to connect brands with customers and do so in a privacy compliant way? And that's really the big challenge we're facing. One of the things that I see is the rise of modeling or machine learning as a mechanism to help remove some of these barriers. If you think about the idea of one-to-one targeting, well, that's going to be less and less possible as we progress. So how am I still as a brand advertiser or as a targeted advertiser, how am I going to still reach the right audience with the right message in a world where I don't necessarily know who they are. And modeling is a really key way of achieving that goal and we're seeing that across a number of different angles. >> We've always talked about on the ad tech business for years, it's the behemoth of contextual and behavioral, those dynamics. And if you look at the content side of the business, you have now this new, massive source of new sources, blogging has been around for a long time, you got video, you got newsletters, you got all kinds of people, self-publishing, that's been around for a while, right? So you're seeing all these new sources. Trust is a big factor, but everyone wants to control their data. So this walled garden perpetuation of value, I got to control my data, but machine learning works best when you expose data, so this is kind of a paradox. Can you talk about the current challenge here and how to overcome it because you can't fight fashion, as they say, and we see people kind of going down this road as saying, data's a competitive advantage, but I got to figure out a way to keep it, own it, but also share it for the machine learning. What's your take on that? >> Yeah, I think first and foremost, if I may, I would just start with, it's super important to make that connection with the consumer in the first place. So you hit the nail on the head for advertisers and marketers today, the importance of gaining first party access to your customer and with permission and consent is paramount. And so just how you establish that connection point with trust and with very clear directive on how you're going to use the data has never been more important. So I would start there if I was a brand advertiser or a marketer, trying to figure out how I'm going to better connect with my consumers and get more first party data that I could leverage. So that's just building the scale of first party data to enable you to actually perform some of the types of approaches we'll discuss. The second thing I would say is that increasingly, the challenge exists with the exchange of the data itself. So if I'm a data control, if I own a set of first party data that I have consent with consumers to use, and I'm passing that data over to a third party, and that data is leaked, I'm still responsible for that data. Or if somebody wants to opt out of a communication and that opt out signal doesn't flow to the third party, I'm still liable, or at least from the consumer's perspective, I've provided a poor customer experience. And that's where we see the rise of the next generation, I call it of data clean rooms, the approaches that you're seeing, a number of customers take in terms of how they connect data without actually moving the data between two sources. And we're seeing that as certainly a mechanism by which you can preserve accessibility data, we call that federated data exchange or federated data clean rooms and I think you're seeing that from a number of different parties in the industry. >> That's awesome, I want to get into the data interoperability because we have a lot of startups presenting in this episode around that area, but why I got you here, you mentioned data clean room. Could you define for us, what is a federated data clean room, what is that about? >> Yeah, I would simply describe it as zero data movement in a privacy and secure environment. To be a little bit more explicit and detailed, it really is the idea that if I'm a party A and I want to exchange data with party B, how can I run a query for analytics or other purposes without actually moving data anywhere? Can I run a query that has accessibility to both parties, that has the security and the levels of aggregation that both parties agree to and then run the query and get those results sets back in a way that it actually facilitates business between the two parties. And we're seeing that expand with partners like Snowflake and InfoSum, even within Amazon itself, AWS, we have data sharing capabilities within Redshift and some of our other data-led capabilities. And we're just seeing explosion of demand and need for customers to be able to share data, but do it in a way where they still control the data and don't ever hand it over to a third party for execution. >> So if I understand this correctly, this is kind of an evolution to kind of take away the middleman, if you will, between parties that used to be historically the case, is that right? >> Yeah, I'd say this, the middleman still exists in many cases. If you think about joining two parties' data together, you still have the problem of the match key. How do I make sure that I get the broadest set of data to match up with the broadest set of data on the other side? So we have a number of partners that provide these types of services from LiveRamp, TransUnion, Experian, et cetera. So there's still a place for that so-called middleman in terms of helping to facilitate the transaction, but as a clean room itself, I think that term is becoming outdated in terms of a physical third party location, where you push data for analysis, that's controlled by a third party. >> Yeah, great clarification there. I want to get into this data interoperability because the benefits of AWS and cloud scales we've seen over the past decade and looking forward is, it's an API based economy. So APIs and microservices, cloud native stuff is going to be the key to integration. And so connecting people together is kind of what we're seeing as the trend. People are connecting their data, they're sharing code in open source. So there's an opportunity to connect the ecosystem of companies out there with their data. Can you share your view on this interoperability trend, why it's important and what's the impact to customers who want to go down this either automated or programmatic connection oriented way of connecting data. >> Never more important than it has been right now. I mean, if you think about the way we transact it and still too today do to a certain extent through cookie swaps and all sorts of crazy exchanges of data, those are going away at some point in the future; it could be a year from now, it could be later, but they're going away. And I think that that puts a great amount of pressure on the broad ecosystem of customers who transact for marketers, on behalf of marketers, both for advertising and marketing. And so data interoperability to me is how we think about providing that transactional layer between multiple parties so that they can continue to transact in a way that's meaningful and seamless, and frankly at lower cost and at greater scale than we've done in the past with less complexity. And so, we're seeing a number of changes in that regard, whether that's data sharing and data clean rooms or federated clean rooms, as we described earlier, whether that's the rise of next generation identity solutions, for example, the UID 2.0 Consortium, which is an effort to use hashed email addresses and other forms of identifiers to facilitate data exchange for the programmatic ecosystem. These are sort of evolutions based on this notion that the old world is going away, the new world is coming, and part of that is how do we connect data sources in a more seamless and frankly, efficient manner. >> It's almost interesting, it's almost flipped upside down, you had this walled garden mentality, I got to control my data, but now I have data interoperability. So you got to own and collect the data, but also share it. This is going to kind of change the paradigm around my identity platforms, attributions, audience, as audiences move around, and with cookies going away, this is going to require a new abstraction, a new way to do it. So you mentioned some of those standards. Is there a path in this evolution that changes it for the better? What's your view on this? What do you see happening? What's going to come out of this new wave? >> Yeah, my father was always fond of telling me, "The customer, my customers is my customer." And I like to put myself in the shoes of the Marc Pritchards of the world at Procter & Gamble and think, what do they want? And frankly, their requirements for data and for marketing have not changed over the last 20 years. It's, I want to reach the right customer at the right time, with the right message and I want to be able to measure it. In other words, summarizing, I want omnichannel execution with omnichannel measurement, and that's become increasingly difficult as you highlighted with the rise of the walled gardens and increasingly data living in silos. And so I think it's important that we, as an industry start to think about what's in the best interest of the one customer who brings virtually 100% of the dollars to this marketplace, which is the CMO and the CMO office. And how do we think about returning value to them in a way that is meaningful and actually drives its industry forward. And I think that's where the data operability piece becomes really important. How do we think about connecting the omnichannel channels of execution? How do we connect that with partners who run attribution offerings with machine learning or partners who provide augmentation or enrichment data such as third party data providers, or even connecting the buy side with the sell side in a more efficient manner? How do I make that connection between the CMO and the publisher in a more efficient and effective way? And these are all challenges facing us today. And I think at the foundational layer of that is how do we think about first of all, what data does the marketer have, what is the first party data? How do we help them ethically source and collect more of that data with proper consent? And then how do we help them join that data into a variety of data sources in a way that they can gain value from it. And that's where machine learning really comes into play. So whether that's the notion of audience expansion, whether that's looking for some sort of cohort analysis that helps with contextual advertising, whether that's the notion of a more of a modeled approach to attribution versus a one-to-one approach, all of those things I think are in play, as we think about returning value back to that customer of our customer. >> That's interesting, you broke down the customer needs in three areas; CMO office and staff, partners ISV software developers, and then third party services. Kind of all different needs, if you will, kind of tiered, kind of at the center of that's the user, the consumer who have the expectations. So it's interesting, you have the stakeholders, you laid out kind of those three areas as to customers, but the end user, the consumer, they have a preference, they kind of don't want to be locked into one thing. They want to move around, they want to download apps, they want to play on Reddit, they want to be on LinkedIn, they want to be all over the place, they don't want to get locked in. So you have now kind of this high velocity user behavior. How do you see that factoring in, because with cookies going away and kind of the convergence of offline-online, really becoming predominant, how do you know someone's paying attention to what and when attention and reputation. All these things seem complex. How do you make sense of it? >> Yeah, it's a great question. I think that the consumer as you said, finds a creepiness factor with a message that follows them around their various sources of engagement with content. So I think at first and foremost, there's the recognition by the brand that we need to be a little bit more thoughtful about how we interact with our customer and how we build that trust and that relationship with the customer. And that all starts with of course, opt-in process consent management center but it also includes how we communicate with them. What message are we actually putting in front of them? Is it meaningful, is it impactful? Does it drive value for the customer? I think we've seen a lot of studies, I won't recite them that state that most consumers do find value in targeted messaging, but I think they want it done correctly and there in lies the problem. So what does that mean by channel, especially when we lose the ability to look at that consumer interaction across those channels. And I think that's where we have to be a little bit more thoughtful with frankly, kind of going back to the beginning with contextual advertising, with advertising that perhaps has meaning, or has empathy with the consumer, perhaps resonates with the consumer in a different way than just a targeted message. And we're seeing that trend, we're seeing that trend both in television, connected television as those converge, but also as we see about connectivity with gaming and other sort of more nuanced channels. The other thing I would say is, I think there's a movement towards less interruptive advertising as well, which kind of removes a little bit of those barriers for the consumer and the brand to interact. And whether that be dynamic product placement, content optimization, or whether that be sponsorship type opportunities within digital. I think we're seeing an increased movement towards those types of executions, which I think will also provide value to both parties. >> Yeah, I think you nailed it there. I totally agree with you on the contextual targeting, I think that's a huge deal and that's proven over the years of providing benefit. People, they're trying to find what they're looking for, whether it's data to consume or a solution they want to buy. So I think that all kind of ties together. The question is these three stakeholders, the CMO office and staff you mentioned, and the software developers, apps, or walled gardens, and then like ad servers as they come together, have to have standards. And so, I think to me, I'm trying to squint through all the movement and the shifting plates that are going on in the industry and trying to figure out where are the dots connecting? And you've seen many cycles of innovation at the end of the day, it comes down to who can perform best for the end user, as well as the marketers and advertisers, so that balance. What's your view on this shift? It's going to land somewhere, it has to land in the right area, and the market's very efficient. I mean, this ad market's very efficient. >> Yeah, I mean, in some way, so from a standards perspective, I support and we interact extensively with the IB and other industry associations on privacy enhancing technologies and how we think about these next generations of connection points or identifiers to connect with consumers. But I'd say this, with respect to the CMO, and I mentioned the publisher earlier, I think over the last 10 years with the rise of programmatic, certainly we saw the power reside mostly with the CMO who was able to amass a large pool of cookies or purchase a large sort of cohort of customers with cookie based attributes and then execute against that. And so almost a blind fashion to the publisher, the publisher was sort of left to say, "Hey, here's an opportunity, do you want to buy it or not?" With no real reason why the marketer might be buying that customer? And I think that we're seeing a shift backwards towards the publisher and perhaps a healthy balance between the two. And so, I do believe that over time, that we're going to see publishers provide a lot more, what I might almost describe as mini walled gardens. So the ability, great publisher or a set of publishers to create a cohort of customers that can be targeted through programmatic or perhaps through programmatic guaranteed in a way that it's a balance between the two. And frankly thinking about that notion of federated data clean rooms, you can see an approach where publishers are able to share their first party data with a marketer's first party data, without either party feeling like they're giving up something or passing all their value over to the other. And I do believe we're going to see some significant technology changes over the next three to four years. That really rely on that interplay between the marketer and the publisher in a way that it helps both sides achieve their goals, and that is, increasing value back to the publisher in terms of higher CPMs, and of course, better reach and frequency controls for the marketer. >> I think you really brought up a big point there we can maybe follow up on, but I think this idea of publishers getting more control and power and value is an example of the market filling a void and the power log at the long tail, it's kind of a straight line. Then it's got the niche kind of communities, it's growing in the middle there, and I think the middle of the torso of that power law is the publishers because they have all the technology to measure the journeys and the click throughs and all this traffic going on their platform, but they just need to connect to someone else. >> Correct. >> That brings in the interoperability. So, as a publisher ourselves, we see that long tail getting really kind of fat in the middle where new brands are going to emerge, if they have audience. I mean, some podcasts have millions of users and some blogs are attracting massive audience, niche audiences that are growing. >> I would say, just look at the rise of what we might not have considered publishers in the past, but are certainly growing as publishers today. Customers like Instacart or Uber who are creating ad platforms or gaming, which of course has been an ad supported platform for some time, but is growing immensely. Retail as a platform, of course, amazon.com being one of the biggest retail platforms with advertising supported models, but we're seeing that growth across the board for retail customers. And I think that again, there's never been more opportunities to reach customers. We just have to do it the right way, in the way that it's not offensive to customers, not creepy, if you want to call it that, and also maximizes value for both parties and that be both the buy and the sell side. >> Yeah, everyone's a publisher and everyone's a media company. Everyone has their own news network, everyone has their own retail, it's a completely new world. Tim, thanks for coming on and sharing your perspective and insights on this key note, Tim Barnes, Global Director, General Manager of Advertiser and Market at AWS here with the Episode three of Season two of the AWS Startup Showcase. I'm John Furrier, thanks for watching. (upbeat music)

