>> from our studios in the heart of Silicon Valley, Palo Alto, California It is a cute conversation >> run. Welcome to this cube conversation here in Palo Alto, California. I have remote. Sarah Varney is the chief marketing officer Tulio Company. We've covered for many, many years one of the most successful A p I now public company. Um, Sarah, welcome to the Cube competition. Good to see you remotely. You're in San Francisco? Were in Palo Alto. Um, thanks for coming on. >> Yeah, thanks so much for having me. >> So you guys have been really a powerhouse company? Twilio. We've been following the rise and success. It just seems just success that the success of success go public stock keeps growing. Big acquisition would send grid for $2,000,000,000 in October. We covered that, but really kind of reading the tea leaves and connecting the dots. It's really the continued evolution of Cloud sas, where AP eyes are becoming Maur and Maur the lingua franca for the next generation way. That's coming, but is going into a whole nother direction. You guys are a big part of that. You're the chief marketing officer. It's >> a hard >> story to tell because it's it's kind of under the hood nerdy, but it's also really big business benefits. So as the c m o. How do you get your arms around that you've been in the business for a while? Take him in to explain the strategy around how you're handling. That's Willie. Oh, Marketing. >> Sure, Yeah. I mean, I do. I agree that, uh, you know, Tulio is >> very much an ingredient brand, but at the same time, everyone is interacting with with in some cheaper form, probably every day, whether or not they realize it or not. If you're getting an appointment reminder from your >> dentist's confirming an appointment, that's probably Tulio behind the scenes, >> if you are communicating with your uber driver to say that you are headed outside that is normally powered by Coolio technology. So even though it might be, ah, technology that exists lower in the stack and something you might not physically see, it is very much something that people everywhere getting every day and you know our goal really is to Leo is to make sure that we're helping companies across the globe from all different types of industries, of all shapes and sizes. to bridge the communication gap with their customers. You know, every day there's a new channel to keep up to speed with. There's a new way that people are customers that are demanding Thio be communicated with. And we want companies to be out in front of that s O that you know, they can connect with their customers on any channel, if that's what's up. If that's SMS. If that's voice, if that's even fax, we want to make that ah possibility. >> I love the Positioning Cloud Communications Company. That's kind of what you guys Air Corps, because you're bringing it all together. And I think you know, the mobile Revolution, starting with the iPhone and 2007. You look at that as a seminal moment and you say OK, mobile device. It's a phone, It's a computer. It's got applications on it. This is a device that's unique to the rest of the infrastructure, but developers and your programming on it, and those things all integrate together. That's where a lot of people kind of saw that for the first time. Then you add cloud to it. Amazon, Microsoft and Google, the top three Amazon dominating really kind of brings a P. I focus even more to make these service's. These Web service is go to a whole nother level on dhe. That's the big wave that we're seeing. I'd >> love to get >> your thoughts and you worked at salesforce dot com, which really pioneered sass. And they were the first real cloud company before you started to see Amazon really cloud infrastructure to service. So Platforms asserts and suffers of service evolve. You were there early. You had a lot of experience working with AP Exchange APP stores early on its sales force. How does that compare to now? What is the trajectory and how does it all connect? >> Yeah, I mean, I think that when I, you know my joke is always that when I started on the APP exchange, its sales force, the Apple App store didn't even exist. So the explosion of mobile devices was just we weren't even. We weren't even there quite yet, and I was working with Iess V's Thio to help them. I think about how they could launch big businesses in the cloud on, I think at that point people were were rotating hard away from the world of on premise, which required a ton of investment of a hardware perspective and service's perspective, and in the process of that, rotated very almost overcorrected towards package solutions. And I think over the last few years what we've seen and something that Tulio is definitely behind and you could see in the vision of our product roadmap he's coming back to the middle, where you have the benefits of the cloud, the speed, the ability to stand something out very quickly. But you also have unlimited customization ability, and you can really put that Theobald ity to build palette for applications that bring the best of different solutions in different applications through a p. I's in the hands of of your developers. Sorry. Go ahead. >> I think that's a great point. I want to just double down on that for a second and ask you how you guys are seeing the developer traction on this because one of the core things that were been reporting over the past couple years this year in particular is the rise of things like Kubernetes Cloud native, where developers now have a seamless way to program the infrastructure, the hard stuff. So you're seeing a faster development cycle for those application developers. Is that where the customization piece comes in? Is that where you guys see that connection point? And what does that mean for customers? >> Yeah, I mean, I think that's part of it. But at a higher level, we really want to empower developers. You create a custom connected journey across >> all different parts of how our customers interacting with the brand. You know, >> if you think about I. I had a recent incident with an airline that will remain nameless, but I I left my laptop on a plane in to get that laptop back. Took multiple calls. Thio the customer service desk. I was bounced around to a bunch of different people. The tracking of that computer was a near impossible. At one point, it traveled from New Jersey, Thio Ireland. You know, there was just so many different points of that journey where there was disconnection and I began to lose trust in this the ability of this customer service department, uh, you know, this This company had an A P I based approach. They could bring all of the data from these different systems from there. >> Your pee from their serum, you know, from their shipping vendor all in one place. And I wouldn't have had that that experience with that particular airline. >> So if you see a P Eyes is a data connector model, really, connecting data sets together fast and easy. >> Ideo. I think it's a way I think developers love working in AP eyes because they can bring all the they can pick the best of breed solutions and bring over that data into one customer united customer experience so that your customer doesn't have >> to do that heavy lifting. It's all there for them. >> You know, one of the things you see from companies like Salesforce pioneering the early days of Assassin Cloud. I mean, even Andy jassy it Amazon many times, and he always uses the expression that they use the Amazon cold you got. You have to be misunderstood for a long time. If you want to be a leader in an emerging Newmarket. You guys that twilio kind of have done that and continue to surpass expectations because you've been kind of skating to where the puck is now, which is the cloud Native Wave. Third party applications, Coyote security all kind of come together for developers. So as a company that's been different and been disruptive as the c m o. >> How do you >> take that? Uh, that that vision in Montreat the next level as you market the solution because you are kind of different. You are not new per se, but you're a new way to create value for customers. How do you go out and tell that story with some of the marketing things that you do? Um, take that twilio to the next level. >> I mean, I personally, in >> my experience, I think, uh, the easiest marking jobs are the ones where you have amazing customer stories and there is no shortage of amazing innovation and our customer base on. And, you know, I think if you think about the companies that are making the news, if that's lift, if that's, you know, cos like Airbnb, they're not. If you think about their business, they're not inventing something. Brando. The Hoover didn't invent the taxi, uh, air being beaten and then a hotel room. But they invented a new way to consume their product to communicate around their product. And, you know, I think it's very easy to show the power of Tulio and how we've evolved through some of these these customer stories. And it's not just the kind of Silicon Valley fast growing, you know, start ups that we're all familiar with here, just just living and being located in the region. But, you know, we're starting to see this more and more in the enterprise as well. Ah, and people really hardest in communication to make sure that that they themselves are not disrupted. >> Yeah, of course. We love that. The enterprise high we've been doing for 10 years now. Everyone talks enterprise because the confidence of consumer ization of I t. Is happening. It's the lines are blurring. Share some customers successors because I think this is a great, great example of just great marketing that the customers do the talking for you. You always got to do this thing. You know the standard operational things and have some a text back and all that good stuff. But at the end of the day, when you have your customer sharing their success, that's really the ultimate testimonial. So share some cool examples of notable customers, if you can. >> Yeah, well, look I mean, we have a wide range, I'll tell you. Three Medtronic, one of the largest medical device companies in the world. They provide a solution for Type one diabetes. They provide a pump that is constantly monitoring the glucose levels in someone's blood. What they've done with Julio's. Now they're layering on messaging capability. So if someone's glucose levels all to a level that's unsafe, they could be messaged. And you know, this is not just for the patient. But if you think of a young child who suffers from Type one diabetes, this could be a very stressful situation for their parents and their caregiving team. And now that team can constantly be in the loop, and they don't have to worry if they are at work and wondering, you know how they're chai that was doing at school. Or, you know, if they're on the soccer field and concerned about you know how, uh, their condition could be affected by them. Participating in that sport s so completely different from your more, um uh, straight down the middle startup that we see here in the Valley. >> So basically, messaging is to keep value. It's not so much a tech thing. It's more of a the outcome. It's a critical service piece toe. Have those kind of real time communications? >> Yes, absolutely. Because, I mean, if you think about >> it monitoring your your, uh, glucose levels, that's not a new phenomenon. People have been doing that for years, but layering on communications on top of this has brought a real time element Thio monitoring this, uh, this condition and has liberated people with this condition so that, you know, they can get back to the things that they've always going to do without having to worry about. You know, the state of their health. It's gone. >> It's like infrastructure is code for devil up you guys air for communications. You make it easy to do that for things like that. Talk about the impact of scale over the years because now you know, we're seeing the data tsunami happen Every day I ot devices air coming on. Everything's got. Ah, a sensor on it. You got doorbells. You got everything out there now has got an I P address and connected in that could potentially be a messaging unit of of data. This is just getting massive. How you guys see scale? And how do you guys getting around the next wave on that piece? >> Yeah. I mean, I think one of the >> huge benefits in working with polio is our super network. So we're constantly maintaining relationships with all the key carriers across the globe to make sure that we can get deliver our to our customers the best routes. And so that means also that they can stand up business virtually anywhere across the globe, a cz, their entry in new markets and coyote. This is especially true for anyone who is in the eye ot space. If you think about the dock Ellis category, companies like lime, uh, who are, you know, delivering rental bike service is where and you know, a market where market share just grabbing as much market share is possible. It seems to be the name of the game. They're able to partner with Julio in bed sim cards and all of their bicycles, and now be able to you track all of those all of those bicycles across the globe as well as scooters. Ah, and then take that information, uh, figure out how customers are engaging with their product and ultimately build a better solution. Long term, >> real time messaging will never go away as values. I see just like data. So it's gonna get faster and larger amounts of messaging making sense of it. Do. The heavy lifting is great story. You guys done a great job. Thanks for coming on and sharing your perspective. Get the plug in for twilio real quick. What's new with the company employees out? See the public companies? You really can't talk about futures, but what's on your plate? What's on the horizon for Tulio? What's the update? >> Yeah, I mean, the company is >> growing extremely quickly. We're really excited about the context, but center market especially. We launched our flex contact center Solution, uh, was made generally available just this past October. On a CZ you've mentioned we're super excited to welcome sing grid into the family of products you know, really, round out our full set communication in the eyes of people communicate with their customers in any way possible. And I would be, uh, it would be a crime for me, not to mention our user conference coming up this August August 6th and seventh at Mosconi West and that's called Signal s O. I highly encourage you to attend. It's a great opportunity to hear from experts in the communications space and also our customers. >> Well, we love the name signal. Extracting the signal from the noise was our original kind of tag line. Really appreciate it. And with all those customers, must be a hard challenge to have a cup conference, doing the keynote selections and figuring out what to do. What you're gonna have breakout sessions. Just get a little more detail on the event. You're gonna see the stage and customer story's going to break out sections. What's the format for the event? >> Yeah, so it's It's a two day, um, session. At most witty West. We have a number of breakouts. We have hands on training, which we call super class. We have, uh, keynotes. Last year we had an interactive performance with the band. OK, go. Uh, we had the creators of Westworld onstage. Geoff Lawson, our CEO, always kicked the Hoff ER, and it's just a great, exciting two days on, and we also this year, given that were hosting it during the summer time frame, we have ah camp experience for your children. And if you're looking to combine it with a summer vacation so we're super excited about signal, it's, uh, it's, Ah, two of my favorite days of the year from, Ah, Giulio perspective. And I'd love for everyone to come join us. >> We got a great customer success over the years, and great names congratulate Sarah. Thanks for been the time here in the Cube. I'm John Furry here in Palo Alto. Ceremony the chief marketing officer with Julio in San Francisco via remote. Thanks for watching this cute conversation.