>>Okay, welcome back everyone. This is the Cube's coverage here in Las Vegas. Back at events re Mars, Amazon re Mars. I'm your host, John fur with the cube. Mars stands for machine learning, automation, robotics, and space. It's great event brings together a lot of the industrial space machine learning and all the new changes in scaling up from going on the moon to, you know, doing great machine learning. And we've got two great guests here with kinda called lunar outpost, Justin Sears, CEO, Lauren, man. He's the co-founder and chief strategy officer lunar outpost. They're right next to us, watching their booth. Love the name, gentlemen. Welcome to the cube. >>Yeah. Thanks for having us, John. >>All right. So lunar outpost, I get the clues here. Tell us what you guys do. Start with that. >>Absolutely. So lunar outpost, we're a company based outta Colorado that has two missions headed to the moon over the course of the next 24 months. We're currently operating on Mars, which forest will tell you a little bit more about here in a second. And we're really pushing out towards expanding the infrastructure on the lunar surface. And then we're gonna utilize that to provide sustainable access to other planetary bodies. >>All right, far as teeing it up for you. Go, how cool is this? We don't, we wanna use every minute. What's the lunar surface look like? What's the infrastructure roads. You gonna pave it down. You what's going on. Well, >>Where we're going. No one has ever been. So, um, our first mission is going to Shackleton connecting Ridge on the south pole, the moon, and that's ripe to add infrastructure such as landing pads and other things. But our first Rover will be primarily driving across the surface, uh, exploring, uh, what the material looks like, prospecting for resources and testing new technologies. >>And you have a lot of technology involved. You're getting data in, you're just doing surveillance. What's the tech involved there. >>Yeah. So the primary technology that we're demonstrating is a 4g network for NOK. Um, we're providing them mobility services, which is basically like the old Verizon commercial. Can you hear me now? Uh, where the Rover drives farther and farther away from the Lander to test their signal strength, and then we're gonna have some other payloads ride sharing along with us for the ride >>Reminds me the old days of wifi. We used to call it war drive and you go around and try to find someone's wifi hotspot <laugh> inside the thing, but no, this is kind of cool. It brings up the whole thing. Now on lunar outpost, how big is the company? What's how what's to some of the stats heres some of the stats. >>Absolutely. So lunar outpost, 58 people, uh, growing quite quickly on track to double. So any of you watching, you want a job, please apply <laugh>. But with lunar outpost, uh, very similar to how launch companies provide people access to different parts of space. Lunar outpost provides people access to different spots on planetary bodies, whether it's the moon, Mars or beyond. So that's really where we're starting. >>So it's kinda like a managed service for all kinds of space utilities. If you kind of think about it, you're gonna provide services. Yeah, >>Absolutely. Yeah. It, it's definitely starting there and, and we're pushing towards building that infrastructure and that long term vision of utilizing space resources. But I can talk about that a little bit more here in a sec. >>Let's get into that. Let's talk about Mars first. You guys said what's going on with >>Mars. Absolutely. >>Yeah. So right now, uh, lunar outpost is part of the science team for, uh, Moxi, which is an instrument on the perseverance Rover. Yeah. Moxi is the first demonstration of space resource utilization on another planet. And what space resource utilization is basically taking resources on another planet, turning them into something useful. What Moxi does is it takes the CO2 from the atmosphere of Mars and atmosphere of Mars is mostly CO2 and it uses a process called solid oxide electrolysis to basically strip oxygen off of that CO2 to produce oh two and carbon monoxide. >>So it's what you need to self sustain on the surface. >>Exactly. It's not just sustaining, um, the astronauts, but also for producing oxygen for propellant. So it'll actually produce, um, it's a, it's a technology that'll produce a propellant for return rockets, um, to come back for Mars. So >>This is the real wildcard and all this, this, this exploration is how fast can the discoveries invent the new science to provide the life and the habitat on the surface. And that seems to be the real focus in the, in the conversations I heard on the keynote as well, get the infrastructure up so you can kinda land and, and we'll pull back and forth. Um, where are we on progress? You guys have the peg from one zero to 10, 10 being we're going, my grandmother's going, everyone's going to zero. Nothing's moving. >>We're making pretty rapid >>Progress. A three six, >>You know, I'll, I'll put it on an eight, John an >>Eight, I'll put it on >>Eight. This is why the mission force was just talking about that's launching within the next 12 months. This is no longer 10 years out. This is no longer 20 years away, 12 months. And then we have mission two shortly after, and that's just the beginning. We have over a dozen Landers that are headed to line surface this decade alone and heavy lift Landers and launchers, uh, start going to the moon and coming back by 2025. >>So, and you guys are from Colorado. You mentioned before you came on camera, right with the swap offices. So you got some space in Colorado, then the rovers to move around. You get, you get weird looks when people drive by and see the space gear. >>Oh yeah, definitely. So we have, um, you know, we have our facility in golden and our Nevada Colorado, and we'll take the vehicles out for strolls and you'll see construction workers, building stuff, and looking over and saying, what's >>Good place to work too. So you're, you're hiring great. You're doubling on the business model side. I can see a lot of demand. It's cheaper to launch stuff now in space. Is there becoming any rules of engagement relative to space? I don't wanna say verified, but like, you know, yet somehow get to the point where, I mean, I could launch a satellite, I could launch something for a couple hundred grand that might interfere with something legitimate. Do you see that on the radar because you guys are having ease of use so smaller, faster, cheaper to get out there. Now you gotta refine the infrastructure, get the services going. Is there threats from just random launches? >>It's a, it's a really interesting question. I mean, current state of the art people who have put rovers on other planetary bodies, you're talking like $3 billion, uh, for the March perseverance Rover. So historically there hasn't been that threat, but when you start talking about lowering the cost and the access to some of these different locations, I do think we'll get to the point where there might be folks that interfere with large scale operations. And that's something that's not very well defined in international law and something you won't really probably get any of the major space powers to agree to. So it's gonna be up to commercial companies to operate responsibly so we can make that space sustainable. And if there is a bad actor, I think it they'll weed themselves out over time. >>Yeah. It's gonna be of self govern, I think in the short term. Good point. Yeah. What about the technology? Where are we in the technology? What are some of the big, uh, challenges that we're overcoming now and what's that next 20 M stare in terms of the next milestone? Yeah, a tech perspective. >>Yeah. So the big technology technological hurdle that has been identified by many is the ability to survive the LUN night. Um, it gets exceptionally cold, uh, when the sun on the moon and that happens every 14 days for another, for, you know, for 14 days. So these long, cold lunar nights, uh, can destroy circuit boards and batteries and different components. So lunar outpost has invested in developing thermal technologies to overcome this, um, both in our offices, in the United States, but we also have opened a new office in, uh, Luxembourg in Europe. That's focusing specifically on thermal technologies to survive the lunar night, not just for rovers, but all sorts of space assets. >>Yeah. Huge. That's a hardware, you know, five, nine kind of like meantime between failure conversation, right. >><laugh> and it's, it gets fun, right? Because you talk five nines and it's such like, uh, you know, ingrained part of the aerospace community. But what we're pitching is we can send a dozen rovers for the cost of one of these historical rovers. So even if 25% of 'em fail, you still have eight rovers for the cost of one of the old rovers. And that's just the, economy's a scale. >>I saw James Hamilton here walking around. He's one of the legendary Amazonians who built out the data center. You might come by the cube. That's just like what they did with servers. Hey, if one breaks throw it away. Yeah. Why buy the big mainframe? Yeah. That's the new model. All right. So now about, uh, space space, that's a not space space, but like room to move around when you start getting some of these habitats going, um, how does space factor into the size of the location? Um, cuz you got the, to live there, solve some of the thermal problems. How do I live on space? I gotta have, you know, how many people gonna be there? What's your forecast? You think from a mission standpoint where there'll be dozens of people or is it still gonna be small teams? >>Yeah. >>Uh, what's that look like? >>I mean you >>Can guess it's okay. >>I mean, my vision's thousands of people. Yep. Uh, living and working in space because it's gonna be, especially the moon I think is a destination that's gonna grow, uh, for tourism. There's an insane drive from people to go visit a new destination. And the moon is one of the most unique experiences you could imagine. Yep. Um, in the near term for Artis, we're gonna start by supporting the Artis astronauts, which are gonna be small crews of astronauts. Um, you know, two to six in the near term. >>And to answer your question, uh, you know, in a different way, the habitat that we're actually gonna build, it's gonna take dozens of these robotic systems to build and maintain over time. And when we're actually talking, timelines, force talks, thousands of people living and working in space, I think that's gonna happen within the next 10 to 15 years. The first few folks are gonna be on the moon by 2025. And we're pushing towards having dozens of people living and working in space and by 2030. >>Yeah. I think it's an awesome goal. And I think it's doable question I'll have for you is the role of software in all this. I had a conversation with, uh, space nerd and we were talking and, and I said open sources everywhere now in the software. Yeah. How do you repair in space? Does you know, you don't want to have a firmware be down. So send down backhoe back to the United States. The us, wait a minute, it's the planet. I gotta go back to earth. Yeah. To get apart. So how does break fix work in space? How, how do you guys see that problem? >>So this one's actually quite fun. I mean, currently we don't have astronauts that can pick up a or change a tire. Uh, so you have to make robots that are really reliable, right. That can continuously operate for years at a time. But when you're talking about long-term repairs, there's some really cool ideas and concepts about standardization of some of these parts, you know, just like Lu knots on your car, right? Yeah. If everyone has the same Lu knots on their wheel, great. Now I can go change it out. I can switch off different parts that are available on the line surface. So I think we're moving towards, uh, that in the long >>Term you guys got a great company. Love the mission. Final question for both of you is I noticed that there's a huge community development around Mars, living on Mars, living on the moon. I mean, there's not a chat group that clubhouse app used, used to be around just kind of dying. But now it's when the Twitter spaces Reddit, you name it, there's a fanatical fan base that loves to talk about an engineer and kind of a collective intelligence, not, may not be official engineering, but they just love to talk about it. So there's a huge fan base for space. How does someone get involved if they really want to dive in and then how do you nurture that audience? How does that, is it developing? What's your take on this whole movement? It's it's beyond just being interested. It's it's become, I won't say cult-like but it's been, there's very, a lot of people in young people interested in space. >>Yeah. >>Yeah. There's, there's a whole, lots of places to get involved. There's, you know, societies, right? Like the Mar society there's technical committees, um, there's, you know, even potentially learning about these, you know, taking a space, resources master program and getting into the field and, and joining the company. So, um, we really, uh, thrive on that energy from the community and it really helps press us forward. And we hope to, uh, have a way to take everyone with us on the mission. And so stay tuned, follow our website. We'll be announcing some of that stuff soon. >>Awesome. And just one last, uh, quick pitch for you, John, I'll leave you with one thought. There are two things that space has an infinite amount of the first is power and the second is resources. And if we can find a way to access either of those, we can fundamentally change the way humanity operates. Yeah. So when you're talking about living on Mars long term, we're gonna need to access the resource from Mars. And then long term, once we get the transportation infrastructure in place, we can start bringing those resources back here to earth. So of course there are gonna be those people that sign up for that first mission out to Mars with SpaceX. But, uh, we'd love for folks to join on with us at lunar outpost and be a part of that kind of next leap accessing those resources. >>I love the mission, as always said, once in the cube, everything in star Trek will be invented someday. <laugh>, we're almost there except for the, the, uh, the transporter room. We don't have that done yet, but almost soon be there. All right. Well, thanks for coming. I, I really appreciate Justin for us for sharing. Great story. Final minute. Give a plug for the company. What are you guys looking for? You said hiring. Yep. Anything else you'd like to share? Put a plug in for lunar outpost. >>Absolutely. So we're hiring across the board, aerospace engineering, robotics engineering, sales marketing. Doesn't really matter. Uh, we're doubling as a company currently around 58 people, as we said, and we're looking for the top people that want to make an impact in aerospace. This is truly a unique moment. First time we've ever had continuous reliable operations. First time NASA is pushing really hard on the public private partnerships for commercial companies like ours to go out and create this sustainable presence on the moon. So whether you wanna work with us, our partner with us, we'd be excited to talk to you and, uh, yeah. Please contact us at info. Lunar outpost.com. >>We'll certainly follow up. Thanks for coming. I love the mission we're behind you and everyone else is too. You can see the energy it's gonna happen. It's the cube coverage from re Mars new actions happening in space on the ground, in the, on the moon you name it's happening right here in Vegas. I'm John furrier. Thanks for watching.

(upbeat music) >> Hey everyone. Welcome to theCUBE's coverage of PagerDuty Summit '22. I'm Lisa Martin. I'm here with one of our alumni. Jonathan Rendy joins me, the SVP of products at PagerDuty. Jonathan, great to have you on the program. >> It's wonderful to be here. Thank you, Lisa. >> Lisa: It's great to be back at PagerDuty Summit. So much news this morning. So much buzz and excitement. Talk to me about some of the things that you're most excited about as we are in such a massively different work environment these days. >> Yeah, so much has been going on and we've been innovating in so many areas. I think you heard in the keynote this morning, automation is such a foundational part of PagerDuty now, and that comes to us via the Rundeck acquisition from a couple of years ago. And we've also extended PagerDuty to new audiences. So we've been a big part of the back office for a long time with SREs and developers and ITOps, and we've really come to realize that the front office is so important, and one of the leading departments there that we can make an impact and extend into with our solution is customer service. >> Lisa: Customer service is absolutely critical these days as we all know. One of the things that was in very short supply the last couple of years is patience. Patience when you're a consumer, patience when you're a business person. And so the voice of the customer, being able to get things escalated quickly and resolved quickly, to those customer service folks is critical for any organization. Without that, people easily go to Twitter or Reddit and escalate problems publicly, and suddenly that becomes a brand reputation problem for the organization. >> Yeah, you're spot on. I mean expectations are at an all time high. People's tolerance is at an all time low. And that gets translated, I always think, to the front door of the organization when there is something that doesn't go right, and that's typically the poor customer service agents who have to deal with that kind of feedback and open up cases and deal with it. And, you know, unfortunately they're not armed a lot of times with the information that could help them not only be better reactive but be better proactive and have information to actually turn what could be a bad experience into a really good one. >> Lisa: You mentioned something really interesting. Jonathan had a great fireside chat this morning that I was able to watch. And you said it takes, for every negative experience that a customer or consumer has, it takes seven additional positive experiences to turn them back around. And I thought, wow, do we even have the patience or the tolerance to your point, to give a business seven more options to turn our experience around? >> Yeah, it's tough. And it's very, very hard for a lot of organizations and nobody's exempt from it. The connection between the front office and the back office, there is no real gold standard for that. And so, is there a path forward? Is there a way forward? We believe there is and we believe there's a way to help, but teams really need to focus on getting information to those folks so that these very negative kind of situations can become a customer satisfaction, can become something where a customer feels like, "Wow, I didn't expect that." There was another statistic that we heard about the other day, which is, you know, greater than 50% of issues are often identified from customers, not from the monitoring products. So, you know, whether it's 50, or 40, or 30, it doesn't really matter. The customer is a signal and it's so important to be attentive to that signal. >> Lisa: What are some, well... you'd rather have that found out before the customer even notices. Talk to me about some of the things that PagerDuty just announced that are going to help not just the front office, back office kind of blurred lines there, but also to ensure that the incident response is smarter, it's faster, and it's being able to detect things before the customer even notices. >> Yeah, so the trick, the $64,000 question, however you want to phrase it or characterize it, is all about getting teams ahead of problems. And while I think it's unrealistic to ever, like every single customer, get ahead of any issue that any customer could see, it's so important that the first customer that comes in with an issue becomes near to the last customer that comes in with an issue, meaning that one, everybody knows about that and they know how it's related to existing issues. That's important so that other customers can be preemptively explained, but then given what PagerDuty's always done, sometimes we know about issues on the back end that may be impacting customers that they don't know about yet. So a shopping cart may not be working correctly, but before somebody hits it, if the customer service team knows about that right away, they can proactively get ready for communication to their customers to let them know, "Hey, there might be an issue here. We know about it, we're working on it. Please stay tuned", or direct them to something else that can help them. >> I can imagine that goes a long way to CSAT scores NPS scores, brand reputation, reducing churn. >> Jonathan: Oh, big time, big time, whether it's CSAT or NPS, you know, everybody is familiar on that big shopping day of the year, of getting that big sale, going to, wanting to order that, and then either not being able to complete the order or having to wait too long for it to be delivered. And then you end up having to go to a brick and mortar outlet to buy it there anyway. So there's so many opportunities and those situations will happen, outages will occur, it's just a matter of when. Those can be avoided in those bad situations via the use of other discounts, coupons, other customer satisfaction areas. You can turn those bad experiences into really good ones. >> Definitely. And I think we all have that expectation that that's going to happen, when outages do happen, 'cause to your point, those are the things that it's not, "Is it going to happen?" It's when, and how quickly can we recover from that so we minimize the impact on everybody else? Couple of the things that you announced this morning, Incident Objects and Service Cloud, talk to me about what that is. It looks like a deeper partnership integration with Salesforce. What are some of the benefits that your customers can expect? >> Jonathan: Yeah, so we have several partners in the front office, and one of the biggest known to the world is Salesforce. And so we've been working with the Service Cloud team there for going on a couple of years now, better integrating our platform into what they're doing. And we've actually built an app that runs inside of Service Cloud. So a customer service agent doesn't need to swivel chair around and look at other products in order to understand what's going on in the back office, it's all built into their experience. That's one, number one. Number two, we've upped that relationship and invested more where Service Cloud, Salesforce has come out with a new incident capability. And so we're integrating directly to that so we can sync up with that system of record from PagerDuty. So wherever the issues are found, whether it's in distributed DevOps teams, or whether it's in a central team, or whether it's a case agent working on the front end, everything will be kept in sync. So we're really excited about that bidirectional integration >> That bidirectional sync is critical. We have, you know, one of the biggest challenges, we've been talking about it since we were back at HP days back in the day, Jonathan, silos, right? That's one of the biggest challenges, is there's still silos between teams and systems, which impacts, you know, time to identify an incident, time to repair that incident, and then of course let alone repair the relationship with the customer on the other end. >> Jonathan: Yeah, yeah, and there's some great examples, working with our own customers, that we run into where when we can make that golden connection between the front office and the back office and sync up customer cases with incidents, magic starts to happen. So we've seen situations where the back office team working on an incident doesn't realize that the issue is customer impacting. They don't realize that there were three, and then four, and then five case tickets opened up, that it's really impacting customers. And when they see that rise in customer impact, they change the priority. They get other people involved. The urgency changes on that issue. Imagine working in a world where that visibility doesn't exist, people continue to work at their own pace and who suffers? The customer, the customer experience. >> Lisa: Without that visibility, so much can suffer. And quickly, we also have this expectation, I mentioned one of the things that was in short supply in the pandemic as patience and tolerance, but another thing is we expect things in real time, realtime access to data, realtime access to the customer, to a product or service, is no longer a nice to have, it is business critical for organizations in every industry. >> Yeah. Yep. And you know, customer service is such a obviously service-centered activity, that it can be, you know, death by a thousand paper cuts to a customer experience. And to the point that you're raising, nobody likes to contact finally someone as an agent, and then get passed to another agent, who gets passed to another agent, and have to repeat the problem that you're having so many times. What if we could capture all that context together. What if we could empower that agent to be able to manage that case from beginning to end more effectively? Like what would the reflection be on the customers who are calling in? They would feel taken care of. They would feel like they were heard. They wouldn't feel ignored, so to speak. So all of that is a part of our solution that we're partnering not only with Salesforce, but also with Zendesk and others to deliver. >> Talk about the automation in CS Ops and some of the main benefits. Obviously, you mentioned this a minute ago, but the ability to empower those agents to have that context is night and day compared to, you know, the solutions from back in the day. >> Jonathan: Yeah. Automation is so fundamental and foundational to everything we do at PagerDuty and if you look at all the audiences that make use of PagerDuty today, whether it's developers, whether it's IT operations and now customer service agents, it's no surprise that, you know, everyone has to do more with less, everyone's working in a more siloed, disconnected manner. So the amount of potential toil, potential manual steps, having to open up a system to get the status of something and then pivot over to my other system, or do research, or ask a customer multiple times when it could automatically be captured what their problem is, what the environment is, and all that information from an agent could be automatically inserted into the case. How valuable is that? Not only for the case, but then the teams on the back end, that helps them diagnose and fix those problems. So the amount of automation that we've built and now just announced and made available as a part of Customer Service Ops just like in DevOps with our automation actions, really important to automating some of those manual toil steps for those agents where, again, 50, 60% of their time is spent doing manual activities. We can get rid of that. We can empower them to do more, to do more with less. >> To do more with less and do more faster and it makes such a huge difference there. Talk a little bit about the DevOps-CS Ops relationship. You know, one of the things that's kind of ironic is here we are in 2022, we have so many tools to collaborate and connect, yet there's still so many silos, and that can either break trust between a customer and a vendor or a solution provider, or it can really facilitate trust. And that was a big theme of the keynote this morning is that trust. But talk about the trust that is you, PagerDuty, really thinks essential between the DevOps folks and the CS Ops folks. >> Yeah. It's critical, as I kind of mentioned before, there really isn't a golden path, a golden connection, a standard that's been set between CS, the customer service organizations and the back office. And how I like to characterize it and what I've seen over the years working with customers is frequently it's almost like when I was a little kid I lived nearby a semi-pro baseball team and I could never get tickets and I would ride my bike to the back of the fence and I would look at the game through a little knot hole in the fence and I'd be like, "Man that would be so great to be in there" Well, that's essentially customer service, sitting there looking at the game happening, constantly trying to interrupt the teams and saying, "Hey, what about us?" And so, by making that a seamless connection, by making customer service a part of the solution, a part of the team in a non impactful, intrusive way, everybody gets what they need, no one's interrupted, and now those customer service agents, they're sitting in the stands. They're not looking through the little knot hole at the back of the center field. >> Lisa: Well you got to tell us, did you ever get tickets? Can you go to pro games now? >> No. No. >> Aww >> Still waiting. >> Oh man. Talk to me, last question here, I asked you before we started filming if you had a crystal ball or a Magic 8-Ball, so next time at least bring me a Magic 8-Ball. What are some of the predictions that you have as you see where we are in... now half of calendar '22 almost gone, the announcements coming from PagerDuty today, this synergy is between PagerDuty, its, what, 21,000 plus customers, your partners, What are some of the things that you're excited about that are coming? >> Jonathan: So a couple things. One is I really think the first example, we talk about the Operations Cloud, what PagerDuty is. And to me, what it really is, is it's not just the DevOps audiences and the ITOps and the SRE teams in the back offices that have to deal with interrupted realtime work, but it's other parts of the organization as well that have to get proactive versus reactive. And the first of those, the first step that kind of personifies the Operations Cloud outside of that back office is customer service. But there will be more, there will be more, whether it's security or other teams. So it's the audiences that can participate and engage in realtime work, that's one. And then I think in the area of customer service and Customer Service Operations, where we are, what we've been doing and what we've been so focused on is making sure that those agents can start to get proactive and start to get to the next step. But wouldn't it be amazing if we could help them, proactively, in a targeted way, talk to their customers and provide that as an automated part of the process. Today that's very manual, so we can empower them with information, but a lot of their communication with their customers is manual. What if we could automate that? And that's our plans, and that's what I'm really excited about doing. >> Can you imagine the trust built between an empowered, proactive CS agent and a customer on the other end. The sky is the limit on that one. >> If I'm a platinum customer or I'm a silver customer, I'm paying for a certain level of customer service. How great would it be if based on the extra that I'm paying, I'm actually getting that service proactively and I'm hearing about issues long before I see them. That to me is building trust. >> Lisa: Absolutely. Jonathan, thank you so much for joining me on theCUBE today. Great to see you back in person. Great to hear some of the things coming down the road for PagerDuty, and we're excited to see your predictions come true. Thanks for your time. >> Likewise, Lisa. Thank you very much. >> My pleasure. For Jonathan Rendy. I'm Lisa Martin covering theCUBE on the ground at PagerDuty summit '22. Stick around, I'll be right back with my next guest. (upbeat music)