(electronic music) >> Announcer: Live from Orlando Florida, it's the Cube, covering Grace Hopper Celebration of Women in Computing, brought to you by SiliconANGLE Media. >> Welcome back to the Cube's coverage of the Grace Hopper conference here in Orlando, Florida. I'm your host, Rebecca Knight. We're joined by LaFawn Davis, she is the global head of culture and inclusion at Twilio. Thanks so much for joining us. >> Thank you for having me. >> So let's start by telling our viewers what you do at Twilio. What does the global head of culture and inclusion do? >> That's a great question, it's kind of a newer title, so the culture piece is around our environment, our workspace, how employees feel, and it also incorporates employee experience, so we want to make sure that all the great talent we get in, we actually keep and develop and grow, and then there's the inclusion piece, the D&I piece, and that's the piece that people typically understand, so that is attracting, recruiting, retaining and developing top talent, it's making sure that we're looking at all of the diverse workforce that we want to have in the company, that we're serving our employees in the right way, and so it's nice that it's going to have both sides of that so it's not just purely about recruiting, it's not purely about numbers. It really is about how employees feel and it's whether or not they feel included, but also belong. >> So how do you do that? I mean, that's what every company wants, is to make employees feel happy about coming to work every morning. How do you do it? >> You have to ask. So it's really important that we have values that we can stand upon, every day. So we have what we call Nine Things, and they really are values, things like draw the owl, which is like you have to start somewhere. >> Rebecca: Draw the owl? >> Draw the owl. It's from an old internet meme that's around the way you draw an owl is you start with two circles, and then you draw the rest of the owl. You have to start somewhere. We have another one that's be humble. No shenanigans, that one you hear a lot, like if you're in a meeting and people are kind of ... thinking of doing things a different way? >> There are a few tech companies that maybe could have benefited from those shenanigans, but yeah. >> We'll call each other out, I mean, you'll hear it around the office. >> Rebecca: Do they, though? >> Oh no, absolutely. They absolutely will, they'll say, "That sounds a little shenanigan-y." or, you know, "We're not supposed to be doing "shenanigans here, so let's really "figure out how to do the right thing." And I think when you have values that are that specific, you can stand on them, you can count on them, and you can call each other out. >> Shenanigan-y? I love it, okay. >> (laughs) So it's like, let's be honest, and let's do what's right. >> But at the same time, I mean, it is, I understand how that can become the sort of safe word, and it's almost funny to say, "Hey, what are you doing here?" But how do you make those employees feel empowered enough to be able to call someone out, particularly if that person is a manager or a white guy that just has more bluster. >> Yeah, it starts from the top down. But even before I got to Twilio, I've only been at Twilio for six months but I did in the space for well over a decade, and what Twilio has is a top down and a bottoms up, so they were doing diversity inclusion and had employee resource groups before I got there. Three years before I got there, and the CEO is fantastic, and it really starts from that, messaging, you can tell the CEO he's being shenanigan-y. He expects you to, so we're hiring in people that espouse our values, we're looking for that, we're making sure that people come in with that understanding of, we don't want shenanigans here, we want you to be humble here, we want you to draw the owl, we want you to really acquire knowledge and thirst after it. Those are the things we look for, and so if you keep hiring people like that that already lend to your values, you're going to have, continue to have that culture. And it's not really about, oh I don't want to say this in front of, like, a C-Suite executive or in front of a leader, it's expected of you that you live those values no matter who you are. >> So as you've said, you've been in this space for a while, you worked for PayPal, Google, Yahoo. What have been the biggest changes you've seen over the course of your career? >> Yeah, so it's really a journey, right? I think the diversity journey especially ten years ago started with diversity, numbers, demographics, and it was really just gender globally and ethnicity U.S., and that's it and that's what people talked about, and those were the efforts that people made. It was really about recruiting, and now it's gone into more of the inclusion space and making sure people feel like they have a voice that can be heard, or they have a seat at the table, but honestly right now where we're at is the belonging space, right? Inclusion is really about making sure other people feel included and that you're hearing other perspectives. Belonging is a personal feeling. I feel like I belong here, and I'll tell you a funny story. When I first started Twilio, probably about two weeks in, I sit on the people team, which is next to the legal team, and the legal team's having this discussion and I'm like, wait a minute, oh my gosh, are you all conspiracy theorists? And they're like yeah! And I go, oh! Oh, you're my people! (Rebecca laughs) 'Cause I'm the one with the whiteboard and the red string and the tinfoil hat, and I immediately felt a sense of, you're my people, I feel like I'm supposed to be here. Everyone wants that feeling, and so the belonging space is really where companies are starting to focus, it's not just about having a seat at the table. Do you want to be here, do teams work well together? Are we working on something that's important to you? Do we have a vision that's inspiring to you? And that's more around belonging. I think the next step in this journey is equality, and we are a long way from that. >> And what do you make of that? I mean, you have been in this space for a while now, at some of the biggest, most respected tech names in the industry, and some of their names have been dragged through the mud around these issues, so I mean, are you discouraged, are you hopeful, what's your feeling now? >> I'm hopeful. I don't think I would still be doing it this long if I wasn't hopeful, and yes, I get tired. (laughs) >> Yeah, that we're still talking about it. >> Definitely get fatigued, but I'm very passionate about it, and that's how I ended up in this career. I started off in operations when I was at Google, and I was one of the founding members of the Black Googler Network, which is an employee's resource group, and I just got really passionate about being strategic. It wasn't just about building a sense of community. It was, no, let's figure out how to attract, recruit, retain and develop talent. Let's figure out like what the company needs and how we can plug in, and not just ... I mean, it lit a fire in me, and so I took lots of different roles within the D&I space and every time I think I'm going to step out, I get sucked back in. (they laugh) And so I think there's so much work to do. I think people inherently want to do the right thing. There's some bad apples that have been dragged through the mud lately, absolutely, but I think for the most part, people are coming from a good place. They may not know what to do, I think we have to change the conversation, because if we continue to do the same things over and over again, and they're not working, that should say something, right? >> So these, in terms of your past companies, Yahoo, Google, PayPal, they are much bigger than Twilio, Twilio is ... >> Less than a thousand employees. >> Less than a thousand people. How would you describe the biggest differences in terms of trying to affect change? >> Yeah, so I think the nice thing is, this is the first company where I don't fee like I have to talk about the business case for diversity. >> Rebecca: They already get it. >> They already get it, it's already got. My CEO will tell the story that when he started this company, he's like, I'm trying to build a company, and people were like, diversity, diversity, he's like, I'm trying to build a company. And then he really thought about it, and said, "Well, when is the right time to think about diversity? Is it when I have a thousand white male engineers?" Right, at that point you're fixing a problem as opposed to just starting with it and hiring people around that, and so it's the first company where I feel like that was already there, which is wonderful because now I can focus on the things that make the greatest impact, instead of starting from scratch, and so a smaller company, especially with more of a startup mentality, they just went public last year, I think it's almost easier in a way to make more progress because of that. >> And just in terms of what your CEO said about having to fix the problem, how do you think Twilio's products, how can you, how would a customer be able to tell that this was made by a diverse group of people, and it wasn't just a bunch of white guys in a room wearing hoodies, developing the Twilio suite? >> Platform. >> Rebecca: Yeah. >> The whole goal of the Twilio platform is to power up communication, right? That's the entire goal, and so I think as we're out and about, I mean we have this really cool role and it made this all tour, I just don't know it, and they're called developer evangelists, which I would love to be if I actually coded a little bit more, and they actually are the kind of, the middle of coding and evangelizing kind of what Twilio does, but a little bit of sales too, and so they're actually touching the community. We have community developers, we have, so it's not just people sitting at a desk in a room talking about what's best for people. It's we get out into the community, we understand what developers need, and we're constantly trying to figure out how do we create more doers, that's what we call people who create things. How do we create more doers? We have twilio.org, which is our foundation working with nonprofits, and there are social justice apps built on the platform. There are life-saving apps built on the platform. And we're funding these organizations so they can continue to build more and more on our platforms and change people's lives, and so I think that, and those examples, actually help people understand it's not just 400 white guys sitting in a room creating something for them. We're actually getting out and understanding what people need. >> And the research around diversity shows that diverse teams, it may take them a little slower to get the work done but the work is better, because it has taken in multiple perspectives, it has there's been more sort of fighting, and I don't mean to say fighting in the pejorative sense, but just getting to the ... >> LaFawn: Debating. >> The right answer, yeah, debate, exactly. (LaFawn laughs) To get to the right answer. I mean, would you say that's the experience? And I know you're not on the technical side, but what are you hearing from your ... >> I challenge that. >> Rebecca: Okay, all right. >> Every employee is encouraged to build something on the Twilio platform when they start, no matter what role they're in, and I am not in a technical role, but I know a little bit of coding now. But yes, absolutely, healthy debate is absolutely encouraged. How else are you going to build something for other people? It's really easy to just say, "I think we need to do this feature," right, but if that's not what people need, or you're not getting other perspectives, then you're building an inferior product. And so absolutely, you have to have that healthy debate, it's encouraged, and I see it (laughs) but it's not in a disrespectful way. So I have, being a part of the tech industry for a long time, I have seen some conversations that weren't so great, and people not treating each other well, thinking that that's how you have-- >> A little shenanigan-y. >> That's very shenanigan-y, right? Or calling each other names because they think that's how you get your point across. And I just don't feel that way at Twilio. It's much more respectful. I'm not saying that they don't get into it because I think you have to in order to really innovate. >> Well, LaFawn, thank you so much for joining us. It's been really a lot of fun talking to you. >> Thank you so much, you too. >> We will have more from Grace Hopper just after this. (electronic music)

(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)

>> Announcer: theCUBE's live coverage is made possible by funding from Dell Technologies. Creating technologies that drive human progress. (upbeat music) >> Hi everybody. Welcome back to Barcelona. We're here at the Fira Live, theCUBE's ongoing coverage of day two of MWC 23. Back in 2021 was my first Mobile World Congress. And you know what? It was actually quite an experience because there was nobody there. I talked to my friend, who's now my co-host, Chris Lewis about what to expect. He said, Dave, I don't think a lot of people are going to be there, but Danielle Royston is here and she's the CEO of Totoge. And that year when Erickson tapped out of its space she took out 60,000 square feet and built out Cloud City. If it weren't for Cloud City, there would've been no Mobile World Congress in June and July of 2021. DR is back. Great to see you. Thanks for coming on. >> It's great to see you. >> Chris. Awesome to see you. >> Yeah, Chris. Yep. >> Good to be back. Yep. >> You guys remember the narrative back then. There was this lady running around this crazy lady that I met at at Google Cloud next saying >> Yeah. Yeah. >> the cloud's going to take over Telco. And everybody's like, well, this lady's nuts. The cloud's been leaning in, you know? >> Yeah. >> So what do you think, I mean, what's changed since since you first caused all those ripples? >> I mean, I have to say that I think that I caused a lot of change in the industry. I was talking to leaders over at AWS yesterday and they were like, we've never seen someone push like you have and change so much in a short period of time. And Telco moves slow. It's known for that. And they're like, you are pushing buttons and you're getting people to change and thank you and keep going. And so it's been great. It's awesome. >> Yeah. I mean, it was interesting, Chris, we heard on the keynotes we had Microsoft, Satya came in, Thomas Curian came in. There was no AWS. And now I asked CMO of GSMA about that. She goes, hey, we got a great relationship with it, AWS. >> Danielle: Yeah. >> But why do you think they weren't here? >> Well, they, I mean, they are here. >> Mean, not here. Why do you think they weren't profiled? >> They weren't on the keynote stage. >> But, you know, at AWS, a lot of the times they want to be the main thing. They want to be the main part of the show. They don't like sharing the limelight. I think they just didn't want be on the stage with the Google CLoud guys and the these other guys, what they're doing they're building out, they're doing so much stuff. As Danielle said, with Telcos change in the ecosystem which is what's happening with cloud. Cloud's making the Telcos think about what the next move is, how they fit in with the way other people do business. Right? So Telcos never used to have to listen to anybody. They only listened to themselves and they dictated the way things were done. They're very successful and made a lot of money but they're now having to open up they're having to leverage the cloud they're having to leverage the services that (indistinct words) and people out provide and they're changing the way they work. >> So, okay in 2021, we talked a lot about the cloud as a potential disruptor, and your whole premise was, look you got to lean into the cloud, or you're screwed. >> Danielle: Yeah. >> But the flip side of that is, if they lean into the cloud too much, they might be screwed. >> Danielle: Yeah. >> So what's that equilibrium? Have they been able to find it? Are you working with just the disruptors or how's that? >> No I think they're finding it right. So my talk at MWC 21 was all about the cloud is a double-edged sword, right? There's two sides to it, and you definitely need to proceed through it with caution, but also I don't know that you have a choice, right? I mean, the multicloud, you know is there another industry that spends more on CapEx than Telco? >> No. >> Right. The hyperscalers are doing it right. They spend, you know, easily approaching over a $100 billion in CapEx that rivals this industry. And so when you have a player like that an industry driving, you know and investing so much Telco, you're always complaining how everyone's riding your coattails. This is the opportunity to write someone else's coattails. So jump on, right? I think you don't have a choice especially if other Telco competitors are using hyperscalers and you don't, they're going to be left behind. >> So you advise these companies all the time, but >> I mean, the issue is they're all they're all using all the hyperscalers, right? So they're the multi, the multiple relationships. And as Danielle said, the multi-layer of relationship they're using the hyperscalers to change their own internal operational environments to become more IT-centric to move to that software centric Telco. And they're also then with the hyperscalers going to market in different ways sometimes with them, sometimes competing with them. What what it means from an analyst point of view is you're suddenly changing the dynamic of a market where we used to have nicely well defined markets previously. Now they're, everyone's in it together, you know, it's great. And, and it's making people change the way they think about services. What I, what I really hope it changes more than anything else is the way the customers at the end of the, at the end of the supply, the value chain think this is what we can get hold of this stuff. Now we can go into the network through the cloud and we can get those APIs. We can draw on the mechanisms we need to to run our personal lives, to run our business lives. And frankly, society as a whole. It's really exciting. >> Then your premise is basically you were saying they should ride on the top over the top of the cloud vendor. >> Yeah. Right? >> No. Okay. But don't they lose the, all the data if they do that? >> I don't know. I mean, I think the hyperscalers are not going to take their data, right? I mean, that would be a really really bad business move if Google Cloud and Azure and and AWS start to take over that, that data. >> But they can't take it. >> They can't. >> From regulate, from sovereignty and regulation. >> They can't because of regulation, but also just like business, right? If they started taking their data and like no enterprises would use them. So I think, I think the data is safe. I think you, obviously every country is different. You got to understand the different rules and regulations for data privacy and, and how you keep it. But I think as we look at the long term, right and we always talk about 10 and 20 years there's going to be a hyperscaler region in every country right? And there will be a way for every Telco to use it. I think their data will be safe. And I think it just, you're going to be able to stand on on the shoulders of someone else for once and use the building blocks of software that these guys provide to make better experiences for subscribers. >> You guys got to explain this to me because when I say data I'm not talking about, you know, personal information. I'm talking about all the telemetry, you know, all the all the, you know the plumbing. >> Danielle: Yeah. >> Data, which is- >> It will increasingly be shared because you need to share it in order to deliver the services in the streamline efficient way that needs to be deliver. >> Did I hear the CEO of Ericsson Wright where basically he said, we're going to charge developers for access to that data through APIs. >> What the Ericsson have done, obviously with the Vage acquisition is they want to get into APIs. So the idea is you're exposing features, quality policy on demand type features for example, or even pulling we still use that a lot of SMS, right? So pulling those out using those APIs. So it will be charged in some way. Whether- >> Man: Like Twitter's charging me for APIs, now I API calls, you >> Know what it is? I think it's Twilio. >> Man: Oh, okay. >> Right. >> Man: No, no, that's sure. >> There's no reason why telcos couldn't provide a Twilio like service itself. >> It's a horizontal play though right? >> Danielle: Correct because developers need to be charged by the API. >> But doesn't there need to be an industry standard to do that as- >> Well. I think that's what they just announced. >> Industry standard. >> Danielle: I think they just announced that. Yeah. Right now I haven't looked at that API set, right? >> There's like eight of them. >> There's eight of them. Twilio has, it's a start you got to start somewhere Dave. (crosstalk) >> And there's all, the TM forum is all the other standard >> Right? Eight is better than zero- >> Right? >> Haven't got plenty. >> I mean for an industry that didn't really understand APIs as a feature, as a product as a service, right? For Mats Granryd, the deputy general of GSMA to stand on the keynote stage and say we partnered and we're unveiling, right. Pay by the use APIs. I was for it. I was like, that is insane. >> I liked his keynote actually, because I thought he was going to talk about how many attendees and how much economic benefiting >> Danielle: We're super diverse. >> He said, I would usually talk about that and you know greening in the network by what you did talk about a little bit. But, but that's, that surprised me. >> Yeah. >> But I've seen in the enterprise this is not my space as, you know, you guys don't live this but I've seen Oracle try to get developers. IBM had to pay $35 billion trying to get for Red Hat to get developers, right? EMC used to have a