(upbeat music) >> Hey everyone. Welcome to theCUBE's coverage of PagerDuty Summit '22. I'm Lisa Martin. I'm here with one of our alumni. Jonathan Rendy joins me, the SVP of products at PagerDuty. Jonathan, great to have you on the program. >> It's wonderful to be here. Thank you, Lisa. >> Lisa: It's great to be back at PagerDuty Summit. So much news this morning. So much buzz and excitement. Talk to me about some of the things that you're most excited about as we are in such a massively different work environment these days. >> Yeah, so much has been going on and we've been innovating in so many areas. I think you heard in the keynote this morning, automation is such a foundational part of PagerDuty now, and that comes to us via the Rundeck acquisition from a couple of years ago. And we've also extended PagerDuty to new audiences. So we've been a big part of the back office for a long time with SREs and developers and ITOps, and we've really come to realize that the front office is so important, and one of the leading departments there that we can make an impact and extend into with our solution is customer service. >> Lisa: Customer service is absolutely critical these days as we all know. One of the things that was in very short supply the last couple of years is patience. Patience when you're a consumer, patience when you're a business person. And so the voice of the customer, being able to get things escalated quickly and resolved quickly, to those customer service folks is critical for any organization. Without that, people easily go to Twitter or Reddit and escalate problems publicly, and suddenly that becomes a brand reputation problem for the organization. >> Yeah, you're spot on. I mean expectations are at an all time high. People's tolerance is at an all time low. And that gets translated, I always think, to the front door of the organization when there is something that doesn't go right, and that's typically the poor customer service agents who have to deal with that kind of feedback and open up cases and deal with it. And, you know, unfortunately they're not armed a lot of times with the information that could help them not only be better reactive but be better proactive and have information to actually turn what could be a bad experience into a really good one. >> Lisa: You mentioned something really interesting. Jonathan had a great fireside chat this morning that I was able to watch. And you said it takes, for every negative experience that a customer or consumer has, it takes seven additional positive experiences to turn them back around. And I thought, wow, do we even have the patience or the tolerance to your point, to give a business seven more options to turn our experience around? >> Yeah, it's tough. And it's very, very hard for a lot of organizations and nobody's exempt from it. The connection between the front office and the back office, there is no real gold standard for that. And so, is there a path forward? Is there a way forward? We believe there is and we believe there's a way to help, but teams really need to focus on getting information to those folks so that these very negative kind of situations can become a customer satisfaction, can become something where a customer feels like, "Wow, I didn't expect that." There was another statistic that we heard about the other day, which is, you know, greater than 50% of issues are often identified from customers, not from the monitoring products. So, you know, whether it's 50, or 40, or 30, it doesn't really matter. The customer is a signal and it's so important to be attentive to that signal. >> Lisa: What are some, well... you'd rather have that found out before the customer even notices. Talk to me about some of the things that PagerDuty just announced that are going to help not just the front office, back office kind of blurred lines there, but also to ensure that the incident response is smarter, it's faster, and it's being able to detect things before the customer even notices. >> Yeah, so the trick, the $64,000 question, however you want to phrase it or characterize it, is all about getting teams ahead of problems. And while I think it's unrealistic to ever, like every single customer, get ahead of any issue that any customer could see, it's so important that the first customer that comes in with an issue becomes near to the last customer that comes in with an issue, meaning that one, everybody knows about that and they know how it's related to existing issues. That's important so that other customers can be preemptively explained, but then given what PagerDuty's always done, sometimes we know about issues on the back end that may be impacting customers that they don't know about yet. So a shopping cart may not be working correctly, but before somebody hits it, if the customer service team knows about that right away, they can proactively get ready for communication to their customers to let them know, "Hey, there might be an issue here. We know about it, we're working on it. Please stay tuned", or direct them to something else that can help them. >> I can imagine that goes a long way to CSAT scores NPS scores, brand reputation, reducing churn. >> Jonathan: Oh, big time, big time, whether it's CSAT or NPS, you know, everybody is familiar on that big shopping day of the year, of getting that big sale, going to, wanting to order that, and then either not being able to complete the order or having to wait too long for it to be delivered. And then you end up having to go to a brick and mortar outlet to buy it there anyway. So there's so many opportunities and those situations will happen, outages will occur, it's just a matter of when. Those can be avoided in those bad situations via the use of other discounts, coupons, other customer satisfaction areas. You can turn those bad experiences into really good ones. >> Definitely. And I think we all have that expectation that that's going to happen, when outages do happen, 'cause to your point, those are the things that it's not, "Is it going to happen?" It's when, and how quickly can we recover from that so we minimize the impact on everybody else? Couple of the things that you announced this morning, Incident Objects and Service Cloud, talk to me about what that is. It looks like a deeper partnership integration with Salesforce. What are some of the benefits that your customers can expect? >> Jonathan: Yeah, so we have several partners in the front office, and one of the biggest known to the world is Salesforce. And so we've been working with the Service Cloud team there for going on a couple of years now, better integrating our platform into what they're doing. And we've actually built an app that runs inside of Service Cloud. So a customer service agent doesn't need to swivel chair around and look at other products in order to understand what's going on in the back office, it's all built into their experience. That's one, number one. Number two, we've upped that relationship and invested more where Service Cloud, Salesforce has come out with a new incident capability. And so we're integrating directly to that so we can sync up with that system of record from PagerDuty. So wherever the issues are found, whether it's in distributed DevOps teams, or whether it's in a central team, or whether it's a case agent working on the front end, everything will be kept in sync. So we're really excited about that bidirectional integration >> That bidirectional sync is critical. We have, you know, one of the biggest challenges, we've been talking about it since we were back at HP days back in the day, Jonathan, silos, right? That's one of the biggest challenges, is there's still silos between teams and systems, which impacts, you know, time to identify an incident, time to repair that incident, and then of course let alone repair the relationship with the customer on the other end. >> Jonathan: Yeah, yeah, and there's some great examples, working with our own customers, that we run into where when we can make that golden connection between the front office and the back office and sync up customer cases with incidents, magic starts to happen. So we've seen situations where the back office team working on an incident doesn't realize that the issue is customer impacting. They don't realize that there were three, and then four, and then five case tickets opened up, that it's really impacting customers. And when they see that rise in customer impact, they change the priority. They get other people involved. The urgency changes on that issue. Imagine working in a world where that visibility doesn't exist, people continue to work at their own pace and who suffers? The customer, the customer experience. >> Lisa: Without that visibility, so much can suffer. And quickly, we also have this expectation, I mentioned one of the things that was in short supply in the pandemic as patience and tolerance, but another thing is we expect things in real time, realtime access to data, realtime access to the customer, to a product or service, is no longer a nice to have, it is business critical for organizations in every industry. >> Yeah. Yep. And you know, customer service is such a obviously service-centered activity, that it can be, you know, death by a thousand paper cuts to a customer experience. And to the point that you're raising, nobody likes to contact finally someone as an agent, and then get passed to another agent, who gets passed to another agent, and have to repeat the problem that you're having so many times. What if we could capture all that context together. What if we could empower that agent to be able to manage that case from beginning to end more effectively? Like what would the reflection be on the customers who are calling in? They would feel taken care of. They would feel like they were heard. They wouldn't feel ignored, so to speak. So all of that is a part of our solution that we're partnering not only with Salesforce, but also with Zendesk and others to deliver. >> Talk about the automation in CS Ops and some of the main benefits. Obviously, you mentioned this a minute ago, but the ability to empower those agents to have that context is night and day compared to, you know, the solutions from back in the day. >> Jonathan: Yeah. Automation is so fundamental and foundational to everything we do at PagerDuty and if you look at all the audiences that make use of PagerDuty today, whether it's developers, whether it's IT operations and now customer service agents, it's no surprise that, you know, everyone has to do more with less, everyone's working in a more siloed, disconnected manner. So the amount of potential toil, potential manual steps, having to open up a system to get the status of something and then pivot over to my other system, or do research, or ask a customer multiple times when it could automatically be captured what their problem is, what the environment is, and all that information from an agent could be automatically inserted into the case. How valuable is that? Not only for the case, but then the teams on the back end, that helps them diagnose and fix those problems. So the amount of automation that we've built and now just announced and made available as a part of Customer Service Ops just like in DevOps with our automation actions, really important to automating some of those manual toil steps for those agents where, again, 50, 60% of their time is spent doing manual activities. We can get rid of that. We can empower them to do more, to do more with less. >> To do more with less and do more faster and it makes such a huge difference there. Talk a little bit about the DevOps-CS Ops relationship. You know, one of the things that's kind of ironic is here we are in 2022, we have so many tools to collaborate and connect, yet there's still so many silos, and that can either break trust between a customer and a vendor or a solution provider, or it can really facilitate trust. And that was a big theme of the keynote this morning is that trust. But talk about the trust that is you, PagerDuty, really thinks essential between the DevOps folks and the CS Ops folks. >> Yeah. It's critical, as I kind of mentioned before, there really isn't a golden path, a golden connection, a standard that's been set between CS, the customer service organizations and the back office. And how I like to characterize it and what I've seen over the years working with customers is frequently it's almost like when I was a little kid I lived nearby a semi-pro baseball team and I could never get tickets and I would ride my bike to the back of the fence and I would look at the game through a little knot hole in the fence and I'd be like, "Man that would be so great to be in there" Well, that's essentially customer service, sitting there looking at the game happening, constantly trying to interrupt the teams and saying, "Hey, what about us?" And so, by making that a seamless connection, by making customer service a part of the solution, a part of the team in a non impactful, intrusive way, everybody gets what they need, no one's interrupted, and now those customer service agents, they're sitting in the stands. They're not looking through the little knot hole at the back of the center field. >> Lisa: Well you got to tell us, did you ever get tickets? Can you go to pro games now? >> No. No. >> Aww >> Still waiting. >> Oh man. Talk to me, last question here, I asked you before we started filming if you had a crystal ball or a Magic 8-Ball, so next time at least bring me a Magic 8-Ball. What are some of the predictions that you have as you see where we are in... now half of calendar '22 almost gone, the announcements coming from PagerDuty today, this synergy is between PagerDuty, its, what, 21,000 plus customers, your partners, What are some of the things that you're excited about that are coming? >> Jonathan: So a couple things. One is I really think the first example, we talk about the Operations Cloud, what PagerDuty is. And to me, what it really is, is it's not just the DevOps audiences and the ITOps and the SRE teams in the back offices that have to deal with interrupted realtime work, but it's other parts of the organization as well that have to get proactive versus reactive. And the first of those, the first step that kind of personifies the Operations Cloud outside of that back office is customer service. But there will be more, there will be more, whether it's security or other teams. So it's the audiences that can participate and engage in realtime work, that's one. And then I think in the area of customer service and Customer Service Operations, where we are, what we've been doing and what we've been so focused on is making sure that those agents can start to get proactive and start to get to the next step. But wouldn't it be amazing if we could help them, proactively, in a targeted way, talk to their customers and provide that as an automated part of the process. Today that's very manual, so we can empower them with information, but a lot of their communication with their customers is manual. What if we could automate that? And that's our plans, and that's what I'm really excited about doing. >> Can you imagine the trust built between an empowered, proactive CS agent and a customer on the other end. The sky is the limit on that one. >> If I'm a platinum customer or I'm a silver customer, I'm paying for a certain level of customer service. How great would it be if based on the extra that I'm paying, I'm actually getting that service proactively and I'm hearing about issues long before I see them. That to me is building trust. >> Lisa: Absolutely. Jonathan, thank you so much for joining me on theCUBE today. Great to see you back in person. Great to hear some of the things coming down the road for PagerDuty, and we're excited to see your predictions come true. Thanks for your time. >> Likewise, Lisa. Thank you very much. >> My pleasure. For Jonathan Rendy. I'm Lisa Martin covering theCUBE on the ground at PagerDuty summit '22. Stick around, I'll be right back with my next guest. (upbeat music)

>>Hey everyone. Welcome to the cubes coverage of PagerDuty summit 22. I'm Lisa Martin. I'm here with one of our alumni. Jonathan Ren joins me the SVP of products at PagerDuty. Jonathan. Great to have you on the program. >>It's wonderful to be here. Thank you, Lisa. >>It's great to be back at PagerDuty summit. So much news this morning. So much buzz and excitement. Talk to me about some of the things that you are most excited about as we are in such a massively different work environment these days. >>Yeah, so much has been going on and we've been innovating in so many areas. Uh, I think you heard in the keynote this morning, automation is such a foundational part of PagerDuty now, and that comes to us via the Rundeck acquisition from a couple of years ago. And we've also extended a PagerDuty to new audiences. So we've been a big part of the back office for a long time with SREs and developers and it ops. And we've really come to realize that, you know, the front office is so important. And one of the, the leading departments there that we can make an impact and extend into with our solution is customer service. >>Customer service is absolutely critical these days, as we all know, one of the things that was in very short supply the last couple of years is patients patients when you're a consumer patients, when you're a business person. And so the, the, the voice of the customer being able to get things escalated quickly and resolve quickly to those customer service folks is critical for any organization without that people easily go to Twitter or Reddit and escalate problems publicly. And suddenly that becomes a brand reputation problem for the organization. >>Yeah, you you're you're spot on, I mean, expectations are at an all time high people's tolerance is at an all time low and that gets translated. I always think to the front door of the organization when there is something that doesn't go right, and that's typically the poor customer service agents who have to deal with that kind of feedback and open up cases and deal with it. And, you know, unfortunately they're not armed a lot of times with the information that could help them not only be better reactive, but be better proactive and have information to actually turn what could be a bad experience into a really good one. >>You mentioned something really interesting. Jonathan had a great fireside chat this morning that I was able to watch. And you said it takes for every negative experience that a customer or consumer has. It takes seven additional positive experiences to turn them back around. And I thought, wow, do we even have the patience or the tolerance to your point to give a business seven more options to turn our experience around? >>Yeah, it's tough. And it's it, it's very, very hard for a lot of organizations and nobody's exempt from it. Um, the connection between the front office and the back office, there is no real gold standard for that. And, and, and so like, is there, is there a path forward? Is there a way forward? We believe there is, and we believe there's a way to help, but teams really need to focus on getting information to those folks so that these very negative kind of situations can become a customer satisfaction, can become something where a customer feels like, wow, I didn't expect that. Um, there was another statistic that, uh, we, we heard about the other day, which is, you know, greater than 50% of issues are often identified from customers, not from the monitoring products. So, you know, whether it's 50 or 40 or 30, it doesn't really matter. The customer is a signal and it's so important to be attentive to that signal. >>What are some of the, well, the, the LA you'd rather have that found out before the customer even notices? Talk to me about some of the things that PagerDuty just announced that are gonna help, not just the front office back office kind of blurred, um, blurred lines there, but also to ensure that the incident response is smarter, it's faster and it's being able to detect things before the customer even notices. >>Yeah. So the, the trick, the, the $64,000 question, however you want to phrase it or characterize it is all about getting teams ahead of problems. And while I think it's unrealistic to ever like every single customer get ahead of any issue that any customer could see, it's so important that the first customer that comes in with an issue becomes near to the last customer that comes in with an issue, meaning that one, everybody knows about that, and they know how it's related to existing issues. That's important so that other customers can be preemptively explained, but then given what PagerDuty's always done, sometimes we know about issues on the back end that may be impacting customers that they don't know about yet. So a shopping cart may not be working correctly, but before somebody hits it, if the customer service team knows about that right away, they can proactively get ready for communication to their customers to let them know, Hey, there might be an issue here we know about it, we're working on it. Please stay tuned or direct them to something else that can help them. >>I can imagine that goes a long way to, um, CSAT scores, NPS scores, brand reputation, reducing churn, >>Oh, big time, big time, whether it's CSAT or NPS. You know, everybody is familiar on that big shopping day of the year of getting that big sale, going to wanting to order that. And then either not being able to complete the order or having to wait too long for it to be delivered. And then you end up having to go to a brick and mortar, uh, outlet to buy it there anyway. So there's so many opportunities and those situations will happen. Outages will occur. It's just a matter of when those can be avoided in those bad situations, via the use of other discounts, coupons, other Jo you know, uh, customer satisfaction areas. You can turn those bad experiences into really good ones. >>Definitely. And I think we all, we all have that expectation that that's gonna happen when things do when outages do happen, cuz to your point that's, those are the things that's not, is it gonna happen? It's when and how quickly can we recover from that? So it's, we minimize the impact on everybody else. Couple the things that you announced this morning, incident objects and service cloud. Talk to me about what that is. It looks like a deeper partnership integration with Salesforce. What are some of the benefits that your customers can expect? >>Yeah, so we have several partners in the front office and one of, one of the biggest, uh, known to the world is Salesforce. And so we've been working with the service cloud team there for going on a couple of years now, uh, better integrating our platform into what they're doing. And we've actually built an app that runs inside of service cloud. So a customer service agent doesn't need to swivel chair around and look at other products in order to understand what's going on in the back office, it's all built into their experience. That's one number one, number two, uh, we've upped that relationship and invested more where service cloud Salesforce has come out with a new incident capability. And so we're integrating directly to that. So we can sync up with that system of record from PagerDuty. So wherever the issues are found, whether it's in distributed DevOps teams or whether it's in a central team or whether it's a case agent working on the front end, everything will be kept in sync. So we're really excited about that. Bidirectional direct, uh, integration >>That bidirectional sync is critical. We have, you know, one of the biggest challenges we've been talking about it since we were back at HP days back in the day, Jonathan silos, right? That's one of the biggest challenges is there's still silos between teams and systems, which impacts, you know, time to identify an incident, time to repair that incident. And then of course, let alone repair the relationship with the customer on the other end. >>Yeah. Yeah. And there's some great examples working with our own customers that we run into where when we can make that golden connection between the front office and the back office and sync up customer cases with incidents magic starts to happen. So, uh, we've seen situations where the back office team working on an incident, uh, doesn't realize that the issue is customer impacting. They don't realize that there were three and then four, and then five case tickets opened up that it's really impacting customers. And when they see that rise in customer impact, they change the priority. They get other people involved. The urgency changes on that issue. Imagine working in a world where that visibility doesn't exist, people continue to work at their own pace and who suffers the customer, the customer experience >>Without that visibility so much can suffer. And, and quickly, we also had this expectation. I, I mentioned one of the things that was in short supply in the pandemic as patients and tolerance. But another thing is we expect things in real time, real time, access to data, real time access to the customer to a product or service is no longer a nice to have it is business critical for organizations in every industry. >>Yeah. Yep. And you know, the customer service is such a obviously service centered activity that it can be, you know, death by a thousand paper cuts to a customer experience. And to the point that you're raising, nobody likes to contact finally, someone in as an agent and then get passed to another agent who gets passed to another agent and have to repeat the problem that you're having so many times what if we could capture all that context together. What if we could empower that agent to be able to manage that case from beginning to end more effectively? Like what would the reflection be on the customers who are calling in, they would feel taken care of. They would feel like they were heard. Yeah. They wouldn't feel ignored, so to speak. So all of that is a part of our solution that we're partnering, not only with Salesforce, but also with Zendesk and others to deliver, >>Talk about the automation in CSOPs and some of the main benefits. Obviously you mentioned this a minute ago, but the ability to empower those agents to have that context is night and day compared to, you know, the solutions from back in the >>Day. Yeah. Automation is so fundamental and foundational to everything we do at PagerDuty. And if you look at all the audiences that make use of PagerDuty today, whether it's developers, whether it's, uh, it operations and now customer service agents, it's no surprise that, you know, everyone has to do more with less everyone's working in a more siloed, disconnected manner. So the amount of potential toil, potential manual steps, uh, having to open up a system to get the status of something and then pivot over to my other system or do research or ask a customer multiple times when it could automatically be captured, what their problem is, what the environment is. And all that information from an agent could be automatically inserted into the case. How valuable is that? Not only for the case, but then the teams on the back end that that helps them diagnose and fix those problems. So the amount of automation that we've built and now just announced and made available as a part of customer service ops, just like in DevOps with our automation actions, really important to automating some of those manual toil steps for those agents where again, um, 50, 60% of their time is spent doing manual activities. We can get rid of that. We can empower them to do more, to do more with less, >>To do more with less and, and do more faster and make such a huge difference there. Talk a little bit about the, the DevOps CS ops relationship. You know, one of the, one of the things that's kind of ironic is here we are in, in 2022, we have so many tools to collaborate and connect yet. There's still so many silos and that can either break trust between a customer and a, and a vendor or a solution provider, or it can really facilitate trust. And that was a big theme of, uh, the keynote this morning is that trust. But talk about the trust that is you PagerDuty really things essential between the DevOps folks and the CS ops folks. >>Yeah. It's, it's, it's critical. As I kind of mentioned before, there really isn't a golden path, a golden connection, uh, a standard that's been set between CS, the customer service organizations and the back office and how I like to characterize it. And what I've seen over the years, working with customers is frequently. It's, it's almost like when I was a little kid, I lived nearby a, um, a semi-pro baseball team and I could never get tickets and I would ride my bike to the back of the fence. And I would look at the game through a little knot hole in the fence and I'd be like, man, that would be so great to be in there. That's essentially customer service sitting there looking at the game happening constantly, like trying to interrupt the teams and saying, Hey, what about us? Like, and so by making that a seamless connection by making customer service a part of the solution, a part of the team in a non impactful intrusive way, everybody gets what they need. No one's interrupted. And now those customer service agents they're sitting in the stands. They're not looking through the little knothole at the back of the center field. >>Well, you gotta tell, did you ever get tickets? Can you go to pro games now? >>Uh, no. No. Oh, still waiting. >>Oh man. Talk to me last question here. I asked you before we, we started filming if you had a crystal ball or, or a magic eight ball. So next time at least bring me a magic eight ball. What are some of the predictions that you have is as you see where we are in now, half of calendar, 22, almost gone. The announcements coming from PagerDuty today, the synergy is between PagerDuty. It's what 21,000 plus customers, your partners. What are some of the things that you're excited about that are coming? >>So a couple things. One is, I, I really think the first example we talk about the operations cloud, what PagerDuty is. And to me, what it really is, is it's not just the DevOps audiences and the it ops and the SRE teams in the back office back offices that have to deal with interrupted, um, real time work, but it's other parts of the organization as well, um, that have to get proactive versus reactive. And the first of those that the, the first step that kind of personifies the operations cloud outside of that back office is customer service. But there will be more, there will be more whether it's security or other teams. So it's the audiences that can participate and engage in like real time work. That's one. And then I think in the area of customer service and customer service operations, where we are, what we've been doing and what we've been so focused on is making sure that those agents can start to get proactive and start to get to the next step. But wouldn't it be amazing if we could help them proactively in a targeted way, talk to their customers, uh, and provide that as an automated part of the process today, that's very manual so we can empower them with information, but a lot of their communication with their customers is manual. What if we could automate that? And that's our plans, and that's what I'm really excited about >>Doing. Can you imagine that the trust built between an empowered, proactive CS agent and a customer on the other end that there's the sky is the limit on that one? >>Uh, if I'm a platinum customer or I'm a silver customer on paying for a certain level of customer service, how great would it be if based on the extra that I'm paying, I'm actually getting that service right. Proactively and I'm hearing about issues long before I see them. That to me is building trust. >>Absolutely. Jonathan, thank you so much for joining me on the cube today. Great to see you back in person. Great to hear some of the things coming down the road for PagerDuty, and we're excited to, to see your predictions come true. <laugh> thanks for your time. >>Likewise, Lisa, thank you very much. >>My pleasure for Jonathan Ren. I'm Lisa Martin covering the cube on the ground at PagerDuty summit 22, stick around of your rack back with my next guest.