thing called EMC code, failed. >> I mean they got to do something, right? So 4G they didn't really make the business case the ROI on the investment in the network. Here we are with 5G, same discussion is having where's the use case? How are we going to monetize and make the ROI on this massive investment? And now they're starting to talk about 6G. Same fricking problem is going to happen again. And so I think they need to start experimenting with new ideas. I don't know if it's going to work. I don't know if this new a API network gateway theme that Mats talked about yesterday will work. But they need to start unbundling that unlimited plan. They need to start charging people who are using the network more, more money. Those who are using it less, less. They need to figure this out. This is a crisis for them. >> Yeah our own CEO, I mean she basically said, Hey, I'm for net neutrality, but I want to be able to charge the people that are using it more and more >> To make a return on, on a capital. >> I mean it costs billions of dollars to build these networks, right? And they're valuable. We use them and we talked about this in Cloud City 21, right? The ability to start building better metaverses. And I know that's a buzzword and everyone hates it, but it's true. Like we're working from home. We need- there's got to be a better experience in Zoom in 2D, right? And you need a great network for that metaverse to be awesome. >> You do. But Danielle, you don't need cellular for doing that, do you? So the fixed network is as important. >> Sure. >> And we're at mobile worlds. But actually what we beginning to hear and Crystal Bren did say this exactly, it's about the comp the access is sort of irrelevant. Fixed is better because it's more the cost the return on investment is better from fiber. Mobile we're going to change every so many years because we're a new generation. But we need to get the mechanism in place to deliver that. I actually don't agree that we should everyone should pay differently for what they use. It's a universal service. We need it as individuals. We need to make it sustainable for every user. Let's just not go for the biggest user. It's not, it's not the way to build it. It won't work if you do that you'll crash the system if you do that. And, and the other thing which I disagree on it's not about standing on the shoulders and benefiting from what- It's about cooperating across all levels. The hyperscalers want to work with the telcos as much as the telcos want to work with the hyperscalers. There's a lot of synergy there. There's a lot of ways they can work together. It's not one or the other. >> But I think you're saying let the cloud guys do the heavy lifting and I'm - >> Yeah. >> Not at all. >> And so you don't think so because I feel like the telcos are really good at pipes. They've always been good at pipes. They're engineers. >> Danielle: Yeah. >> Are they hanging on to the to the connectivity or should they let that go and well and go toward the developer. >> I mean AWS had two announcements on the 21st a week before MWC. And one was that telco network builder. This is literally being able to deploy a network capability at AWS with keystrokes. >> As a managed service. >> Danielle: Correct. >> Yeah. >> And so I don't know how the telco world I felt the shock waves, right? I was like, whoa, that seems really big. Because they're taking something that previously was like bread and butter. This is what differentiates each telco and now they've standardized it and made it super easy so anyone can do it. Now do I think the five nines of super crazy hardcore network criteria will be built on AWS this way? Probably not, but no >> It's not, it's not end twin. So you can't, no. >> Right. But private networks could be built with this pretty easily, right? And so telcos that don't have as much funding, right. Smaller, more experiments. I think it's going to change the way we think about building networks in telcos >> And those smaller telcos I think are going to be more developer friendly. >> Danielle: Yeah. >> They're going to have business models that invite those developers in. And that's, it's the disruption's going to come from the ISVs and the workloads that are on top of that. >> Well certainly what Dish is trying to do, right? Dish is trying to build a- they launched it reinvent a developer experience. >> Dave: Yeah. >> Right. Built around their network and you know, again I don't know, they were not part of this group that designed these eight APIs but I'm sure they're looking with great intent on what does this mean for them. They'll probably adopt them because they want people to consume the network as APIs. That's their whole thing that Mark Roanne is trying to do. >> Okay, and then they're doing open ran. But is it- they're not really cons- They're not as concerned as Rakuten with the reliability and is that the right play? >> In this discussion? Open RAN is not an issue. It really is irrelevant. It's relevant for the longer term future of the industry by dis aggregating and being able to share, especially ran sharing, for example, in the short term in rural environments. But we'll see some of that happening and it will change, but it will also influence the way the other, the existing ran providers build their services and offer their value. Look you got to remember in the relationship between the equipment providers and the telcos are very dramatically. Whether it's Ericson, NOKIA, Samsung, Huawei, whoever. So those relations really, and the managed services element to that depends on what skills people have in-house within the telco and what service they're trying to deliver. So there's never one size fits all in this industry. >> You're very balanced in your analysis and I appreciate that. >> I try to be. >> But I am not. (chuckles) >> So when Dr went off, this is my question. When Dr went off a couple years ago on the cloud's going to take over the world, you were skeptical. You gave a approach. Have you? >> I still am. >> Have you moderated your thoughts on that or- >> I believe the telecom industry is is a very strong industry. It's my industry of course I love it. But the relationship it is developing much different relationships with the ecosystem players around it. You mentioned developers, you mentioned the cloud players the equipment guys are changing there's so many moving parts to build the telco of the future that every country needs a very strong telco environment to be able to support the site as a whole. People individuals so- >> Well I think two years ago we were talking about should they or shouldn't they, and now it's an inevitability. >> I don't think we were Danielle. >> All using the hyperscalers. >> We were always going to need to transform the telcos from the conservative environments in which they developed. And they've had control of everything in order to reduce if they get no extra revenue at all, reducing the cost they've got to go on a cloud migration path to do that. >> Amenable. >> Has it been harder than you thought? >> It's been easier than I thought. >> You think it's gone faster than >> It's gone way faster than I thought. I mean pushing on this flywheel I thought for sure it would take five to 10 years it is moving. I mean the maths comp thing the AWS announcements last week they're putting in hyperscalers in Saudi Arabia which is probably one of the most sort of data private places in the world. It's happening really fast. >> What Azure's doing? >> I feel like I can't even go to sleep. Because I got to keep up with it. It's crazy. >> Guys. >> This is awesome. >> So awesome having you back on. >> Yeah. >> Chris, thanks for co-hosting. Appreciate you stay here. >> Yep. >> Danielle, amazing. We'll see you. >> See you soon. >> A lot of action here. We're going to come out >> Great. >> Check out your venue. >> Yeah the Togi buses that are outside. >> The big buses. You got a great setup there. We're going to see you on Wednesday. Thanks again. >> Awesome. Thanks. >> All right. Keep it right there. We'll be back to wrap up day two from MWC 23 on theCUBE. (upbeat music)

(bright upbeat music) >> Hello, everyone. Welcome to SiliconANGLE News breaking story here. Amazon Web Services expanding their relationship with Hugging Face, breaking news here on SiliconANGLE. I'm John Furrier, SiliconANGLE reporter, founder, and also co-host of theCUBE. And I have with me, Swami, from Amazon Web Services, vice president of database, analytics, machine learning with AWS. Swami, great to have you on for this breaking news segment on AWS's big news. Thanks for coming on and taking the time. >> Hey, John, pleasure to be here. >> You know- >> Looking forward to it. >> We've had many conversations on theCUBE over the years, we've watched Amazon really move fast into the large data modeling, SageMaker became a very smashing success, obviously you've been on this for a while. Now with ChatGPT OpenAI, a lot of buzz going mainstream, takes it from behind the curtain inside the ropes, if you will, in the industry to a mainstream. And so this is a big moment, I think, in the industry, I want to get your perspective, because your news with Hugging Face, I think is another tell sign that we're about to tip over into a new accelerated growth around making AI now application aware, application centric, more programmable, more API access. What's the big news about, with AWS Hugging Face, you know, what's going on with this announcement? >> Yeah. First of all, they're very excited to announce our expanded collaboration with Hugging Face, because with this partnership, our goal, as you all know, I mean, Hugging Face, I consider them like the GitHub for machine learning. And with this partnership, Hugging Face and AWS, we'll be able to democratize AI for a broad range of developers, not just specific deep AI startups. And now with this, we can accelerate the training, fine tuning and deployment of these large language models, and vision models from Hugging Face in the cloud. And the broader context, when you step back and see what customer problem we are trying to solve with this announcement, essentially if you see these foundational models, are used to now create like a huge number of applications, suggest like tech summarization, question answering, or search image generation, creative, other things. And these are all stuff we are seeing in the likes of these ChatGPT style applications. But there is a broad range of enterprise use cases that we don't even talk about. And it's because these kind of transformative, generative AI capabilities and models are not available to, I mean, millions of developers. And because either training these elements from scratch can be very expensive or time consuming and need deep expertise, or more importantly, they don't need these generic models, they need them to be fine tuned for the specific use cases. And one of the biggest complaints we hear is that these models, when they try to use it for real production use cases, they are incredibly expensive to train and incredibly expensive to run inference on, to use it at a production scale. So, and unlike web search style applications, where the margins can be really huge, here in production use cases and enterprises, you want efficiency at scale. That's where Hugging Face and AWS share our mission. And by integrating with Trainium and Inferentia, we're able to handle the cost efficient training and inference at scale, I'll deep dive on it. And by teaming up on the SageMaker front, now the time it takes to build these models and fine tune them is also coming down. So that's what makes this partnership very unique as well. So I'm very excited. >> I want to get into the time savings and the cost savings as well on the training and inference, it's a huge issue, but before we get into that, just how long have you guys been working with Hugging Face? I know there's a previous relationship, this is an expansion of that relationship, can you comment on what's different about what's happened before and then now? >> Yeah. So, Hugging Face, we have had a great relationship in the past few years as well, where they have actually made their models available to run on AWS, you know, fashion. Even in fact, their Bloom Project was something many of our customers even used. Bloom Project, for context, is their open source project which builds a GPT-3 style model. And now with this expanded collaboration, now Hugging Face selected AWS for that next generation office generative AI model, building on their highly successful Bloom Project as well. And the nice thing is, now, by direct integration with Trainium and Inferentia, where you get cost savings in a really significant way, now, for instance, Trn1 can provide up to 50% cost to train savings, and Inferentia can deliver up to 60% better costs, and four x more higher throughput than (indistinct). Now, these models, especially as they train that next generation generative AI models, it is going to be, not only more accessible to all the developers, who use it in open, so it'll be a lot cheaper as well. And that's what makes this moment really exciting, because we can't democratize AI unless we make it broadly accessible and cost efficient and easy to program and use as well. >> Yeah. >> So very exciting. >> I'll get into the SageMaker and CodeWhisperer angle in a second, but you hit on some good points there. One, accessibility, which is, I call the democratization, which is getting this in the hands of developers, and/or AI to develop, we'll get into that in a second. So, access to coding and Git reasoning is a whole nother wave. But the three things I know you've been working on, I want to put in the buckets here and comment, one, I know you've, over the years, been working on saving time to train, that's a big point, you mentioned some of those stats, also cost, 'cause now cost is an equation on, you know, bundling whether you're uncoupling with hardware and software, that's a big issue. Where do I find the GPUs? Where's the horsepower cost? And then also sustainability. You've mentioned that in the past, is there a sustainability angle here? Can you talk about those three things, time, cost, and sustainability? >> Certainly. So if you look at it from the AWS perspective, we have been supporting customers doing machine learning for the past years. Just for broader context, Amazon has been doing ML the past two decades right from the early days of ML powered recommendation to actually also supporting all kinds of generative AI applications. If you look at even generative AI application within Amazon, Amazon search, when you go search for a product and so forth, we have a team called MFi within Amazon search that helps bring these large language models into creating highly accurate search results. And these are created with models, really large models with tens of billions of parameters, scales to thousands of training jobs every month and trained on large model of hardware. And this is an example of a really good large language foundation model application running at production scale, and also, of course, Alexa, which uses a large generator model as well. And they actually even had a research paper that showed that they are more, and do better in accuracy than other systems like GPT-3 and whatnot. So, and we also touched on things like CodeWhisperer, which uses generative AI to improve developer productivity, but in a responsible manner, because 40% of some of the studies show 40% of this generated code had serious security flaws in it. This is where we didn't just do generative AI, we combined with automated reasoning capabilities, which is a very, very useful technique to identify these issues and couple them so that it produces highly secure code as well. Now, all these learnings taught us few things, and which is what you put in these three buckets. And yeah, like more than 100,000 customers using ML and AI services, including leading startups in the generative AI space, like stability AI, AI21 Labs, or Hugging Face, or even Alexa, for that matter. They care about, I put them in three dimension, one is around cost, which we touched on with Trainium and Inferentia, where we actually, the Trainium, you provide to 50% better cost savings, but the other aspect is, Trainium is a lot more power efficient as well compared to traditional one. And Inferentia is also better in terms of throughput, when it comes to what it is capable of. Like it is able to deliver up to three x higher compute performance and four x higher throughput, compared to it's previous generation, and it is extremely cost efficient and power efficient as well. >> Well. >> Now, the second element that really is important is in a day, developers deeply value the time it takes to build these models, and they don't want to build models from scratch. And this is where SageMaker, which is, even going to Kaggle uses, this is what it is, number one, enterprise ML platform. What it did to traditional machine learning, where tens of thousands of customers use StageMaker today, including the ones I mentioned, is that what used to take like months to build these models have dropped down to now a matter of days, if not less. Now, a generative AI, the cost of building these models, if you look at the landscape, the model parameter size had jumped by more than thousand X in the past three years, thousand x. And that means the training is like a really big distributed systems problem. How do you actually scale these model training? How do you actually ensure that you utilize these efficiently? Because these machines are very expensive, let alone they consume a lot of power. So, this is where SageMaker capability to build, automatically train, tune, and deploy models really concern this, especially with this distributor training infrastructure, and those are some of the reasons why some of the leading generative AI startups are actually leveraging it, because they do not want a giant infrastructure team, which is constantly tuning and fine tuning, and keeping these clusters alive. >> It sounds like a lot like what startups are doing with the cloud early days, no data center, you move to the cloud. So, this is the trend we're seeing, right? You guys are making it easier for developers with Hugging Face, I get that. I love that GitHub for machine learning, large language models are complex and expensive to build, but not anymore, you got Trainium and Inferentia, developers can get faster time to value, but then you got the transformers data sets, token libraries, all that optimized for generator. This is a perfect storm for startups. Jon Turow, a former AWS person, who used to work, I think for you, is now a VC at Madrona Venture, he and I were talking about the generator AI landscape, it's exploding with startups. Every alpha entrepreneur out there is seeing this as the next frontier, that's the 20 mile stairs, next 10 years is going to be huge. What is the big thing that's happened? 