>>Welcome everyone to this cube conversation featuring unit Q. I'm your host, Lisa Martin. And we are excited to be joined by Christian Vickle, the founder and CEO of unit Q Christian. Thank you so much for joining me today. >>Thank you so much, Lisa pleasure to be here. >>Let's talk a little bit about unit Q. You guys were founded in 2018, so pretty recent. What is it that unit Q does. And what were some of the gaps in the market that led you to founding the company? >>Yep. So me and my co-founder Nick, we're actually doing our second company now is the unit Q is number two, and our first company was called scout years ago. We were back ES wicks and it was very different from unit Q. It's a social network for meeting people. And it was really during that experience where we saw the impact that quality of the experience quality of the product can have on your growth trajectory and the challenges we faced. How do we test everything before we ship it? And in reality, a modern company will have, let's say, 20 languages supported you support Android, Iowas, web big screen, small screen, you have 20 plus integrations and you have lots of different devices out there that might run your binary a little differently. So who is the ultimate test group of all of these different permutation and that's the end user. >>And we, we saw the, the big gap in the market, sort of the dream platform for us was unit queue. So if, if this would've existed back in the day, we would've been a, a happy purchaser and customer, and it really comes down to how do we, how do we harness the power of user feedback? You know, the end user, that's testing your product every single day in all different configurations. And then they're telling you that, Hey, something didn't work for me. I got double build or the passive recent link didn't work, or I couldn't, you know, when music, when the ad is finished playing on, on my app, the music doesn't resume. So how do we capture those signals into something that the company and different teams can align on? So that's where, you know, unit Q the, the vision here is to build a quality company, to help other companies build higher quality products. >>So really empowering companies to take a data driven approach to product quality. I was looking on your website and noticed that Pandora is one of your customers, but talk to me a little bit about a customer example that you think really articulates the value of what Q unit he was delivering. >>Right? So maybe we should just go back one little step and talk about what is quality. And I think quality is something that is, is a bit subjective. It's something that we live and breathe every day. It's something that can be formed in an instant first impressions. Last it's something that can be built over time that, Hey, I'm using this product and it's just not working for me. Maybe it's missing features. Maybe there are performance related bots. Maybe there is there's even fulfillment related issues. Like we work with Uber and hello, fresh and, and other types of more hybrid type companies in addition to the Pandoras and, and Pinterest and, and Spotify, and these more digital, only products, but the, the end users I'm producing this data, the reporting, what is working and not working out there in many different channels. So they will leave app produce. >>They will write into support. They might engage with a chat support bot. They will post stuff on Reddit on Twitter. They will comment on Facebook ads. So like this data is dispersed everywhere. The end user is not gonna fill out a perfect bug report in a form somewhere that gets filed into gr like they're, they're producing this content everywhere in different languages. So the first value of what we do is to just ingest all of that data. So all the entire surface area of use of feedback, we ingest into a machine and then we clean the data. We normalize it, and then we translate everything into English. And it was actually a surprise to us when we started this company, that there are quite a few companies out there that they're only looking at feedback in English. So what about my Spanish speaking users? What about my French speaking users? >>And when, when, when that is done, like when all of that data is, is need to organized, we extract signals from that around what is impacting the user experience right now. So we break these, all of this data down into something called quality monitors. So quality monitor is basically a topic which can be again, passive reset, link noting, or really anything that that's impacting the end user. And the important part here is that we need to have specific actionable data. For instance, if I tell you, Hey, Lisa music stops playing is a growing trend that our users are reporting. You will tell me, well, what can I do with that? Like what specifically is breaking? So we deploy up to 1500 unique quality monitors per customer. So we can then alert different teams inside of the organization of like, Hey, something broke and you should take a look at it. >>So it's really breaking down data silos within the company. It aligns cross-functional teams to agree on what should be fixed next. Cause there's typically a lot of confusion, you know, marketing, they might say, Hey, we want this fixed engineering. They're like, well, I can't reproduce, or that's not a high priority for us. The support teams might also have stuff that they want to get fixed. And what we've seen is that these teams, they struggle to communicate. So how do we align them around the single source of truth? And I think that's for unit two is early identification of stuff. That's not working in production and it's also aligning the teams so they can quickly triage and say, yes, we gotta fix this right before it snowballs into something. We say, you know, we wanna, we wanna cap catch issues before you go into crisis PR mode, right? So we want to get this, we wanna address it early in the cycle. >>Talk to me about when you're in customer conversations, Christian, the MarTech landscape is competitive. There's nearly 10,000 different solutions out there, and it's growing really quickly quality monitors that you just described is that one of the key things that, that you talk to customers about, that's a differentiator for unit Q. >>Yeah. So I mean, it, it, it comes down to, as you're building your product, right, you, you have, you have a few different options. One is to build new features and we need to build new features and innovate and, and, and that's all great. We also need to make sure that the foundation of the product is working and that we keep improving quality and what, what we see with, with basically every customer that we work with, that, that when quality goes up, it's supercharges the growth machine. So quality goes up, you're gonna see less support tickets. You're gonna see less one star reviews, less one star reviews is of course good for making the store front convert better. You know, I, I want install a 4.5 star app, not a 3.9 star app. We also see that sentiment. So for those who are interested in getting that NPS score up for the next time we measure it, we see that quality is of course a very important piece of that. >>And maybe even more importantly, so sort of inside of the product machine, the different conversion steps, let's say sign up to activate it to coming back in second day, 30 day, 90 day, and so forth. We see a dramatic impact on how quality sort of moves that up and down the retention function, if you will. So it, it really, if you think about a modern company, like the product is sort of the center of the existence of the company, and if the product performs really well, then you can spend more money in marketing because it converts really good. You can hire more engineers, you can hire, you can hire more support people and so forth. So it's, it's really cool to see that when quality improves its supercharges, everything else I think for marketing it's how do you know if you're spending into a broken product or not? >>And I, and I, I feel like marketing has, they have their insights, but it's, it's not deep enough where they can go to engineering and say, Hey, these 10 issues are impacting my MPS score and they're impacting my conversion and I would love for you to fix it. And when you can bring tangible impact, when you can bring real data to, to engineering and product, they move on it cause they also wanna help build the company. And, and so I think that's, that's how we stand out from the more traditional MarTech, because we need to fix the core of, of sort of this growth engine, which is the quality of the product >>Quality of the product. And obviously that's directly related to the customer experience. And we know these days, one of the things I think that's been in short supply the last couple of years is patience. We know when customers are unhappy with the product or service, and you talked about it a minute ago, they're gonna go right to, to Reddit or other sources to complain about that. So being able to, for uniq, to help companies to improve the customer experience, isn't I think table stakes for businesses it's mission critical these days. Yeah, >>It is mission critical. So if you look at the, let's say that we were gonna start a, a music app. Okay. So how do we, how do we compete as a music app? Well, if you, if you were to analyze all different music apps out there, they have more or less the same features app. Like they, the feature differentiation is minimal. And, and if you launch a new cool feature than your competitor will probably copy that pretty quickly as well. So competing with features is really hard. What about content? Well, I'm gonna get the same content on Spotify as apple SD. So competing with content is also really hard. What about price? So it turns out you'll pay 9 99 a month for music, but there's no, there's no 1 99. It's gonna be 9 99. So quality of the experience is one of the like last vectors or areas where you can actually compete. >>And we see consistently that if you' beating your competition on quality, you will do better. Like the best companies out there also have the highest quality experience. So it's, it's been, you know, for us at our last company, measuring quality was something that was very hard. How do we talk about it? And when we started this company, I went out and talked to a bunch of CEOs and product leaders and board members. And I said, how do you talk about quality in a board meeting? And they were, they said, well, we don't, we don't have any metrics. So actually the first thing we did was to define a metrics. We have, we have this thing called this unit Q score, which is on our website as well, where we can base it's like the credit score. So you can see your score between zero and a hundred. >>And if your score is 100, it means that we're finding no quality issues in the public domain. If your score is 90, it means that 10% of the data we look at refers to a quality issue. And the definition of a quality issue is quite simple. It is when the user experience doesn't match the user expectation. There is a gap in between, and we've actually indexed the 5,000 largest apps out there. So we're then looking at all the public review. So on our website, you can go in and, and look up the unit Q score for the 5,000 largest products. And we republish these every night. So it's an operational metric that changes all the time. >>Hugely impactful. Christian, thank you so much for joining me today, talking to the audience about unit Q, how you're turning qualitative feedback into pretty significant product improvements for your customers. We appreciate your insights. >>Thank you, Lisa, have a great day. >>You as well, per Christian Lin, I'm Lisa Martin. You're watching a cube conversation.

>>Hey everyone. Welcome to this cube conversation featuring Sendbird. I'm your host, Lisa Martin, John Kim joins me next, the CEO of Sendbird John, welcome to the program. Talk to the audience about Sendbird. What is it that you guys do? What gaps in the market did you see back in 2013? >>Yeah. Well thank you for so much and I'm excited to be here. So just to give you a quick introduction about Sendbird, we started a company back in 2013, and then we first started out as a consumer based product building social network for moms, but around 2015, when the world was really moving towards messaging, we kind of looked at as an opportunity to build a message feature for our own application. That's when we kind of realized a problem that we, there weren't really modern SDK or API products that can enable modern messaging experience for other applications. So we decided to kind of build that and then actually launched on the side, which actually became the main business. So we applied a wide Combinator with that idea and launched to the world in 2016 and then kind of fast forward, you know, good six years. We're now powering over a quarter billion users on a monthly basis, sending billions of billions of messages, cross different vertical site, online community site credit like door C. So it's kinda where we're today. >>And you're now valued at 1 billion. So a lot of evolution, a lot of momentum since 2013, especially since 2016, but also during the last couple of years. Talk to me about some of the philosophies and the approaches that Sendbird has applied to be driving such momentum during such volatile times. >>Yeah, I think over the years, what we're all came to realize is that more and more and more businesses are becoming mobile first. So by focusing on the mobile basic experiences, conversations really became one of the most efficient and effective ways to build relationship between the users as well as the relationship with the brands. So by incorporating experiences like messaging, people were able to increase the engagement and the retention and ultimately conversion within the applications. And that's kind of where we come in because more and more it's, it's becoming harder and harder for developers and the business operators to build modern messaging experience. So we really want to make sure that all of the developers and all of the businesses can harness the power of in a messaging as easily as possible, getting all the, you know, feature richness plus the scalability that you need. So we really try to build the best in class product so that you can have those know messaging within your application. >>Let's talk about that. So B building relationships in a digital world today is table stakes for any business consumers, patience was quite thin. The last couple of years, it probably still is to some extent, but building relationships in today's omnichannel world, whereas consumers, we expect we can go to many different applications, apps, and complain, or raise issues with technologies or products or services. How is that table stakes for an organization to be able to have that in-app experience to retain the customers, the data, the insights. >>Yeah. Today, if you think about how a businesses are engaging with customers, there are a lot of different channels, right? There's SMS, there's, you know, phone calls, direct mailing emails, and also a messaging. If you think about as a user, what is the best experience you want to have with the, with the brands it's usually through the mobile applications. That's why the entire mobile economy has really grew and exploded over the years. One thing that if you think about again as a user, what are the experience that you don't like to have is if you think about SMSs SM now plagued with like phishing and scams issues, FTC reported that they're more than hundreds of millions of dollars that are costing us consumers last year, and that's more than 50% growth from the previous year. So more and more of these kind of other external channels are becoming a channel for again, for like fishing and scams and really disrupting the user experience. >>But if you think about the, a messaging becoming your default mode of engaging with the brands and other users is secure more reliable, and also as businesses you get, you, you get to control the user experience, plus actually owning the data. So you can actually improve your products and services on top of that. So that's some of the approaches that we've seen over the years. More and more businesses are using in a messaging as the default mode of communication, and then using other channels as a, kind of like a last mile delivery in case, you know, users, miss certain kind of conversation, they may rely on those other channels as all that option. Just to touch a little bit on the, just to touch a little bit on the messaging side of things. So if you think about how the world is using messaging today, you might, you know, think of missing apps like yo meta facing messenger, or, you know, WhatsApp and all of this, this other kind of consumer applications, consumer mobile messaging is kind of really dominating the world. But if you think about individual businesses, you really don't really want to hand over those experiences and the user data to other kind of social media networks. So what you want to do is actually have that similar level, if not better experience within your application, but also be able to, again, own those data, control this, those data and make sure that your users and your customers are having a very clean and secure experience on your application. >>Absolutely. Without secure clean experience is critical for brands. Talk to me about how your customer conversations have evolved over the last few years as brand loyalty, customer satisfaction, scores, churn. All of these things are very impactful to organizations. Has the conversation risen up the C-suite? Is it, is it that impactful these days? >>Yeah. So B really based on the brands that you are operating again, like the customer engagement and customer retention, and sometimes the conversations turning into business outcomes through convergence, all of these things are really impacted a lot by the conversations or in a messaging. So what we've seen over the years is anywhere from the user acquisition perspective, from the marketing also within the user engagement retention, that's happening in your application, whether it be user to user or your sales team, having conversations with the customers, ultimately to like customer support measuring CS, and how do you keep the customers? Sure that customers never hit a dead end. All of this entire customer journey now can be mapped through messaging. So because that's becoming more and more important and critical for your business, now's the, if you think about our buyers today, we are talking to CEOs and CTOs, as well as chief digital officers in some of these enterprises companies. >>That makes sense. I mean, some of the, the benefits that you've mentioned, increasing retention, driving I'm direct sales cross sale up sale, brand loyalty that impacts every aspect of an organization, customer success, et cetera. Let's talk now about some customer examples. I know you mentioned Reddit. I know hinge is another great customer example. Give me a couple examples that really showcase the value that Sunbird delivers. >>Yeah. So Reddit has been one of our earliest customers, even when you're like just a C stage company. If you think about Reddit, red has successfully trans trans transformed from the web based company to a mobile first company. And by incorporating a messaging to a modern experiences, just like, again, once you have on WhatsApp, they're able to increase the user engagement and ultimately the retention on the application. So more and more users are coming back to the application in any given month. So that's one, one example. And again, keeping the community safe and secure is very, very important for a community like Reddit. So offering powerful and moderation capabilities for the community MOS. Those are also very important factors why Reddi decided to work with us. Some of the other examples, like, you know, Crafton pub, one of the world's most successful and largest games today now, they able, they were able to increase their user engagement and ultimately the overall, you know, session time within the game by incorporating messaging that powers the users online communities through lobby chat, as well as, you know, client chat. >>So how to keep the users more engaged in return to game and stay there for a longer period of time, ultimately increasing the lifetime value of the gamers. And then a few other like business industry use cases like keep trucking recently rebranded as motive, drastically improved the collaboration between this, you know, operations control and, and it's truck drivers. So those kind of communication capabilities obviously increase the safety of the drivers as well as the trust and then openness and overall collaboration within the businesses. So those are some of the examples. And I think we mentioned like hinge before, how do you kind of bring all of those conversations to stay within the applications? So the users don't have to reveal their, you know, personal information so that the conversation become, again, stays on the application, keep the user happy, more secure and safe for the, all the users. >>That security is something that keeps jumping out to me. We have seen the threat landscape change dramatically in the last couple of years. It is so amorphous, but you mentioned the SMS security issues that it has. And I, I think a staff that you guys provided to me was that the FTC reported that tech scams cost us consumers 131 million last year in 2021, which as you mentioned, is a huge increase from 2020. Talk a little bit more about the importance of being able to abstract some of that personal information as consumers. We give it out so freely and it's, it's a it's risk. >>Absolutely. So again, some of the most common fishing scams that we all as the consumers receive these days are, you know, pretending to be another businesses telling you, Hey, click here to, you know, get a refund on, on, on a credit card charge or, you know, there's a fraudulent cases. Like there's something that makes you either call a number or, you know, go to a certain link and you kind of have to trust and try to figure out is this a messaging that's really that brand that you are engaging with? Or is this something someone else that's pretending to that, to be that brand? So is the burden is on the end customers, unfortunately, all the fishings and everything's like a law, large, large number. So the more people you send out those messages, ultimately someone will get tricked into those messages and ultimately costing a lot of money for the end consumers. >>Now, the benefit of having enough conversations is that your users are secure when the users get a push notification or in a message, you know, where that's exactly happening, cuz you have full context of the business and the application you're in. And then whenever someone, somebody sends you a message, you know, the sender and the receiver's already authenticated. So those users are secure from the get go. And because of the contextual rich experience you have within the messaging, plus all those extra security layers they're bake to the user experience, the, the end benefit for the customers are incredible. Cuz again, you can trust the conversation that you're having with the brand and then the messages tend to be a lot more richer and better user experience, also better latency and just overall more frictionless experience for the end customers. So that gives a lot more safety and more benefit for the end customer as well as the business brands. >>Absolutely two things that you just said that really jumped out at me. Trust and authenticity. We think of the five generations that are in the workforce today, engaging with companies via apps that, that trust and authenticity and that security is. It just, it gets more important every day. Talk to me about when you're in customer conversations or you're talking with analysts, what are some of the things that you describe as the key differentiators that makes Sendbird in-app messaging really stand out about the competition? >>Yeah. One of the things that we really focus on was can we actually serve the world? So scalability is one of the key important aspects, how we were able to win customers like Reddit, you know, DoorDash and even like incredible customers like Paytm, one of the largest FinTech application in India. So being able to provide us scalability so that your customers, our customers, and the developers can go to sleep at night without having to worry about will this work now, but also other on top of top of those things, the feature richness cuz ultimately what our customer want is how can they engage with their customers in a modern and ale way. So by offering the features that are up in the latest, in the greatest that you'd expect out of other consumer application, again like WhatsApp, Facebook messenger, or even things like slack, we offer a lot of those features from get go. >>So by having those feature richness out of the box, you can implement a modern missing experience from day one. So you can go to market much faster, but also give more trust for the users cuz ultimately end customers are already used to using the best missing experiences out there. So as soon as they kind of feel the experience are a little bit, you know, outdated, they'll stop trusting the brand. So how do you kind of give them moderate and trusting and, and secure experience for the user is very, very critical for the businesses. So you can offer those again from out of the box, >>Out of the box, absolutely table stakes for businesses in every industry. John, thank you so much for coming on the queue today. Talking to me about Sendbird in-app messaging, the values, the benefits, the what's in it for customers and businesses. We appreciate your insights. >>Thanks. So >>John Kim I'm Lisa Martin, you're watching this conversation.

(upbeat music) >> Welcome, everyone, to theCUBE's presentation of the AWS Startup Showcase. And this episode two of season two is called "Data as Code," the ongoing series covering exciting new startups in the AWS ecosystem. I'm John Furrier, your host of theCUBE. Today, we're excited to be joined by Jon Dahl, who is the co-founder and CEO of MUX, a hot new startup building cloud video for developers, video with data. John, great to see you. We did an interview on theCube Conversation. Went into big detail of the awesomeness of your company and the trend that you're on. Welcome back. >> Thank you, glad to be here. >> So, video is everywhere, and video for pivot to video, you hear all these kind of terms in the industry, but now more than ever, video is everywhere and people are building with it, and it's becoming part of the developer experience in applications. So people have to stand up video into their code fast, and data is code, video is data. So you guys are specializing this. Take us through that dynamic. >> Yeah, so video clearly is a growing part of how people are building applications. We see a lot of trends of categories that did not involve video in the past making a major move towards video. I think what Peloton did five years ago to the world of fitness, that was not really a big category. Now video fitness is a huge thing. Video in education, video in business settings, video in a lot of places. I think Marc Andreessen famously said, "Software is eating the world" as a pretty, pretty good indicator of what the internet is actually doing to the economy. I think there's a lot of ways in which video right now is eating software. So categories that we're not video first are becoming video first. And that's what we help with. >> It's not obvious to like most software developers when they think about video, video industries, it's industry shows around video, NAB, others. People know, the video folks know what's going on in video, but when you start to bring it mainstream, it becomes an expectation in the apps. And it's not that easy, it's almost a provision video is hard for a developer 'cause you got to know the full, I guess, stack of video. That's like low level and then kind of just basic high level, just play something. So, in between, this is a media stack kind of dynamic. Can you talk about how hard it is to build video for developers? How is it going to become easier? >> Yeah, I mean, I've lived this story for too long, maybe 13 years now, when I first build my first video stack. And, you know, I'll sometimes say, I think it's kind of a miracle every time a video plays on the internet because the internet is not a medium designed for video. It's been hijacked by video, video is 70% of internet traffic today in an unreliable, sort of untrusted network space, which is totally different than how television used to work or cable or things like that. So yeah, so video is hard because there's so many problems from top to bottom that need to be solved to make video work. So you have to worry about video compression encoding, which is a complicated topic in itself. You have to worry about delivering video around the world at scale, delivering it at low cost, at low latency, with good performance, you have to worry about devices and how every device, Android, iOS, web, TVs, every device handles video differently and so there's a lot of work there. And at the end of the day, these are kind of unofficial standards that everyone's using. So one of the miracles is like, if you want to watch a video, somehow you have to get like Apple and Google to agree on things, which is not always easy. And so there's just so many layers of complexity that are behind it. I think one way to think about it is, if you want to put an image online, you just put an image online. And if you want to put video online, you build complex software, and that's the exact problem that MUX was started to help solve. >> It's interesting you guys have almost creating a whole new category around video infrastructure. And as you look at, you mentioned stack, video stack. I'm looking at a market where the notion of a media stack is developing, and you're seeing these verticals having similar dynamics with cloud. And if you go back to the early days of cloud computing, what was the developer experience or entrepreneurial experience, you had to actually do a lot of stuff before you even do anything, provision a server. And this has all kind of been covered in great detail in the glory of Agile and whatnot. It was expensive, and you had that actually engineer before you could even stand up any code. Now you got video that same thing's happening. So the developers have two choices, go do a bunch of stuff complex, building their own infrastructure, which is like building a data center, or lean in on MUX and say, "Hey, thank you for doing all that years of experience building out the stacks to take that hard part away," but using APIs that they have. This is a developer focused problem that you guys are solving. >> Yeah, that's right. my last company was a company called Zencoder, that was an API to video encoding. So it was kind of an API to a small part of what MUX does today, just one of those problems. And I think the thing that we got right at Zencoder, that we're doing again here at MUX, was building four developers first. So our number one persona is a software developer. Not necessarily a video expert, just we think any developer should be able to build with video. It shouldn't be like, yeah, got to go be a specialist to use this