'Cause some people were saying, the founder of Yquem said, "Oh, the start ups won't be real, because they don't all have AI experience." John Markoff, former New York Times writer told me that, AI, there's so much work done, this is going to explode, accelerate really fast, because it's almost like it's been waiting for this moment. What's your reaction? >> I actually think there is going to be an explosion of startups, not because they need to be AI startups, but now finally AI is really accessible or going to be accessible, so that they can create remarkable applications, either for enterprises or for disrupting actually how customer service is being done or how creative tools are being built. And I mean, this is going to change in many ways. When we think about generative AI, we always like to think of how it generates like school homework or arts or music or whatnot, but when you look at it on the practical side, generative AI is being actually used across various industries. I'll give an example of like Autodesk. Autodesk is a customer who runs an AWS and SageMaker. They already have an offering that enables generated design, where designers can generate many structural designs for products, whereby you give a specific set of constraints and they actually can generate a structure accordingly. And we see similar kind of trend across various industries, where it can be around creative media editing or various others. I have the strong sense that literally, in the next few years, just like now, conventional machine learning is embedded in every application, every mobile app that we see, it is pervasive, and we don't even think twice about it, same way, like almost all apps are built on cloud. Generative AI is going to be part of every startup, and they are going to create remarkable experiences without needing actually, these deep generative AI scientists. But you won't get that until you actually make these models accessible. And I also don't think one model is going to rule the world, then you want these developers to have access to broad range of models. Just like, go back to the early days of deep learning. Everybody thought it is going to be one framework that will rule the world, and it has been changing, from Caffe to TensorFlow to PyTorch to various other things. And I have a suspicion, we had to enable developers where they are, so. >> You know, Dave Vellante and I have been riffing on this concept called super cloud, and a lot of people have co-opted to be multicloud, but we really were getting at this whole next layer on top of say, AWS. You guys are the most comprehensive cloud, you guys are a super cloud, and even Adam and I are talking about ISVs evolving to ecosystem partners. I mean, your top customers have ecosystems building on top of it. This feels like a whole nother AWS. How are you guys leveraging the history of AWS, which by the way, had the same trajectory, startups came in, they didn't want to provision a data center, the heavy lifting, all the things that have made Amazon successful culturally. And day one thinking is, provide the heavy lifting, undifferentiated heavy lifting, and make it faster for developers to program code. AI's got the same thing. How are you guys taking this to the next level, because now, this is an opportunity for the competition to change the game and take it over? This is, I'm sure, a conversation, you guys have a lot of things going on in AWS that makes you unique. What's the internal and external positioning around how you take it to the next level? >> I mean, so I agree with you that generative AI has a very, very strong potential in terms of what it can enable in terms of next generation application. But this is where Amazon's experience and expertise in putting these foundation models to work internally really has helped us quite a bit. If you look at it, like amazon.com search is like a very, very important application in terms of what is the customer impact on number of customers who use that application openly, and the amount of dollar impact it does for an organization. And we have been doing it silently for a while now. And the same thing is true for like Alexa too, which actually not only uses it for natural language understanding other city, even national leverages is set for creating stories and various other examples. And now, our approach to it from AWS is we actually look at it as in terms of the same three tiers like we did in machine learning, because when you look at generative AI, we genuinely see three sets of customers. One is, like really deep technical expert practitioner startups. These are the startups that are creating the next generation models like the likes of stability AIs or Hugging Face with Bloom or AI21. And they generally want to build their own models, and they want the best price performance of their infrastructure for training and inference. That's where our investments in silicon and hardware and networking innovations, where Trainium and Inferentia really plays a big role. And we can nearly do that, and that is one. The second middle tier is where I do think developers don't want to spend time building their own models, let alone, they actually want the model to be useful to that data. They don't need their models to create like high school homeworks or various other things. What they generally want is, hey, I had this data from my enterprises that I want to fine tune and make it really work only for this, and make it work remarkable, can be for tech summarization, to generate a report, or it can be for better Q&A, and so forth. This is where we are. Our investments in the middle tier with SageMaker, and our partnership with Hugging Face and AI21 and co here are all going to very meaningful. And you'll see us investing, I mean, you already talked about CodeWhisperer, which is an open preview, but we are also partnering with a whole lot of top ISVs, and you'll see more on this front to enable the next wave of generated AI apps too, because this is an area where we do think lot of innovation is yet to be done. It's like day one for us in this space, and we want to enable that huge ecosystem to flourish. >> You know, one of the things Dave Vellante and I were talking about in our first podcast we just did on Friday, we're going to do weekly, is we highlighted the AI ChatGPT example as a horizontal use case, because everyone loves it, people are using it in all their different verticals, and horizontal scalable cloud plays perfectly into it. So I have to ask you, as you look at what AWS is going to bring to the table, a lot's changed over the past 13 years with AWS, a lot more services are available, how should someone rebuild or re-platform and refactor their application of business with AI, with AWS? What are some of the tools that you see and recommend? Is it Serverless, is it SageMaker, CodeWhisperer? What do you think's going to shine brightly within the AWS stack, if you will, or service list, that's going to be part of this? As you mentioned, CodeWhisperer and SageMaker, what else should people be looking at as they start tinkering and getting all these benefits, and scale up their ups? >> You know, if we were a startup, first, I would really work backwards from the customer problem I try to solve, and pick and choose, bar, I don't need to deal with the undifferentiated heavy lifting, so. And that's where the answer is going to change. If you look at it then, the answer is not going to be like a one size fits all, so you need a very strong, I mean, granted on the compute front, if you can actually completely accurate it, so unless, I will always recommend it, instead of running compute for running your ups, because it takes care of all the undifferentiated heavy lifting, but on the data, and that's where we provide a whole variety of databases, right from like relational data, or non-relational, or dynamo, and so forth. And of course, we also have a deep analytical stack, where data directly flows from our relational databases into data lakes and data virus. And you can get value along with partnership with various analytical providers. The area where I do think fundamentally things are changing on what people can do is like, with CodeWhisperer, I was literally trying to actually program a code on sending a message through Twilio, and I was going to pull up to read a documentation, and in my ID, I was actually saying like, let's try sending a message to Twilio, or let's actually update a Route 53 error code. All I had to do was type in just a comment, and it actually started generating the sub-routine. And it is going to be a huge time saver, if I were a developer. And the goal is for us not to actually do it just for AWS developers, and not to just generate the code, but make sure the code is actually highly secure and follows the best practices. So, it's not always about machine learning, it's augmenting with automated reasoning as well. And generative AI is going to be changing, and not just in how people write code, but also how it actually gets built and used as well. You'll see a lot more stuff coming on this front. >> Swami, thank you for your time. I know you're super busy. Thank you for sharing on the news and giving commentary. Again, I think this is a AWS moment and industry moment, heavy lifting, accelerated value, agility. AIOps is going to be probably redefined here. Thanks for sharing your commentary. And we'll see you next time, I'm looking forward to doing more follow up on this. It's going to be a big wave. Thanks. >> Okay. Thanks again, John, always a pleasure. >> Okay. This is SiliconANGLE's breaking news commentary. I'm John Furrier with SiliconANGLE News, as well as host of theCUBE. Swami, who's a leader in AWS, has been on theCUBE multiple times. We've been tracking the growth of how Amazon's journey has just been exploding past five years, in particular, past three. You heard the numbers, great performance, great reviews. This is a watershed moment, I think, for the industry, and it's going to be a lot of fun for the next 10 years. Thanks for watching. (bright music)

(gentle music) >> Good morning from Las Vegas. It's theCUBE live at AWS Reinvent 2022 with tons of thousands of people today. Really kicks off the event. Big keynote that I think is probably just wrapping up. Lisa Martin here with Dave Vellante. Dave, this is going to be an action packed week on theCUBE no doubt. We talked with so many different companies. Every company's a software company these days but we're also seeing a lot of companies leaving software that can help them operate more efficiently in the background. >> Yeah, well some things haven't changed at Reinvent. A lot of people here, you know, back to 2019 highs and I think we exceeded those two hour keynotes. Peter DeSantis last night talking about new Graviton instances and then Adam Selipsky doing the typical two hour keynote. But what was different he was a lot more poetic than we used to hear from Andy Jassy, right? He was talking about the universe as an analogy for data. >> I loved that. >> Talked about ocean exploration as for the security piece and then exploring into the Antarctic for, you know, better chips, you know? So yeah, I think he did a good job there. I think a lot of people might not love it but I thought it was very well done. >> I thought so too. We're having kicking off a great day of live content for you all day today. We've got Eleanor Dorfman joining us, the sales leader at Retool. Eleanor, welcome to theCUBE. It's great to have you. >> Thank you so much for having me. >> So let's talk a little bit about Retool. I was looking on your LinkedIn page. I love the tagline, build custom internal tools best. >> Eleanor: Yep. >> Talk to us a little bit about the company you recently raised, series C two. Give us the backstory. >> Yeah, so the company was founded in 2017 by two co-founders who are best friends from college. They actually set out to build a FinTech company, a payments company. And as they were building that, they needed to build a ton of custom operations software that goes with that. If you're going to be managing people's money, you need to be able to do refunds. You need to be able to look up accounts, you need to be able to detect fraud, you need to do know your customer operations. And as they were building the sort of operations software that supports the business, they realized that there were patterns to all of it and that the same components were used at and again. And had the insight that that was actually probably a better direction to go in than recreating Venmo, which was I think the original idea. And that actually this is a problem every company has because every company needs operations engineering and operations software to run their business. And so they pivoted and started building Retool which is a platform for building custom operations software or internal tools. >> Dave: Good pivot. >> In hindsight, actually probably in the moment as well, was a good pivot. >> But you know, when you talk about some of those things, refunds, fraud, you know, KYC, you know, you think of operations software, you think of it as just internal, but all those things are customer facing. >> Eleanor: Yep. >> Right so, are we seeing as sort of this new era? Is that a trend that you guys, your founders saw that hey, these internal operations can be pointed at customers to support what, a better customer service, maybe even generate revenue, subscriptions? >> I think it's a direction we're actually heading now but we're just starting to scratch the surface of that. The focus for the last five years has very much been on this operations software and sort of changing the economics of developing it and making it easy and fast to productize workflows that were previously being done in spreadsheets or hacky workarounds and make it easier for companies to prioritize those so they can run their business more efficiently. >> And where are you having your customer conversations these days? Thinking of operations software in the background, but to Dave's point, it ends up being part of the customer experience. So where are you having your customer conversations, target audience, who's that persona? >> Mainly developers. So we're working almost exclusively with developer teams who have backlogs and backlogs of internal tools requests to build that sales teams are building manual forecasts. Support teams are in 19 different tools. Their supply chain teams are using seven different spreadsheets to do demand forecasting or freight forwarding or things like that. But they've never been able to be prioritized to the top of the list because customer facing software, revenue generating software, always takes prioritization. And in this economic environment, which is challenging for many companies right now, it's important to be able to do more with less and maximize the productivity especially of high value employees like engineers and developers. >> So what would you say the biggest business outcomes are? If the developer is really the focus, productivity is the- >> Productivity. It's for both, I would say. Developer productivity and being able to maximize your sort of R and D and maximize the productivity of your engineers and take away some of the very boring parts of the job. But, so I would say developer productivity, but then also the tools and the software that they're building are very powerful for end users. So I would say efficiency and productivity across your business. >> Across the business. >> I mean historically, you know, operations is where we focused IT and code. How much of the code out there is dedicated to sort of operations versus that customer facing? >> So I think it would actually be, it's kind of surprising. We have run a few surveys on this sort of, we call them the state of engineering time, and focusing on what developers are spending their time on. And a third of all code that is being written today is actually for this internal operations software. >> Interesting. And do you guys have news at the show? Are you announcing anything interesting or? >> Yeah, so our focus historically, you sort of gave away with one of your early questions, but our focus has always been on this operations, this building web applications on building UIs on top of databases and APIs and doing that incredibly fast and being able to do it all in one place and integrate with as any data source that you need. We abstract away access authentication deployment and you build applications for your internal teams. But recently, we've launched two new products. We're actually supporting more external use cases and more customer facing use cases as well as automating CRON jobs, ETL jobs alerting with the new retail workflows product. So we're expanding the scope of operations software from web applications to also internal operations like CRON jobs and ETL jobs. >> Explain that. Explain the scourge of CRON jobs to the audience. >> Yeah, so operations software businesses run on operations software. It's interesting, zooming out, it's actually something you said earlier as well. Every company has become a software company. So when you think about software, you tend to think about here. Very cool software that people are selling. And software that you use as a consumer. But Coca-Cola for example, has hundreds of software engineers that are building tools to make the business run for forecasting, for demand gen, for their warehouse distribution and monitoring inventory. And there's two types of that. There's the applications that they build and then the operations that have to run behind that. Maybe a workflow that is detecting how many bottles of Coca-Cola are in every warehouse and sending a notification to the right person when they're out or when they, a refill is very strong, but you know when you need a refill. So it does that, it takes those tasks, those jobs that run in the background and enables you to customize them and build them very rapidly in a code first way. >> So some of the notes that you guys provided say that there's over 500 million software apps that are going to be built in the next few years alone. That's tremendous. How much of that is operation software? >> I mean I think at least a third of that, if not more. To the point where every company is being forced to maximize their resources today and operational efficiency is the way to do that. And so it can become a competitive advantage when you can take the things that humans are doing in spreadsheets with 19 open tabs and automate that. That saves hours a day. That's a significant, significant driver of efficiency and productivity for a business >> It does, and there's direct correlation to the customer experience. The use experience. >> Almost certainly. When you think about building support tooling, I was web chat, chatting on the with Gogo wifi support on my flight over here and they asked for my order number and I sent it and they looked up my account and that's a custom piece of software they were using to look up the account, create a new account for me, and restore my second wifi purchase. And so when you think about it, you're actually, even just as a consumer, interacting with this custom software on the day time. And that's because that's what companies use to have a good customer experience and have an efficient business. >> And what's the relationship with AWS? You guys started, I think you said 2017, so you obviously started in the cloud, but I'm particularly interested in from a seller perspective, what that's like. Working with Amazon, how's that affected your business? >> Yeah, I mean so we're built on AWS, so we're customers and big fans. And obviously like from a selling perspective, we have a ton of integrations with AWS so we're able to integrate directly into all the different AWS products that people are using for databases, for data warehouses, for deployment configurations, for monitoring, for security, for observability, we can basically fit into your existing AWS stack in order to make it as seamless integration with your software so that building in Retool is just as seamless as building it on your own, just much, much faster. >> So in your world, I know you wanted to but, in your world is it more analytics? is it more transactional, sort of? Is it both? >> It's all of the above. And I think what's, over Thanksgiving, I was asked a lot to explain what Retool did with people who were like, we just got our first iPhone. And so I tried to explain with an example because I have yet to stumble on the perfect metaphor. But the example I typically use is DoorDash is a customer of ours. And for about three years, and three years ago, they had a problem. They had no way of turning off delivery in certain zip codes during storms. Which as someone who has had orders canceled during a storm, it's an incredibly frustrating experience. And the way it worked is that they had operation team members manually submitting requests to engineers to say there's a storm in this zip code and an engineer would run a manual task. This didn't scale with Doordash as they were opening in new countries all over the world that have very different weather patterns. And so they looked, they had one, they were sort of confronted with a choice. They could buy a piece of software out of the box. There is not a startup that does this yet. They could build it by hand, which would mean scoping the requirements designing a UI, building authentication, building access controls, putting it into a, putting it into a sprint, assigning an engineer. This would've taken months and months. And then it would take just as long to iterate on it or they could use Retool. So they used Retool, they built this app, it saved, I think they were saying up to two years of engineering time for this one application because of how quickly it was. And since then they've built, I think 50 or 60 more automating away other tasks like that that were one out of spreadsheets or in Jira or in Slack notifications or an email saying, "Hey, could you please do this thing? There's a storm." And so now they use us for dozens and dozens of operations like that. >> A lot of automation and of course a lot of customer delight on the other end of the spectrum as you were talking about. It is frustrating when you don't get that order but it's also the company needs to be able to have the the tools in place to automate to be able to react quickly. >> Eleanor: Exactly. >> Because the consumers are, as we know, quite demanding. I wanted to ask you, I mentioned the tagline in the beginning, build custom internal tools fast. You just gave us a great example of DoorDash. Huge business outcomes they're achieving but how fast are we talking? How fast can the average developer build these internal tools? >> Well, we've been doing a fun thing at our booth where we ask people what a problem is and build a tool for them while we're there. So for something lightweight, you can build it in 10 minutes. For something a little more complex, it can take up to a few weeks depending on what the requirements are. But we all have people who will be on a call with us introducing them to our software for the first time and they'll start telling us about their problems and in the background we'll be building it and then at the end we're like, is this what you meant? And they're like, we'd like to add that to our cart. And obviously, it's a platform so you can't do that. But we've been able to build applications on a call before while people are telling us what they need. >> So fast is fast. >> I would say very fast, yeah. >> Now how do you price? >> Right now, we have a couple different plans. We actually have a motion where you can sign up on our website and get started. So we have a free plan, we've got plans for startups, and then we've got plans all the way up to the enterprise. >> Right. And that's a subscription pricing kind of thing? >> Subscription model, yes. >> So I get a subscription to the platform and then what? Is there also a consumption component? >> Exactly. So there's a consumption component as well. So there's access to the platform and then you can build as many applications as you need. Or build as many workflows. >> When you're having customer conversations with prospects, what do you define as Retool's superpowers? You're the sales leader. What are some of those key superpowers that you think really differentiate Retool? >> I do think, well, the sales team first and foremost, but that's not a fair answer. I would say that people are a bit differentiator though. We have a lot of very talented people who are have a ton of domain expertise and care a ton about the customer outcomes, which I do actually think is a little more rare than it should be. But we're one of the only products out there that's built with a developer first mindset, a varied code first mindset, built to integrate with your software development life cycle but also built with the security and robustness that enterprise companies require. So it's able to take an enterprise grade software with a developer first approach while still having a ton of agility and nimbleness which is what people are really craving as the earth keeps moving around them. So I would say that's something that really sets us apart from the field. >> And then talk about some of the what developers are saying, some of the feedback, some of the responses, and maybe even, I know we're just on day one of the show, but any feedback from the booth so far? >> We've had a few people swing by our booth and show us their Retool apps, which is incredibly cool. That's my absolute favorite thing is encountering a Retool application in the wild which happens a lot more than I would've thought, which I shouldn't say, but is incredibly rewarding. But people love it. It's the reason I joined is I'd never heard someone have a product that customers talked about the way they talk about Retool because Retool enables them to do things. For some folks who use it, it enables them to do something they previously couldn't do. So it gives them super powers in their job and to triple their impact. And then for others, it just makes things so fast. And it's a very delightful experience. It's very much built by developers, for developers. And so it's built with a developer's first mindset. And so I think it's quite fun to build in Retool. Even I can build and Retool, though not well. And then it's extremely impactful and people are able to really impact their business and delight their coworkers which I think can be really meaningful. >> Absolutely. Delighting the coworkers directly relates to delighting the customers. >> Eleanor: Exactly. >> Those customer experience, employee experience, they're like this. >> Eleanor: Exactly. >> They go hand in hand and the employee experience has to be outstanding to be able to delight those customers, to reduce churn, to increase revenue- >> Eleanor: Exactly. >> And for brand reputation. >> And it also, I think there is something as someone who is customer facing, when my coworkers and developers I work with build tools that enable me to do my job better and feel better about my own performance and my ability to impact the customer experience, it's just this incredibly virtuous cycle. >> So Retool.com is where folks can go to learn more and also try that subscription that you said was free for up to five users. >> Yes, exactly. >> All right. I guess my last question, well couple questions for you. What are some of the things that excited you that you heard from Adam Selipsky this morning? Anything from the keynote that stood out in terms of- >> Dave: Did you listen to the keynote? >> I did not. I had customer calls this morning. >> Okay, so they're bringing- >> East coast time, east coast time. >> One of the things that will excite you I think is they're connecting, making it easier to connect their databases. >> Eleanor: That would very much exciting. >> Aurora and Redshift, right? Okay. And they're making it easier to share data. I dunno if it goes across regions, but they're doing better integration. >> Amazing. >> Right? And you guys are integrating with those tools, right? Those data platforms. So that to me was a big thing for you guys. >> It is also and what a big thing Retool does is you can build a UI layer for your application on top of every single data source. And you hear, it's funny, you hear people talk about the 360 degree review of the customer so much. This is another, it's not our primary value proposition, but it is certainly another way to get there is if you have data from their desk tickets from in Redshift, you have data from Stripe, from their payments, you have data from Twilio from their text messages, you have data from DataDog where they're having your observability where you can notice analytics issues. You can actually just use Retool to build an app that sits on top of that so that you can give your support team, your sales team, your account management team, customer service team, all of the data that they need on their customers. And then you can build workflows so that you can do automated customer engagement reports. I did a Slack every week that shows what our top customers are doing with the product and that's built using all of our automation software as well. >> The integration is so important, as you just articulated, because every, you know, we say every company's a software company these days. Every company's a data company. But also, the data democratization that needs to happen to be able for lines of business so that data moves out of certain locked in functions and enables lines of business to use it. To get that visibility that you were just talking about is really going to be a competitive advantage for those that survive and thrive and grow in this market. >> It's able to, I think it's first it's visibility, but then it's action. And I think that's what Retool does very uniquely as well is it can take and unite the data from all the places, takes it out of the black box, puts it in front of the teams, and then enables them to act on it safely and securely. So not only can you see who might be fraudulent, you can flag them as fraud. Not only can you see who's actually in danger, you can click a button and send them an email and set up a meeting. You can set up an approval workflow to bring in an exec for engagement. You can update a password for someone in one place where you can see that they're having issues and not have to go somewhere else to update the password. So I think that's the key is that Retool can unlock the data visibility and then the action that you need to serve your customers. >> That's a great point. It's all about the actions, the insights that those actions can be acted upon. Last question for you. If you had a billboard that you could put any message that you want on Retool, what would it say? What's the big aha? This is why Retool is so great. >> I mean, I think the big thing about Retool is it's changing the economics of software development. It takes something that previously would've been below the line and that wouldn't get prioritized because it wasn't customer facing and makes it possible. And so I would say one of two billboards if I could be a little bit greedy, one would be Retool changed the economics of software development and one would be build operations software at the speed of thought. >> I love that. You're granted two billboards. >> Eleanor: Thank you. >> Those are both outstanding. Eleanor, it's been such a pleasure having you on the program. Thank you for talking to us about Retool. >> Eleanor: Thank you. >> Operations software and the massive impact that automating it can make for developers, businesses alike, all the way to the top line. We appreciate your insights. >> Thank you so much. >> For our guests and Dave Vellante, I'm Lisa Martin. You're watching theCUBE, the leader in live, emerging, and enterprise tech coverage. (gentle music)

>>Hey guys. Welcome back to the Cubes coverage of Ansible Fast 2022. This is day two of our wall to wall coverage. Lisa Martin here with John Ferer. John, we're seeing this world where companies are saying if we can't automate it, we need to, The automation market is transforming. There's been a lot of buzz about that. A lot of technical chops here at Ansible Fest. >>Yeah, I mean, we've got a great guest here coming on Cuba alumni, Dean Newman, future room. He travels every event he's got. He's got his nose to the grindstone ear to the ground. Great analysis. I mean, we're gonna get into why it's important. How does Ansible fit into the big picture? It's really gonna be a great segment. The >>Board do it well, John just did my job for me about, I'll introduce him again. Daniel Newman, one of our alumni is Back Principal Analyst at Future and Research. Great to have you back on the cube. >>Yeah, it's good to join you. Excited to be back in Chicago. I don't know if you guys knew this, but for 40 years, this was my hometown. Now I don't necessarily brag about that anymore. I'm, I live in Austin now. I'm a proud Texan, but I did grow up here actually out in the west suburbs. I got off the plane, I felt the cold air, and I almost turned around and said, Does this thing go back? Yeah. Cause I'm, I've, I've grown thin skin. It did not take me long. I, I like the warm, Come on, >>I'm the saying, I'm from California and I got off the plane Monday. I went, Whoa, I need a coat. And I was in Miami a week ago and it was 85. >>Oh goodness. >>Crazy. So you just flew in. Talk about what's going on, your take on, on Ansible. We've talked a lot with the community, with partners, with customers, a lot of momentum. The flywheel of the community is going around and round and round. What are some of your perspectives that you see? >>Yeah, absolutely. Well, let's you know, I'm gonna take a quick step back. We're entering an era where companies are gonna have to figure out how to do more with less. Okay? We've got exponential data growth, we've got more architectural complexity than ever before. Companies are trying to discern how to deal with many different environments. And just at a macro level, Red Hat is one of the companies that is almost certainly gonna be part of this multi-cloud hybrid cloud era. So that should initially give a lot of confidence to the buying group that are looking at how to automate their environments. You're automating workflows, but really with, with Ansible, we're focused on automating it, automating the network. So as companies are kind of dig out, we're entering this recessionary period, Okay, we're gonna call it what it is. The first thing that they're gonna look at is how do we tech our way out of it? >>I had a wonderful one-on-one conversation with ServiceNow ceo, Bill McDermott, and we saw ServiceNow was in focus this morning in the initial opening session. This is the integration, right? Ansible integrating with ServiceNow. What we need to see is infrastructure automation, layers and applications working in concert to basically enable enterprises to be up and running all the time. Let's first fix the problems that are most common. Let's, let's automate 'em, let's script them. And then at some point, let's have them self resolving, which we saw at the end with Project Wisdom. So as I see it, automation is that layer that enterprises, boards, technologists, all can agree upon are basically here's something that can make our business more efficient, more profitable, and it's gonna deal with this short term downturn in a way that tech is actually gonna be the answer. Just like Bill and I said, let's tech our way out of it. >>If you look at the Red Hat being bought by ibm, you see Project Wisdom Project, not a product, it's a project. Project Wisdom is the confluence of research and practitioners kind of coming together with ai. So bringing AI power to the Ansible is interesting. Red Hat, Linux, Rel OpenShift, I mean, Red Hat's kind of position, isn't it? Kind of be in that right spot where a puck might be coming maybe. I mean, what do you think? >>Yeah, as analysts, we're really good at predicting the, the recent past. It's a joke I always like to make, but Red Hat's been building toward the future. I think for some time. Project Wisdom, first of all, I was very encouraged with it. One of the things that many people in the market probably have commented on is how close is IBM in Red Hat? Now, again, it's a $34 billion acquisition that was made, but boy, the cultures of these two companies couldn't be more different. And of course, Red Hat kind of carries this, this sort of middle ground layer where they provide a lot of value in services to companies that maybe don't use IBM at, at, for the public cloud especially. This was a great indication of how you can take the power of IBM's research, which of course has some of the world's most prolific data scientists, engineers, building things for the future. >>You know, you see things like yesterday they launched a, you know, an AI solution. You know, they're building chips, semiconductors, and technologies that are gonna power the future. They're building quantum. Long story short, they have these really brilliant technologists here that could be adding value to Red Hat. And I don't know that the, the world has fully been able to appreciate that. So when, when they got on stage and they kind of say, Here's how IBM is gonna help power the next generation, I was immediately very encouraged by the fact that the two companies are starting to show signs of how they can collaborate to offer value to their customers. Because of course, as John kind of started off with, his question is, they've kind of been where the puck is going. Open source, Linux hybrid cloud, This is the future. In the future. Every company's multi-cloud. And I said in a one-on-one meeting this morning, every company is going to probably have workloads on every cloud, especially large enterprises. >>Yeah. And I think that the secret's gonna be how do you make that evolve? And one of the things that's coming out of the industry over the years, and looking back as historians, we would say, gotta have standards. Well, with cloud, now people standards might slow things down. So you're gonna start to figure out how does the community and the developers are thinking it'll be the canary in the coal mine. And I'd love to get your reaction on that, because we got Cuban next week. You're seeing people kind of align and try to win the developers, which, you know, I always laugh cuz like, you don't wanna win, you want, you want them on your team, but you don't wanna win them. It's like a, it's like, so developers will decide, >>Well, I, I think what's happening is there are multiple forces that are driving product adoption. And John, getting the developers to support the utilization and adoption of any sort of stack goes a long way. We've seen how sticky it can be, how sticky it is with many of the public cloud pro providers, how sticky it is with certain applications. And it's gonna be sticky here in these interim layers like open source automation. And Red Hat does have a very compelling developer ecosystem. I mean, if you sat in the keynote this morning, I said, you know, if you're not a developer, some of this stuff would've been fairly difficult to understand. But as a developer you saw them laughing at jokes because, you know, what was it the whole part about, you know, it didn't actually, the ping wasn't a success, right? And everybody started laughing and you know, I, I was sitting next to someone who wasn't technical and, and you know, she kinda goes, What, what was so funny? >>I'm like, well, he said it worked. Do you see that? It said zero data trans or whatever that was. So, but if I may just really quickly, one, one other thing I did wanna say about Project Wisdom, John, that the low code and no code to the full stack developer is a continuum that every technology company is gonna have to think deeply about as we go to the future. Because the people that tend to know the process that needs to be automated tend to not be able to code it. And so we've seen every automation company on the planet sort of figuring out and how to address this low code, no code environment. I think the power of this partnership between IBM Research and Red Hat is that they have an incredibly deep bench of capabilities to do things like, like self-training. Okay, you've got so much data, such significant size models and accuracy is a problem, but we need systems that can self teach. They need to be able self-teach, self learn, self-heal so that we can actually get to the crux of what automation is supposed to do for us. And that's supposed to take the mundane out and enable those humans that know how to code to work on the really difficult and hard stuff because the automation's not gonna replace any of that stuff anytime soon. >>So where do you think looking at, at the partnership and the evolution of it between IBM research and Red Hat, and you're saying, you know, they're, they're, they're finally getting this synergy together. How is it gonna affect the future of automation and how is it poised to give them a competitive advantage in the market? >>Yeah, I think the future or the, the competitive space is that, that is, is ecosystems and integration. So yesterday you heard, you know, Red Hat Ansible focusing on a partnership with aws. You know, this week I was at Oracle Cloud world and they're talking about running their database in aws. And, and so I'm kind of going around to get to the answer to your question, but I think collaboration is sort of the future of growth and innovation. You need multiple companies working towards the same goal to put gobs of resources, that's the technical term, gobs of resources towards doing really hard things. And so Ansible has been very successful in automating and securing and focusing on very certain specific workloads that need to be automated, but we need more and there's gonna be more data created. The proliferation, especially the edge. So you saw all this stuff about Rockwell, How do you really automate the edge at scale? You need large models that are able to look and consume a ton of data that are gonna be continuously learning, and then eventually they're gonna be able to deliver value to these companies at scale. IBM plus Red Hat have really great resources to drive this kind of automation. Having said that, I see those partnerships with aws, with Microsoft, with ibm, with ServiceNow. It's not one player coming to the table. It's a lot of players. They >>Gotta be Switzerland. I mean they have the Switzerland. I mean, but the thing about the Amazon deal is like that marketplace integration essentially puts Ansible once a client's in on, on marketplace and you get the central on the same bill. I mean, that's gonna be a money maker for Ansible. I >>Couldn't agree more, John. I think being part of these public cloud marketplaces is gonna be so critical and having Ansible land and of course AWS largest public cloud by volume, largest marketplace today. And my opinion is that partnership will be extensible to the other public clouds over time. That just makes sense. And so you start, you know, I think we've learned this, John, you've done enough of these interviews that, you know, you start with the biggest, with the highest distribution and probability rates, which in this case right now is aws, but it'll land on in Azure, it'll land in Google and it'll continue to, to grow. And that kind of adoption, streamlining make it consumption more consumable. That's >>Always, I think, Red Hat and Ansible, you nailed it on that whole point about multicloud, because what happens then is why would I want to alienate a marketplace audience to use my product when it could span multiple environments, right? So you saw, you heard that Stephanie yesterday talk about they, they didn't say multiple clouds, multiple environments. And I think that is where I think I see this layer coming in because some companies just have to work on all clouds. That's the way it has to be. Why wouldn't you? >>Yeah. Well every, every company will probably end up with some workloads in every cloud. I just think that is the fate. Whether it's how we consume our SaaS, which a lot of people don't think about, but it always tends to be running on another hyperscale public cloud. Most companies tend to be consuming some workloads from every cloud. It's not always direct. So they might have a single control plane that they tend to lead the way with, but that is only gonna continue to change. And every public cloud company seems to be working on figuring out what their niche is. What is the one thing that sort of drives whether, you know, it is, you know, traditional, we know the commoditization of traditional storage network compute. So now you're seeing things like ai, things like automation, things like the edge collaboration tools, software being put into the, to the forefront because it's a different consumption model, it's a different margin and economic model. And then of course it gives competitive advantages. And we've seen that, you know, I came back from Google Cloud next and at Google Cloud next, you know, you can see they're leaning into the data AI cloud. I mean, that is their focus, like data ai. This is how we get people to come in and start using Google, who in most cases, they're probably using AWS or Microsoft today. >>It's a great specialty cloud right there. That's a big use case. I can run data on Google and run something on aws. >>And then of course you've got all kinds of, and this is a little off topic, but you got sovereignty, compliance, regulatory that tends to drive different clouds over, you know, global clouds like Tencent and Alibaba. You know, if your workloads are in China, >>Well, this comes back down at least to the whole complexity issue. I mean, it has to get complex before it gets easier. And I think that's what we're seeing companies opportunities like Ansible to be like, Okay, tame, tame the complexity. >>Yeah. Yeah, I totally agree with you. I mean, look, when I was watching the demonstrations today, my take is there's so many kind of simple, repeatable and mundane tasks in everyday life that enterprises need to, to automate. Do that first, you know? Then the second thing is working on how do you create self-healing, self-teaching, self-learning, You know, and, and I realize I'm a little broken of a broken record at this, but these are those first things to fix. You know, I know we want to jump to the future where we automate every task and we have multi-term conversational AI that is booking our calendars and driving our cars for us. But in the first place, we just need to say, Hey, the network's down. Like, let's make sure that we can quickly get access back to that network again. Let's make sure that we're able to reach our different zones and locations. Let's make sure that robotic arm is continually doing the thing it's supposed to be doing on the schedule that it's been committed to. That's first. And then we can get to some of these really intensive deep metaverse state of automation that we talk about. Self-learning, data replication, synthetic data. I'm just gonna throw terms around. So I sound super smart. >>In your customer conversations though, from an looking at the automation journey, are you finding most of them, or some percentage is, is wanting to go directly into those really complex projects rather than starting