technology, because it should become just of the internet. Video should just be something that any developer can work with. So yeah, so we build for developers first, which means we spend a lot of time thinking about API design, we spend a lot of time thinking about documentation, transparent pricing, the right features, great support and all those kind of things that tend to be characteristics of good developer companies. >> Tell me about the pipe lining of the products. I'm a developer, I work for a company, my boss is putting pressure on me. We need video, we have all this library, it's all stacking up. We hired some people, they left. Where's the video, we've stored it somewhere. I mean, it's a nightmare, right? So I'm like, okay, I'm cloud native, I got an API. I need to get my product to market fast, 'cause that is what Agile developers want. So how do you describe that acceleration for time to market? You mentioned you guys are API first, video first. How do these customers get their product into the market as fast as possible? >> Yeah, well, I mean the first thing we do is we put what we think is probably on average, three to four months of hard engineering work behind a single API call. So if you want to build a video platform, we tell our customers like, "Hey, you can do that." You probably need a team, you probably need video experts on your team so hire them or train them. And then it takes several months just to kind of to get video flowing. One API call at MUX gives you on-demand video or live video that works at scale, works around the world with good performance, good reliability, a rich feature set. So maybe just a couple specific examples, we worked with Robin Hood a few years ago to bring video into their newsfeed, which was hugely successful for them. And they went from talking to us for the first time to a big launch in, I think it was three months, but the actual code time there was like really short. I want to say they had like a proof of concept up and running in a couple days, and then the full launch in three months. Another customer of ours, Bandcamp, I think switched from a legacy provider to MUX in two weeks in band. So one of the big advantages of going a little bit higher in the abstraction layer than just building it yourself is that time to market. >> Talk about this notion of video pipeline 'cause I know I've heard people I talk about, "Hey, I just want to get my product out there. I don't want to get stuck in the weeds on video pipeline." What does that mean for folks that aren't understanding the nuances of video? >> Yeah, I mean, it's all the steps that it takes to publish video. So from ingesting the video, if it's live video from making sure that you have secure, reliable ingest of that live feed potentially around the world to the transcoding, which is we talked a little bit about, but it is a, you know, on its own is a massively complicated problem. And doing that, well, doing that well is hard. Part of the reason it's hard is you really have to know where you're publishing too. And you might want to transcode video differently for different devices, for different types of content. You know, the pipeline typically would also include all of the workflow items you want to do with the video. You want to thumbnail a video, you want clip, create clips of the video, maybe you want to restream the video to Facebook or Twitter or a social platform. You want to archive the video, you want it to be available for downloads after an event. If it's just a, if it's a VOD upload, if it's not live in the first place. You have all those things and you might want to do simulated live with the video. You might want to actually record something and then play it back as a live stream. So, the pipeline Ty typically refers to everything from the ingest of the video to the time that the bits are delivered to a device. >> You know, I hear a lot of people talking about video these days, whether it's events, training, just want peer to peer experience, video is powerful, but customers want to own their own platform, right? They want to have the infrastructure as a service. They kind of want platform as a service, this is cloud talk now, but they want to have their own capability to build it out. This allows them to get what they want. And so you see this, like, is it SaaS? Is it platform? People want customization? So kind of the general purpose video solution does it really exist or doesn't? I mean, 'cause this is the question. Can I just buy software and work or is it going to be customized always? How do you see that? Because this becomes a huge discussion point. Is it a SaaS product or someone's going to make a SaaS product? >> Yeah, so I think one of the most important elements of designing any software, but especially when you get into infrastructure is choosing an abstraction level. So if you think of computing, you can go all the way down to building a data center, you can go all the way down to getting a colo and racking a server like maybe some of us used to do, who are older than others. And that's one way to run a server. On the other extreme, you have just think of the early days of cloud competing, you had app engine, which was a really fantastic, really incredible product. It was one push deploy of, I think Python code, if I remember correctly, and everything just worked. But right in the middle of those, you had EC2, which was, EC2 is basically an API to a server. And it turns out that that abstraction level, not Colo, not the full app engine kind of platform, but the API to virtual server was the right abstraction level for maybe the last 15 years. Maybe now some of the higher level application platforms are doing really well, maybe the needs will shift. But I think that's a little bit of how we think about video. What developers want is an API to video. They don't want an API to the building blocks of video, an API to transcoding, to video storage, to edge caching. They want an API to video. On the other extreme, they don't want a big application that's a drop in white label video in a box like a Shopify kind of thing. Shopify is great, but developers don't want to build on top of Shopify. In the payments world developers want Stripe. And that abstraction level of the API to the actual thing you're getting tends to be the abstraction level that developers want to build on. And the reason for that is, it's the most productive layer to build on. You get maximum flexibility and also maximum velocity when you have that API directly to a function like video. So, we like to tell our customers like you, you own your video when you build on top of MUX, you have full control over everything, how it's stored, when it's stored, where it goes, how it's published, we handle all of the hard technology and we give our customers all of the flexibility in terms of designing their products. >> I want to get back some use case, but you brought that up I might as well just jump to my next point. I'd like you to come back and circle back on some references 'cause I know you have some. You said building on infrastructure that you own, this is a fundamental cloud concept. You mentioned API to a server for the nerds out there that know that that's cool, but the people who aren't super nerdy, that means you're basically got an interface into a server behind the scenes. You're doing the same for video. So, that is a big thing around building services. So what wide range of services can we expect beyond MUX? If I'm going to have an API to video, what could I do possibly? >> What sort of experience could you build? >> Yes, I got a team of developers saying I'm all in API to video, I don't want to do all that transit got straight there, I want to build experiences, video experiences on my app. >> Yeah, I mean, I think, one way to think about it is that, what's the range of key use cases that people do with video? We tend to think about six at MUX, one is kind of the places where the content is, the prop. So one of the things that use video is you can create great video. Think of online courses or fitness or entertainment or news or things like that. That's kind of the first thing everyone thinks of, when you think video, you think Netflix, and that's great. But we see a lot of really interesting uses of video in the world of social media. So customers of ours like Visco, which is an incredible photo sharing application, really for photographers who really care about the craft. And they were able to bring video in and bring that same kind of Visco experience to video using MUX. We think about B2B tools, videos. When you think about it, all video is, is a high bandwidth way of communicating. And so customers are as like HubSpot use video for the marketing platform, for business collaboration, you'll see a lot of growth of video in terms of helping businesses engage their customers or engage with their employees. We see live events obviously have been a massive category over the last few years. You know, we were all forced into a world where we had to do live events two years ago, but I think now we're reemerging into a world where the online part of a conference will be just as important as the in-person component of a conference. So that's another big use case we see. >> Well, full disclosure, if you're watching this live right now, it's being powered by MUX. So shout out, we use MUX on theCUBE platform that you're experiencing in this. Actually in real time, 'cause this is one application, there's many more. So video as code, is data as code is the theme, that's going to bring up the data ops. Video also is code because (laughs) it's just like you said, it's just communicating, but it gets converted to data. So data ops, video ops could be its own new category. What's your reaction to that? >> Yeah, I mean, I think, I have a couple thoughts on that. The first thought is, video is a way that, because the way that companies interact with customers or users, it's really important to have good monitoring and analytics of your video. And so the first product we ever built was actually a product called MUX video, sorry, MUX data, which is the best way to monitor a video platform at scale. So we work with a lot of the big broadcasters, we work with like CBS and Fox Sports and Discovery. We work with big tech companies like Reddit and Vimeo to help them monitor their video. And you just get a huge amount of insight when you look at robust analytics about video delivery that you can use to optimize performance, to make sure that streaming works well globally, especially in hard to reach places or on every device. That's we actually build a MUX data platform first because when we started MUX, we spent time with some of our friends at companies like YouTube and Netflix, and got to know how they use data to power their video platforms. And they do really sophisticated things with data to ensure that their streams well, and we wanted to build the product that would help everyone else do that. So, that's one use. I think the other obvious use is just really understanding what people are doing with their video, who's watching what, what's engaging, those kind of things. >> Yeah, data is definitely there. You guys mentioned some great brands that are working with you guys, and they're doing it because of the developer experience. And I'd like you to explain, if you don't mind, in your words, why is the MUX developer experience so good? What are some of the results you're seeing from your customers? What are they saying to you? Obviously when you win, you get good feedback. What are some of the things that they're saying and what specific develop experiences do they like the best? >> Yeah, I mean, I think that the most gratifying thing about being a startup founder is when your customers like what you're doing. And so we get a lot of this, but it's always, we always pay attention to what customers say. But yeah, people, the number one thing developers say when they think about MUX is that the developer experience is great. I think when they say that, what they mean is two things, first is it's easy to work with, which helps them move faster, software velocity is so important. Every company in the world is investing and wants to move quickly and to build quickly. And so if you can help a team speed up, that's massively valuable. The second thing I think when people like our developer experience is, you know, in a lot of ways that think that we get out of the way and we let them do what they want to do. So well, designed APIs are a key part of that, coming back to abstraction, making sure that you're not forcing customers into decisions that they actually want to make themselves. Like, if our video player only had one design, that that would not be, that would not work for most developers, 'cause developers want to bring their own design and style and workflow and feel to their video. And so, yeah, so I think the way we do that is just think comprehensively about how APIs are designed, think about the workflows that users are trying to accomplish with video, and make sure that we have the right APIs, make sure they're the right information, we have the right webhooks, we have the right SDKs, all of those things in place so that they can build what they want. >> We were just having a conversation on theCUBE, Dave Vellante and I, and our team, and I'd love to get you a reaction to this. And it's more and more, a riff real quick. We're seeing a trend where video as code, data as code, media stack, where you're starting to see the emergence of the media developer, where the application of media looks a lot like kind of software developer, where the app, media as an app. It could be a chat, it could be a peer to peer video, it could be part of an event platform, but with all the recent advances, in UX designers, coders, the front end looks like an emergence of these creators that are essentially media developers for all intent and purpose, they're coding media. What's your reaction to that? How do you see that evolving? >> I think the. >> Or do you agree with it? >> It's okay. >> Yeah, yeah. >> Well, I think a couple things. I think one thing, I think this goes along through saying, but maybe it's disagreement, is that we don't think you should have to be an expert at video or at media to create and produce or create and publish good video, good audio, good images, those kind of things. And so, you know, I think if you look at software overall, I think of 10 years ago, the kind of DevOps movement, where there was kind of a movement away from specialization in software where the same software developer could build and deploy the same software developer maybe could do front end and back end. And we want to bring that to video as well. So you don't have to be a specialist to do it. On the other hand, I do think that investments and tooling, all the way from video creation, which is not our world, but there's a lot of amazing companies out there that are making it easier to produce video, to shoot video, to edit, a lot of interesting innovations there all the way to what we do, which is helping people stream and publish video and video experiences. You know, I think another way about it is, that tool set and companies doing that let anyone be a media developer, which I think is important. >> It's like DevOps turning into low-code, no-code, eventually it's just composability almost like just, you know, "Hey Siri, give me some video." That kind of thing. Final question for you why I got you here, at the end of the day, the decision between a lot of people's build versus buy, "I got to get a developer. Why not just roll my own?" You mentioned data center, "I want to build a data center." So why MUX versus do it yourself? >> Yeah, I mean, part of the reason we started this company is we have a pretty, pretty strong opinion on this. When you think about it, when we started MUX five years ago, six years ago, if you were a developer and you wanted to accept credit cards, if you wanted to bring payment processing into your application, you didn't go build a payment gateway. You just probably used Stripe. And if you wanted to send text messages, you didn't build your own SMS gateway, you probably used Twilio. But if you were a developer and you wanted to stream video, you built your own video gateway, you built your own video application, which was really complex. Like we talked about, you know, probably three, four months of work to get something basic up and running, probably not live video that's probably only on demand video at that point. And you get no benefit by doing it yourself. You're no better than anyone else because you rolled your own video stack. What you get is risk that you might not do a good job, maybe you do worse than your competitors, and you also get distraction where you've just taken, you take 10 engineers and 10 sprints and you apply it to a problem that doesn't actually really give you differentiated value to your users. So we started MUX so that people would not have to do that. It's fine if you want to build your own video platform, once you get to a certain scale, if you can afford a dozen engineers for a VOD platform and you have some really massively differentiated use case, you know, maybe, live is, I don't know, I don't have the rule of thumb, live videos maybe five times harder than on demand video to work with. But you know, in general, like there's such a shortage of software engineers today and software engineers have, frankly, are in such high demand. Like you see what happens in the marketplace and the hiring markets, how competitive it is. You need to use your software team where they're maximally effective, and where they're maximally effective is building differentiation into your products for your customers. And video is just not that, like very few companies actually differentiate on their video technology. So we want to be that team for everyone else. We're 200 people building the absolute best video infrastructure as APIs for developers and making that available to everyone else. >> John, great to have you on with the showcase, love the company, love what you guys do. Video as code, data as code, great stuff. Final plug for the company, for the developers out there and prospects watching for MUX, why should they go to MUX? What are you guys up to? What's the big benefit? >> I mean, first, just check us out. Try try our APIs, read our docs, talk to our support team. We put a lot of work into making our platform the best, you know, as you dig deeper, I think you'd be looking at the performance around, the global performance of what we do, looking at our analytics stack and the insight you get into video streaming. We have an emerging open source video player that's really exciting, and I think is going to be the direction that open source players go for the next decade. And then, you know, we're a quickly growing team. We're 60 people at the beginning of last year. You know, we're one 50 at the beginning of this year, and we're going to a add, we're going to grow really quickly again this year. And this whole team is dedicated to building the best video structure for developers. >> Great job, Jon. Thank you so much for spending the time sharing the story of MUX here on the show, Amazon Startup Showcase season two, episode two, thanks so much. >> Thank you, John. >> Okay, I'm John Furrier, your host of theCUBE. This is season two, episode two, the ongoing series cover the most exciting startups from the AWS Cloud Ecosystem. Talking data analytics here, video cloud, video as a service, video infrastructure, video APIs, hottest thing going on right now, and you're watching it live here on theCUBE. Thanks for watching. (upbeat music)