with the basics? >>I don't know that you're, you're finding that the customers want to do that? I think it's the architecture that often ends up being a problem is we as, as the vendor side, will tend to talk about the most complex problems that they're able to solve before companies have really started solving the, the immediate problems that are before them. You know, it's, we talk about, you know, the metaphor of the cloud is a great one, but we talk about the cloud, like it's ubiquitous. Yeah. But less than 30% of our workloads are in the public cloud. Automation is still in very early days and in many industries it's fairly nascent. And doing things like self-healing networks is still something that hasn't even been able to be deployed on an enterprise-wide basis, let alone at the industrial layer. Maybe at the company's on manufacturing PLAs or in oil fields. Like these are places that have difficult to reach infrastructure that needs to be running all the time. We need to build systems and leverage the power of automation to keep that stuff up and running. That's, that's just business value, which by the way is what makes the world go running. Yeah. Awesome. >>A lot of customers and users are struggling to find what's the value in automating certain process, What's the ROI in it? How do you help them get there so that they understand how to start, but truly to make it a journey that is a success. >>ROI tends to be a little bit nebulous. It's one of those things I think a lot of analysts do. Things like TCO analysis Yeah. Is an ROI analysis. I think the businesses actually tend to know what the ROI is gonna be because they can basically look at something like, you know, when you have an msa, here's the downtime, right? Business can typically tell you, you know, I guarantee you Amazon could say, Look for every second of downtime, this is how much commerce it costs us. Yeah. A company can generally say, if it was, you know, we had the energy, the windmills company, like they could say every minute that windmill isn't running, we're creating, you know, X amount less energy. So there's a, there's a time value proposition that companies can determine. Now the question is, is about the deployment. You know, we, I've seen it more nascent, like cybersecurity can tend to be nascent. >>Like what does a breach cost us? Well there's, you know, specific costs of actually getting the breach cured or paying for the cybersecurity services. And then there's the actual, you know, ephemeral costs of brand damage and of risks and customer, you know, negative customer sentiment that potentially comes out of it. With automation, I think it's actually pretty well understood. They can look at, hey, if we can do this many more cycles, if we can keep our uptime at this rate, if we can reduce specific workforce, and I'm always very careful about this because I don't believe automation is about replacement or displacement, but I do think it is about up-leveling and it is about helping people work on things that are complex problems that machines can't solve. I mean, said that if you don't need to put as many bodies on something that can be immediately returned to the organization's bottom line, or those resources can be used for something more innovative. So all those things are pretty well understood. Getting the automation to full deployment at scale, though, I think what often, it's not that roi, it's the timeline that gets misunderstood. Like all it projects, they tend to take longer. And even when things are made really easy, like with what Project Wisdom is trying to do, semantically enable through low code, no code and the ability to get more accuracy, it just never tends to happen quite as fast. So, but that's not an automation problem, That's just the crux of it. >>Okay. What are some of the, the next things on your plate? You're quite a, a busy guy. We, you, you were at Google, you were at Oracle, you're here today. What are some of the next things that we can expect from Daniel Newman? >>Oh boy, I moved Really, I do move really quickly and thank you for that. Well, I'm very excited. I'm taking a couple of work personal days. I don't know if you're a fan, but F1 is this weekend. I'm the US Grand Prix. Oh, you're gonna Austin. So I will be, I live in Austin. Oh. So I will be in Austin. I will be at the Grand Prix. It is work because it, you know, I'm going with a number of our clients that have, have sponsorships there. So I'll be spending time figuring out how the data that comes off of these really fun cars is meaningfully gonna change the world. I'll actually be talking to Splunk CEO at the, at the race on Saturday morning. But yeah, I got a lot of great things. I got a, a conversation coming up with the CEO of Twilio next week. We got a huge week of earnings ahead and so I do a lot of work on that. So I'll be on Bloomberg next week with Emily Chang talking about Microsoft and Google. Love talking to Emily, but just as much love being here on, on the queue with you >>Guys. Well we like to hear that. Who you're rooting for F one's your favorite driver. I, >>I, I like Lando. Do you? I'm Norris. I know it's not necessarily a fan favorite, but I'm a bit of a McLaren guy. I mean obviously I have clients with Oracle and Red Bull with Ball Common Ferrari. I've got Cly Splunk and so I have clients in all. So I'm cheering for all of 'em. And on Sunday I'm actually gonna be in the Williams Paddock. So I don't, I don't know if that's gonna gimme me a chance to really root for anything, but I'm always, always a big fan of the underdog. So maybe Latifi. >>There you go. And the data that comes off the how many central unbeliev, the car, it's crazy's. Such a scientific sport. Believable. >>We could have Christian, I was with Christian Horner yesterday, the team principal from Reside. Oh yeah, yeah. He was at the Oracle event and we did a q and a with him and with the CMO of, it's so much fun. F1 has been unbelievable to watch the momentum and what a great, you know, transitional conversation to to, to CX and automation of experiences for fans as the fan has grown by hundreds of percent. But just to circle back full way, I was very encouraged with what I saw today. Red Hat, Ansible, IBM Strong partnership. I like what they're doing in their expanded ecosystem. And automation, by the way, is gonna be one of the most robust investment areas over the next few years, even as other parts of tech continue to struggle that in cyber security. >>You heard it here. First guys, investment in automation and cyber security straight from two analysts. I got to sit between. For our guests and John Furrier, I'm Lisa Martin, you're watching The Cube Live from Chicago, Ansible Fest 22. John and I will be back after a short break. SO'S stick around.

(upbeat music) >> Man: We're good. >> Hey everyone. Welcome back to theCube's live coverage of AWS Summit NYC. We're in New York City, been here all day. Lisa Martin, John Furrier, talking with AWS partners ecosystem folks, customers, AWS folks, you name it. Next up, one of our alumni, rejoins us. Please welcome Anshu Sharma the co-founder and CEO of Skyflow. Anshu great to have you back on theCube. >> Likewise, I'm excited to be back. >> So I love how you guys founded this company. Your inspiration was the zero trust data privacy vault pioneered by two of our favorites, Apple and Netflix. You started with a simple question. What if privacy had an API? So you built a data privacy vault delivered as an API. Talk to us, and it's only in the last three and a half years. Talk to us about a data privacy vault and what's so unique about it. >> Sure. I think if you think about all the key challenges we are seeing in our personal lives when we are dealing with technology companies a lot of anxiety is around what happens to my data, right? If you want to go to a pharmacy they want to know not just your health ID number but they want to know your social security number your credit card number, your phone number and all of that information is actually useful because they need to be able to engage with you. And it's true for hospitals, health systems. It's true for your bank. It's true for pretty much anybody you do business with even an event like this. But then question that keeps coming up is where does this data go? And how is it protected? And the state of the art here has always been to keep kind of, keep it protected when it's in storage but almost all the breaches, all the hacks happen not because you've steal somebody's disc, but because someone enters through an API or a portal. So the question we asked was we've been building different shapes of containers for different types of data. You don't store your logs in a data warehouse. You don't store your analytical data in a regular RDBMS. Similarly, you don't store your passwords and usernames you store them in identity systems. So if PI is so special why isn't it a container that's used for storing PII? So that's how the idea of Pii.World came up. >> So you guys just got a recent funding, a series B financing which means for the folks out there that don't know the inside baseball, must people do, means you're doing well. It's hard to get that round of funding means you're up and growing to the right. What's the differentiator? Why are you guys so successful? Why the investment growth, what's the momentum driver? >> So I think in some ways we took one of the most complex problems, data privacy, like half the people can't even describe like, does data privacy mean like I have to be GDPR compliant or does it actually mean I'm protecting the data? So you have multiple stakeholders in any company. If you're a pharma company, you may have a chief privacy officer, a data officer, this officer, that officer, and all of these people were talking and the answer was buy more tools. So if you look around behind our back, there's probably dozens of companies out there. One protecting data in an API call another protecting data in a database, another one data warehouse. But as a CEO, CTO, I want to know what happens to my social security number from a customer end to end. So we said, if you can radically simplify the whole thing and the key insight was you can simplify it by actually isolating and protecting this data. And this architecture evolved on its own at companies like Apple and other places, but it takes dozens of engineers for those companies to build it out. So we like, well, the pattern will makes sense. It logically kind is just common sense. So instead of selling dozens of tools, we can just give you a very simple product, which is like one API call, you know, protect this data... >> So like Stripe is for a plugin for a financial transaction you plug it into the app, similar dynamic here, right? >> Exactly. So it's Stripe for payments, Twilio for Telephony. We have API for everything, but if you have social security numbers or pan numbers you still are like relying on DIY. So I think what differentiated us and attracted the investors was, if this works, >> It's huge. every company needs it. >> Well, that's the integration has become the key thing. I got to ask you because you mentioned GDPR and all the complexities around the laws and the different regulations. That could be a real blocker in a wet blanket for innovation. >> Anshu: Yes. >> And with the market we're seeing here at, at your Summit New York, small event. 10,000 people, more people here than were at Snowflake Summit as an example. And they're the hottest company in data. So this small little New York event is proven that that world is growing. So why should this wet blanket, these rules slow it down? How do you balance it? 'Cause that's a concern. If you checking all the boxes you're never actually building anything. >> So, you know, we just ran into a couple of customers who still are struggling with moving from the data center to AWS Cloud. Now the fact that here means they want to but something is holding them back. I also met the AI team of Amazon. They're doing some amazing work and they're like, the biggest hindrance for them is making customers feel safe when they do the machine learning. Because now you're opening up the data sets to more people. And in all of those cases your innovation basically stops because CSO is like, look you can't put PII in the cloud unprotected. And with the vault architecture we call it privacy by architecture. So there's a term called privacy by design. I'm like what the, is privacy by design, right? >> John: It's an architecture. (John laughing) >> But if you are an architecture and a developer like me I was like, I know what architecture is. I don't know what privacy by design is. >> So you guys are basically have that architecture by design which means foundational based services. So you're providing that as a service. So other people don't have to build the complex. >> Anshu: Exactly. >> You know that you will be Apple's backend team to build that privacy with you you get all that benefit. >> Exactly. And traditionally, people have had to make compromises. If you encrypt the data and secure it, then you can't use it. Using a proprietary polymorphic encryption technology you can actually have your cake and eat it to. So what that means for customers is, if you want to protect data in Snowflake or REDshare, use Skyflow with it. We have integrations to databases, to data lakes, all the common workflow tools. >> Can you give us a customer example that you think really articulates the value of what Skyflow is delivering? >> Well, I'll give you two examples. One in the FinTech space, one in the health space. So in the FinTech space this is a company called Nomi Health. They're a large payments processor for the health insurance market. And funnily enough, their CTO actually came from Goldman Sachs. He actually built apple card. (John laughing) Right? That if we all have in our phones. And he saw our product and he's like, for my new company, I'm going to just use you guys because I don't want to go hire 20 engineers. So for them, we had a HIPAA compliant environment a PCI compliant environment, SOC 2 compliant environment. And he can sleep better at night because he doesn't have to worry what is my engineer in Poland or Ukraine doing right now? I have a vault. I have rules set up. I can audit it. Everything is logged. Similarly for Science 37, they run clinical trials globally. They wanted to solve data residency. So for them the problem was, how do I run one common global instance? When the rules say you have to break everything up and that's very expensive. >> And so I love this. I'm a customer. For them a customer. I love it. You had me at hello, API integration. I love it. How much does it cost? What's it going to cost me? How do I need to think about my operationalizing? 'Cause I know with an API, I can do that. Am I paying by the usage, by the drink? How do I figure out? >> So we have programs for startups where it's really really inexpensive. We get them credits. And then for enterprises, we basically have a platform fee. And then based on the amount of data PII, we charge them. We don't nickel and dime the customers. We don't like the usage based model because, you don't know how many times you're going to hit an API. So we usually just based on the number of customer records that you have and you can hit them as many time as you want. There's no API limits. >> So unlimited record based. >> Exactly. that's your variable. >> Exactly. We think about you buying odd zero, for example, for authentication you pay them by the number of active users you have. So something similar. >> So you run on AWS, but you just announced a couple of new GTM partners, MuleSoft and plan. Can you talk to us about, start with MuleSoft? What are you doing and why? And the same with VLA? >> Sure. I mean, MuleSoft was very interesting customers who were adopting our products at, you know, we are buying this product for our new applications but what about our legacy code? We can't go in there and add APIs there. So the simplest way to do integration in the legacy world is to use an integration broker. So that's where MuleSoft integration came out and we announced that. It's a logical place for you to swap out real social security numbers with, you know, fake ones. And then we also announced a partnership with SnowFlake, same thing. I think every workload as it's moving to the cloud needs some kind of data protection with it. So I think going forward we are going to be announcing even more partnerships. So you can imagine all the places you're storing PII today whether it's in a call center solution or analytics solution, there's a PII story there. >> Talk about the integration aspect because I love the momentum. I get everything makes secure the customers all these environments, integrations are super important to plug into. And then how do I essentially operate you on my side? Do I import the records? How do you connect to my environment in my databases? >> So it's really, really easy when you encrypt the data and use Skyflow wall, we create what is called a format preserving token, which is essentially replacing a social security number with something that looks like an SSN but it's not. So that there's no schema changes involved. You just have to do that one time swap over and then in terms of integrations, most of these integrations are prebuilt. So Snowflake integration is prebuilt. MuleSoft integration is prebuilt. We're going to announce some new ones. So the goal is for off the table in platforms like Snowflake and MuleSoft, we prebuilt all the integrations. You can build your own. It takes about like a day. And then in terms of data import basically it's the same standard process that you would use with any other data store. >> Got to ask you about data breaches. Obviously the numbers in 2021 were huge. We're seeing so much change in the cyber security landscape ransomware becoming a household word, a matter of when but not if... How does Skyflow help organizations protect themselves or reduce the number of breaches so that they are not the next headline? >> You know, the funny thing about breaches is again and again, we see people doing the same mistakes, right? So Equifax had a breach four years ago where a customer portal, you know, no customer support rep should have access to a 100 million people's data. Like is that customer agent really accessing 100 million? But because we've been using legacy security tools they either give you access or don't give you access. And that's not how it's going to work. Because if I'm going to engage with the pharmacy and airline they need to be able to use my data in multiple different places. So you need to have fine grain controls around it. So I think the reason we keep getting breaches is cybersecurity industry is selling, 10s of billions of dollars worth of tools in the name of security but they cannot be applied at a fine grain level enough. I can't say things like for my call center agent that's living in Phoenix, Arizona they can only verify last four digits, but the same call center worker in Philippines can't even see that. So how do you get all that granular control in place? Is really why we keep seeing data breaches. So the Equifax breach, the Shopify breach the Twitter breaches, they're all the same. Like again and again, it's either an inside person or an external person who's gotten in. And once you're in and this is the whole idea of zero trust as you know. Once you're in, you can access all the data. Zero trust means that you don't assume that you actually isolate PII separately. >> A lot of the cybersecurity issues as you were talking about, are people based. Somebody clicking on something or gaining access. And I always talk to security experts about how do you control for the people aspect besides training, awareness, education. Is Skyflow a facilitator of that in a way that we haven't seen before? >> Yeah. So I think what ends up happening is, people even after they have breaches, they will lock down the system that had the breach, but then they have the same data sitting in a partner database, maybe a customer database maybe a billing system. So by centralizing and isolating PII in one system you can then post roles based access control rules. You can put limitations around it. But if you try to do that across hundreds of DS bases, you're just not going to be able to do it because it's basically just literally impossible, so... >> My final question for you is on, for me is you're here at AWS Summits, 10,000 people like I said. More people here than some big events and we're just in New York city. Okay. You actually work with AWS. What's next for you guys as you got the fresh funding, you guys looking for more talent, what's your next mountain you're going to climb? Tell us what's next for the company. Share your vision, put a plug in for the company. >> Well, it's actually very simple. Today we actually announced that we have a new chief revenue officer who's joining us. Tammy, she's joined us from LaunchDarkly which is it grew from like, you know, single digits to like over nine digits in revenue. And the reason she's joining Skyflow is because she sees the same inflection point hitting us. And for us that means more marketing, more sales, more growth in more geographies and more partnerships. And we think there's never been a better time to solve privacy. Literally everything that we deal with even things like rove evade issues eventually ties back into a issue around privacy. >> Lisa: Yes. >> AWS gets the model API, you know, come on, right? That's their model. >> Exactly. So I think if you look at the largest best companies that have been built in the last 20 years they took something that should have been simple but was not. There used to be Avayas of the world, selling Telephony intel, Twilio came and said, look an API. And we are trying to do the same to the entire security compliance and privacy industry is to narrow the problem down and solve it once. >> (indistinct) have it. We're going to get theCube API. (Lisa laughing) That's what we're going to do. All right. >> Thank you so much. >> Awesome. Anshu, thank you for joining us, talking to us about what's new at Skyflow. It sounds like you got that big funding investment. Probably lots of strategic innovation about to happen. So you'll have to come back in a few months and maybe at next reinvent in six months and tell us what's new, what's going on. >> Last theCube interview was very well received. People really like the kind of questions you guys asked. So I love this show and I think... >> It's great when you're a star like you, you got good market, great team, smart. I mean, look at this. I mean, what slow down are we talking about here? >> Yeah. I don't see... >> There is no slow down on the enterprise. >> Privacy's hot and it's incredibly important and we're only going to be seeing more and more of it. >> You can talk to any CIO, CSO, CTO or the board and they will tell you there is no limit to the budget they have for solving the core privacy issues. We love that. >> John: So you want to move on to building? >> Lisa: Obviously that must make you smile. >> John: You solved a big problem. >> Thank you. >> Awesome. Anshu, thank you again. Congrats on the momentum and we'll see you next time and hear more on the evolution of Skyflow. Thank you for your time. >> Thank you. >> For John furrier, I'm Lisa Martin. You're watching theCube live from New York City at AWS Summit NYC 22. We'll be right back with our next guest. So stick around. (upbeat music)

>>Hello, everyone. Welcome to the cubes presentation of the 80, but startup showcases MarTech is the focus. And this is all about the emerging cloud scale customer experience. This is season two, episode three of the ongoing series covering the exciting, fast growing startups from the cloud AWS ecosystem to talk about the future and what's available now, where are the actions? I'm your host John fur. Today. We joined by Cub alumni, Jerry Chen partner at Greylock ventures. Jerry. Great to see you. Thanks for coming on, >>John. Thanks for having me back. I appreciate you welcome there for season two. Uh, as a, as a guest star, >><laugh>, you know, Hey, you know, season two, it's not a one and done it's continued coverage. We, we got the episodic, uh, cube flicks model going >>Here. Well, you know, congratulations, the, the coverage on this ecosystem around AWS has been impressive, right? I think you and I have talked a long time about AWS and the ecosystem building. It just continues to grow. And so the coverage you did last season, all the events of this season is, is pretty amazing from the data security to now marketing. So it's, it's great to >>Watch. And 12 years now, the cube been running. I remember 2013, when we first met you in the cube, we just left VMware just getting into the venture business. And we were just riffing the next 80. No one really kind of knew how big it would be. Um, but we were kinda riffing on. We kind of had a sense now it's happening. So now you start to see every vertical kind of explode with the right digital transformation and disruption where you see new incumbents. I mean, new Newton brands get replaced the incumbent old guard. And now in MarTech, it's ripe for, for disruption because web two has gone on to web 2.5, 3, 4, 5, um, cookies are going away. You've got more governance and privacy challenges. There's a slew of kind of ad tech baggage, but yet lots of new data opportunities. Jerry, this is a huge, uh, thing. What's your take on this whole MarTech cloud scale, uh, >>Market? I, I think, I think to your point, John, that first the trends are correct and the bad and the good or good old days, the battle days MarTech is really about your webpage. And then email right there. There's, there's the emails, the only channel and the webpage was only real estate and technology to care about fast forward, you know, 10 years you have webpages, mobile apps, VR experiences, car experiences, your, your, your Alexa home experiences. Let's not even get to web three web 18, whatever it is. Plus you got text messages, WhatsApp, messenger, email, still great, et cetera. So I think what we've seen is both, um, explosion and data, uh, explosion of channel. So sources of data have increases and the fruits of the data where you can reach your customers from text, email, phone calls, etcetera have exploded too. So the previous generation created big company responses, Equa, you know, that exact target that got acquired by Oracle or, or, um, Salesforce, and then companies like, um, you know, MailChimp that got acquired as well, but into it, you're seeing a new generation companies for this new stack. So I, I think it's exciting. >>Yeah. And you mentioned all those things about the different channels and stuff, but the key point is now the generation shifts going on, not just technical generation, uh, and platform and tools, it's the people they're younger. They don't do email. They have, you know, proton mail accounts, zillion Gmail accounts, just to get the freebie. Um, they're like, they're, they'll do subscriptions, but not a lot. So the generational piece on the human side is huge. Okay. And then you got the standards, bodies thrown away, things like cookies. Sure. So all this is makes it for a complicated, messy situation. Um, so out of this has to come a billion dollar startup in my mind, >>I, I think multiple billion dollars, but I think you're right in the sense that how we want engage with the company branch, either consumer brands or business brands, no one wants to pick a phone anymore. Right? Everybody wants to either chat or DM people on Twitter. So number one, the, the way we engage is different, both, um, where both, how like chat or phone, but where like mobile device, but also when it's the moment when we need to talk to a company or brand be it at the store, um, when I'm shopping in real life or in my car or at the airport, like we want to reach the brands, the brands wanna reach us at the point of decision, the point of support, the point of contact. And then you, you layer upon that the, the playing field, John of privacy security, right? All these data silos in the cloud, the, the, the, the game has changed and become even more complicated with the startup. So the startups are gonna win. Will do, you know, the collect, all the data, make us secure in private, but then reach your customers when and where they want and how they want it. >>So I gotta ask you, because you had a great podcast just this week, published and snowflake had their event going on the data cloud, there's a new kind of SAS platform vibe going on. You're starting to see it play out. Uh, and one of the things I, I noticed on your podcast with the president of Hashi Corp, who was on people should listen to that podcast. It's on gray matter, which is the Greylocks podcast, uh, plug for you guys. He mentioned he mentions the open source dynamic, right? Sure. And, and I like what he, things, he said, he said, software business has changed forever. It's my words. Now he said infrastructure, but I'm saying software in general, more broader infrastructure and software as a category is all open source. One game over no debate. Right. You agree? >>I, I think you said infrastructure specifically starts at open source, but I would say all open source is one more or less because open source is in every bit of software. Right? And so from your operating system to your car, to your mobile phone, open source, not necessarily as a business model or, or, or whatever, we can talk about that. But open source as a way to build software distribute, software consume software has one, right? It is everywhere. So regardless how you make money on it, how you build software, an open source community ha has >>One. Okay. So let's just agree. That's cool. I agree with that. Let's take it to the next level. I'm a company starting a company to sell to big companies who pay. I gotta have a proprietary advantage. There's gotta be a way. And there is, I know you've talked about it, but I have my opinion. There is needs to be a way to be proprietary in a way that allows for that growth, whether it's integration, it's not gonna be on software license or maybe support or new open source model. But how does startups in the MarTech this area in general, when they disrupt or change the category, they gotta get value creation going. What's your take on, on building. >>You can still build proprietary software on top of open source, right? So there's many companies out there, um, you know, in a company called rock set, they've heavily open source technology like Rock's DB under the hood, but they're running a cloud database. That's proprietary snowflake. You talk about them today. You know, it's not open source technology company, but they use open source software. I'm sure in the hoods, but then there's open source companies, data break. So let's not confus the two, you can still build proprietary software. There's just components of open source, wherever we go. So number one is you can still build proprietary IP. Number two, you can get proprietary data sources, right? So I think increasingly you're seeing companies fight. I call this systems intelligence, right, by getting proprietary data, to train your algorithms, to train your recommendations, to train your applications, you can still collect data, um, that other competitors don't have. >>And then it can use the data differently, right? The system of intelligence. And then when you apply the system intelligence to the end user, you can create value, right? And ultimately, especially marketing tech, the highest level, what we call the system of engagement, right? If, if the chat bot the mobile UI, the phone, the voice app, etcetera, if you own the system of engagement, be a slack, or be it, the operating system for a phone, you can also win. So still multiple levels to play John in multiple ways to build proprietary advantage. Um, just gotta own system record. Yeah. System intelligence, system engagement. Easy, right? Yeah. >>Oh, so easy. Well, the good news is the cloud scale and the CapEx funded there. I mean, look at Amazon, they've got a ton of open storage. You mentioned snowflake, but they're getting a proprietary value. P so I need to ask you MarTech in particular, that means it's a data business, which you, you pointed out and we agree. MarTech will be about the data of the workflows. How do you get those workflows what's changing and how these companies are gonna be building? What's your take on it? Because it's gonna be one of those things where it might be the innovation on a source of data, or how you handle two parties, ex handling encrypted data sets. I don't know. Maybe it's a special encryption tool, so we don't know what it is. What's your what's, what's your outlook on this area? >>I, I, I think that last point just said is super interesting, super genius. It's integration or multiple data sources. So I think either one, if it's a data business, do you have proprietary data? Um, one number two with the data you do have proprietary, not how do you enrich the data and do you enrich the data with, uh, a public data set or a party data set? So this could be cookies. It could be done in Brad street or zoom info information. How do you enrich the data? Number three, do you have machine learning models or some other IP that once you collected the data, enriched the data, you know, what do you do with the data? And then number four is once you have, um, you know, that model of the data, the customer or the business, what do you deal with it? Do you email, do you do a tax? >>Do you do a campaign? Do you upsell? Do you change the price dynamically in our customers? Do you serve a new content on your website? So I think that workflow to your point is you can start from the same place, what to do with the data in between and all the, on the out the side of this, this pipeline is where a MarTech company can have then. So like I said before, it was a website to an email go to website. You know, we have a cookie fill out a form. Yeah. I send you an email later. I think now you, you can't just do a website to email, it's a website plus mobile apps, plus, you know, in real world interaction to text message, chat, phone, call Twitter, a whatever, you know, it's >>Like, it's like, they're playing checkers in web two and you're talking 3d chess. <laugh>, I mean, there's a level, there's a huge gap between what's coming. And this is kind of interesting because now you mentioned, you know, uh, machine learning and data, and AI is gonna factor into all this. You mentioned, uh, you know, rock set. One of your portfolios has under the hood, you know, open source and then use proprietary data and cloud. Okay. That's a configuration, that's an architecture, right? So architecture will be important in terms of how companies posture in this market, cuz MarTech is ripe for innovation because it's based on these old technologies, but there's tons of workflows, but you gotta have the data. Right. And so if I have the best journey map from a client that goes to a website, but then they go and they do something in the organic or somewhere else. If I don't have that, what good is it? It's like a blind spot. >>Correct. So I think you're seeing folks with the data BS, snowflake or data bricks, or an Amazon that S three say, Hey, come to my data cloud. Right. Which, you know, Snowflake's advertising, Amazon will say the data cloud is S3 because all your data exists there anyway. So you just, you know, live on S3 data. Bricks will say, S3 is great, but only use Amazon tools use data bricks. Right. And then, but on top of that, but then you had our SaaS companies like Oracle, Salesforce, whoever, and say, you know, use our qua Marketo, exact target, you know, application as a system record. And so I think you're gonna have a battle between, do I just work my data in S3 or where my data exists or gonna work my data, some other application, like a Marketo Ella cloud Z target, um, or, you know, it could be a Twilio segment, right. Was combination. So you'll have this battle between these, these, these giants in the cloud, easy, the castles, right. Versus, uh, the, the, the, the contenders or the, or the challengers as we call >>'em. Well, great. Always chat with the other. We always talk about castles in the cloud, which is your work that you guys put out, just an update on. So check out greylock.com. They have castles on the cloud, which is a great thesis on and a map by the way ecosystem. So you guys do a really good job props to Jerry and the team over at Greylock. Um, okay. Now I gotta ask kind of like the VC private equity sure. Market question, you know, evaluations. Uh, first of all, I think it's a great time to do a startup. So it's a good time to be in the VC business. I think the next two years, you're gonna find some nice gems, but also you gotta have that cleansing period. You got a lot of overvaluation. So what happened with the markets? So there's gonna be a lot of M and a. So the question is what are some of the things that you see as challenges for product teams in particular that might have that killer answer in MarTech, or might not have the runway if there's no cash, um, how do people partner in this modern era, cuz scale's a big deal, right? Mm-hmm <affirmative> you can measure everything. So you get the combination of a, a new kind of M and a market coming, a potential growth market for the right solution. Again, value's gotta be be there. What's your take on this market? >>I, I, I think you're right. Either you need runway, so cash to make it through, through this next, you know, two, three years, whatever you think the market Turmo is or two, you need scale, right? So if you're at a company of scale and you have enough data, you can probably succeed on your own. If not, if you're kind of in between or early to your point, either one focus, a narrower wedge, John, just like we say, just reduce the surface area. And next two years focus on solving one problem. Very, very well, or number two in this MarTech space, especially there's a lot of partnership and integration opportunities to create a complete solution together, to compete against kind of the incumbents. Right? So I think they're folks with the data, they're folks doing data, privacy, security, they're post focusing their workflow or marketing workflows. You're gonna see either one, um, some M and a, but I definitely can see a lot of Coopers in partnership. And so in the past, maybe you would say, I'm just raise another a hundred million dollars and do what you're doing today. You might say, look, instead of raising more money let's partner together or, or merge or find a solution. So I think people are gonna get creative. Yeah. Like said scarcity often is good. Yeah. I think forces a lot more focus and a lot more creativity. >>Yeah. That's a great point. I'm glad you brought that up up. Cause I didn't think you were gonna go there. I was gonna ask that biz dev activity is going to be really fundamental because runway combined with the fact that, Hey, you know, if you know, get real or you're gonna go under is a real issue. So now people become friends. They're like, okay, if we partner, um, it's clearly a good way to go if you can get there. So what advice would you give companies? Um, even most experienced, uh, founders and operators. This is a different market, right? It's a different kind of velocity, obviously architectural data. You mentioned some of those key things. What's the posture to partner. What's your advice? What's the combat man manual to kind of compete in this new biz dev world where some it's a make or break time, either get the funding, get the customers, which is how you get funding or you get a biz dev deal where you combine forces, uh, go to market together or not. What's your advice? >>I, I think that the combat manual is either you're partnering for one or two things, either one technology or two customers or sometimes both. So it would say which partnerships, youre doing for technology EG solution completers. Like you have, you know, this puzzle piece, I have this puzzle piece data and data privacy and let's work together. Um, or number two is like, who can help you with customers? And that's either a, I, they can be channel for you or, or vice versa or can share customers and you can actually go to market together and find customers jointly. So ideally you're partner for one, if not the other, sometimes both. And just figure out where in your life cycle do you need? Um, friends. >>Yeah. Great. My final question, Jerry, first of all, thanks for coming on and sharing your in insight as usual. Always. Awesome final question for the folks watching that are gonna be partnering and buying product and services from these startups. Um, there's a select few great ones here and obviously every other episode as well, and you've got a bunch you're investing in this, it's actually a good market for the ones that are lean companies that are lean and mean have value. And the cloud scale does provide that. So a lot of companies are getting it right, they're gonna break through. So they're clearly gonna be getting customers the buyer side, how should they be looking through the lens right now and looking at companies, what should they look for? Um, and they like to take chances with seeing that. So it's not so much, they gotta be vetted, but you know, how do they know the winners from the pretenders? >>You know, I, I think the customers are always smart. I think in the, in the, in the past in market market tech, especially they often had a budget to experiment with. I think you're looking now the customers, the buyer technologies are looking for a hard ROI, like a return on investment. And before think they might experiment more, but now they're saying, Hey, are you gonna help me save money or increase revenue or some hardcore metric that they care about? So I think, um, the startups that actually have a strong ROI, like save money or increased revenue and can like point empirically how they do that will, will, you know, rise to the top of, of the MarTech landscape. And customers will see that they're they're, the customers are smart, right? They're savvy buyers. They, they, they, they, they can smell good from bad and they're gonna see the strong >>ROI. Yeah. And the other thing too, I like to point out, I'd love to get your reaction real quick is a lot of the companies have DNA, any open source or they have some community track record where communities now, part of the vetting. I mean, are they real good people? >>Yeah. I, I think open stores, like you said, in the community in general, like especially all these communities that move on slack or discord or something else. Right. I think for sure, just going through all those forums, slack communities or discord communities, you can see what's a good product versus next versus bad. Don't go to like the other sites. These communities would tell you who's working. >>Well, we got a discord channel on the cube now had 14,000 members. Now it's down to six, losing people left and right. We need a moderator, um, to get on. If you know anyone on discord, anyone watching wants to volunteer to be the cube discord, moderator. Uh, we could use some help there. Love discord. Uh, Jerry. Great to see you. Thanks for coming on. What's new at Greylock. What's some of the things happening. Give a quick plug for the firm. When you guys working on, I know there's been some cool things happening, new investments, people moving. >>Yeah. Look we're we're Greylock partners, seed series a firm. I focus at enterprise software. I have a team with me that also does consumer investing as well as crypto investing like all firms. So, but we're we're seed series a occasionally later stage growth. So if you're interested, uh, FA me@jkontwitterorjgreylock.com. Thank you, John. >>Great stuff, Jerry. Thanks for coming on. This is the Cube's presentation of the, a startup showcase. MarTech is the series this time, emerging cloud scale customer experience where the integration and the data matters. This is season two, episode three of the ongoing series covering the hottest cloud startups from the ADWS ecosystem. Um, John farrier, thanks for watching.

>>Okay, welcome back. Everyone's Cube's coverage here in Las Vegas for Amazon re Mars machine learning, automation, robotics, and space out. John fir host of the queue. Got a great set of guests here talking about AI, Jason Montgomery CTO and co-founder man and Ryans CEO, founder guys. Thanks for coming on. We're just chatting, lost my train of thought. Cuz we were chatting about something else, your history with DataRobot and, and your backgrounds entrepreneurs. Welcome to the queue. Thanks >>Tur. Thanks for having >>Us. So first, before we get into the conversation, tell me about the company. You guys have a history together, multiple startups, multiple exits. What are you guys working on? Obviously AI is hot here as part of the show. M is Mars machine learning, which we all know is the basis for AI. What's the story. >>Yeah, really. We're we're here for two of the letters and Mars. We're here for the machine learning and the automation part. So at the high level, man is a no code AI application development platform. And basically anybody could log in and start making AI applications. It could be anything from just texting it with the Twilio integration to tell you that you're doing great or that you need to exercise more to integrating with zenes to get support tickets classified. >>So Jason, we were talking too about before he came on camera about the cloud and how you can spin up resources. The data world is coming together and I, and I like to see two flash points. The, I call it the 2010 big data era that began and then failed Hadoop crashed and burned. Yeah. Then out of the, out of the woodwork came data robots and the data stacks and the snowflakes >>Data break snowflake. >>And now you have that world coming back at scale. So we're now seeing a huge era of, I need to stand up infrastructure and platform to do all this heavy lifting. I don't have time to do. Right. That sounds like what you guys are doing. Is that kind of the case? >>That's absolutely correct. Yeah. Typically you would have to hire a whole team. It would take you months to sort of get the infrastructure automation in place, the dev ops DevOps pipelines together. And to do the automation to spin up, spin down, scale up scale down requires a lot of special expertise with, you know, Kubernetes. Yeah. And a lot of the other data pipelines and a lot of the AWS technologies. So we automate a lot of that. So >>If, if DevOps did what they did, infrastructure has code. Yeah. Data has code. This is kind of like that. It's not data ops per se. Is there a category? How do you see this? Cuz it's you could say data ops, but that's also it's DevOps dev. It's a lot going on. Oh yeah. It's not just seeing AI ops, right? There's a lot more, what, what would you call this? >>It's a good question. I don't know if we've quite come up with the name. I know >>It's not data ops. It's not >>Like we call it AI process automation >>SSPA instead of RPA, >>What RPA promised to be. Yes, >>Exactly. But what's the challenge. The number one problem is it's I would say not, not so much all on ever on undifferent heavy lifting. It's a lot of heavy lifting that for sure. Yes. What's involved. What's the consequences of not going this way. If I want to do it myself, can you take me through the, the pros and cons of what the scale scope, the scale of without you guys? >>Yeah. Historically you needed to curate all your data, bring it together and have some sort of data lake or something like that. And then you had to do really a lot of feature engineering and a lot of other sort of data science on the back end and automate the whole thing and deploy it and get it out there. It's a, it's a pretty rigorous and, and challenging problem that, you know, we there's a lot of automation platforms for, but they typically focus on data scientists with these large language models we're using they're pre-trained. So you've sort of taken out that whole first step of all that data collection to start out and you can basically start prototyping almost instantly because they've already got like 6 billion parameters, 10 billion parameters in them. They understand the human language really well. And a lot of other problems. I dunno if you have anything you wanna add to that, Ryan, but >>Yeah, I think the other part is we deal with a lot of organizations that don't have big it teams. Yeah. And it would be impossible quite frankly, for them to ever do something like deploy text, track as an example. Yeah. They're just not gonna do it, but now they can come to us. They know the problem they want solved. They know that they have all these invoices as an example and they wanna run it through a text track. And now with us they can just drag and drop and say, yeah, we want tech extract. Then we wanted to go through this. This is what we >>Want. Expertise is a huge problem. And the fact that it's changing too, right? Yeah. Put that out there. You guys say, you know, cybersecurity challenges. We guys do have a background on that. So you know, all the cutting edge. So this just seems to be this it, I hate to say transformation. Cause I not the word I'm looking for, I'd say stuck in the mud kind of scenario where they can't, they have to get bigger, faster. Yeah. And the scale is bigger and they don't have the people to do it. So you're seeing the rise of managed service. You mentioned Kubernetes, right? I know this young 21 year old kid, he's got a great business. He runs a managed service. Yep. Just for Kubernetes. Why? Because no, one's there to stand up the clusters. >>Yeah. >>It's a big gap. >>So this, you have these sets of services coming in now, where, where do you guys fit into that conversation? If I'm the customer? My problem is what, what is my, what is my problem that I need you guys for? What does it look like to describe my problem? >>Typically you actually, you, you kind of know that your employees are spending a lot of time, a lot of hours. So I'll just give you a real example. We have a customer that they were spending 60 hours a week just reviewing these accounts, payable, invoices, 60 hours a week on that. And they knew there had to be a better way. So manual review manual, like when we got their data, they were showing us these invoices and they had to have their people circle the total on the invoice, highlight the customer name, the >>Person who quit the next day. Right? >>No like they, they, Hey, you know, they had four people doing this, I think. And the point is, is they come to us and we say, well, you know, AI can, can just basically using something like text track can just do this. And then we can enrich those outputs from text track with the AI. So that's where the transformers come in. And when we showed them that and got them up and running in about 30 minutes, they were mind blown. Yeah. And now this is a company that doesn't have a big it department. So the >>Kind, and they had the ability to quantify the problem >>They knew. And, and in this case it was actually a business user. It was not a technical >>In is our she consequence technical it's hours. She consequences that's wasted. Manual, labor wasted. >>Exactly. Yeah. And, and to their point, it was look, we have way more high, valuable tasks that our people could be doing yeah. Than doing this AP thing. It takes 60 hours. And I think that's really important to remember about AI. What're I don't think it's gonna automate away people's jobs. Yeah. What it's going to do is it's going to free us up to focus on what really matters and focus on the high value stuff. And that's what people should >>Be doing. I know it's a cliche. I'm gonna say it again. Cause I keep saying, cause I keep saying for people to listen, the bank teller argument always was the big thing. Oh yeah. They're gonna get killed by the ATM machine. No, they're opening up more branches. That's right. That's right. So it's like, come on. People let's get, get over that. So I, I definitely agree with that. Then the question, next question is what's your secret sauce? I'm the customer I'm gonna like that value proposition. You make something go away. It's a pain relief. Then there's the growth side. Okay. You can solve from problems. Now I want this, the, the vitamin you got aspirin. And I want the vitamin. What's the growth angle for you guys with your customers. What's the big learnings. Once they get the beach head with problem solving. >>I think it, it, it it's the big one is let's say that we start with the account payable thing because it's so our platform's so approachable. They go in and then they start tinkering with the initial, we'll call it a template. So they might say, Hey, you know what, actually, in this edge case, I'm gonna play with this. And not only do I want it to go to our accounting system, but if it's this edge case, I want it to email me. So they'll just drag and drop an email block into our canvas. And now they're making it >>Their own. There is the no code, low code's situation. They're essentially building a notification engine under the covers. They have no idea what they're doing. That's >>Right. They get the, they just know that, Hey, you know what? When, when like the amount's over $10,000, I want an email. They know that's what they want. They don't, they don't know that's the notification engine. Of >>Course that's value email. Exactly. I get what I wanted. All right. So tell me about the secret sauce. What's under the covers. What's the big, big, big scale, valuable, valuable, secret sauce. >>I would say part of it. And, and honestly, the reason that we're able to do this now is transformer architecture. When the transformer papers came out and then of course the attention is all you need paper, those kind of unlocked it and made this all possible. Beyond that. I think the other secret sauce we've been doing this a long time. >>So we kind of, we know we're in the paid points. We went to those band points. Cause we weren't data scientists or ML people. >>Yeah. >>Yeah. You, you walked the snow and no shoes on in the winter. That's right. These kids now got boots on. They're all happy. You've installed machines. You've loaded OSS on, on top of rack switches. Yeah. I mean, it's unbelievable how awesome it's right now to be a developer and now a business user's doing the low code. Yep. If you have the system architecture set up, so back to the data engineering side, you guys had the experience got you here. This is a big discussion right now. We're having in, in, on the cube and many conversations like the server market, you had that go away through Amazon and Google was one of the first, obviously the board, but the idea that servers could be everywhere. So the SRE role came out the site reliability engineer, right. Which was one guy or gal and zillions of servers. Now you're seeing the same kind of role with data engineering. And then there's not a lot of people that fit the requirement of being a data engineer. It's like, yeah, it's very unique. Cause you're dealing with a system architecture, not data science. So start to see the role of this, this, this new persona, because they're taking on all the manual challenges of doing that. You guys are kind of replaced that I think. Well, do you agree with it about the data engineer? First of all? >>I think, yeah. Well and it's different cuz there's the older data engineer and then there's sort of the newer cloud aware one who knows how to use all the cloud technologies. And so when you're trying, we've tried to hire some of those and it's like, okay, you're really familiar with old database technology, but can you orchestrate that in a serverless environment with a lot of AWS technology for instance. And it's, and that's hard though. They don't, they don't, there's not a lot of people who know that space, >>So there's no real curriculum out there. That's gonna teach you how to handle, you know, ETL. And also like I got I'm on stream data from this source. Right. I'm using sequel I'm I got put all together. >>Yeah. So it's yeah, it's a lot of just not >>Data science. It's >>Figure that out. So its a large language models too. We don't have to worry about some of the data there too. It's it's already, you know, codified in the model. And then as we collect data, as people use our platform, they can then curate data. They want to annotate or enrich the model with so that it works better as it goes. So we're kind of curating, collecting the data as it's used. So as it evolves, it just gets better. >>Well, you guys obviously have a lot of experience together and congratulations on the venture. Thank you. What's going on here at re Mars. Why are you here? What's the pitch. What's the story. Where's your, you got two letters. You got the, you got the M for the machine learning and AI and you got the, a for automation. What's the ecosystem here for you? What are you doing? >>Well, I mean, I think you, you kind of said it right. We're here because the machine learning and the automation part, >>But >>More, more widely than that. I mean we work very, very closely with Amazon on a number of front things like text track, transcribe Alexa, basically all these AWS services are just integrations within our system. So you might want to hook up your AI to an Alexa so that you could say, Hey Alexa, tell me updates about my LinkedIn feed. I don't know, whatever, whatever your hearts content >>Is. Well what about this cube transcription? >>Yeah, exactly. A hundred percent. >>Yeah. We could do that. You know, feed all this in there and then we could do summarization of everything >>Here, >>Q and a extraction >>And say, Hey, these guys are >>Technicals. Yeah, >>There you go. No, they mentioned Kubernetes. We didn't say serverless chef puppet. Those are words straight, you know, and no linguistics matters right into that's a service that no one's ever gonna build. >>Well, and actually on that point, really interesting. We work with some healthcare companies and when you're basically, when people call in and they call into the insurance, they have a question about their, what like is this gonna be covered? And what they want to key in on are things like I just went to my doctor and got a cancer diagnosis. So the, the, the relevant thing here is they just got this diagnosis. And why is that important? Well, because if you just got a diagnosis, they want to start a certain triage to make you successful with your treatments. Because obviously there's an >>Incentive to do time. That time series matters and, and data exactly. And machine learning reacts to it. But also it could be fed back old data. It used to be time series to store it. Yeah. But now you could reuse it to see how to make the machine learning better. Are you guys doing anything, anything around that, how to make that machine learning smarter, look doing look backs or maybe not the right word, but because you have data, I might as well look back at it's happened. >>So part of, part of our platform and part of what we do is as people use these applications, to your point, there's lots of data that's getting generated, but we capture all that. And that becomes now a labeled data set within our platform. And you can take that label data set and do something called fine tuning, which just makes the underlying model more and more yours. It's proprietary. The more you do it. And it's more accurate. Usually the more you do it. >>So yeah, we keep all that. I wanna ask your reaction on this is a good point. The competitive advantage in the intellectual property is gonna be the workflows. And so the data is the IP. If this refinement happens, that becomes intellectual property. Yeah. That's kind of not software. It's the data modeling. It's the data itself is worth something. Are you guys seeing that? >>Yeah. And actually how we position the company is man team is a control plane and you retain ownership of the data plane. So it is your intellectual property. Yeah. It's in your system, it's in your AWS environment. >>That's not what everyone else is doing. Everyone wants to be the control plane and the data plan. We >>Don't wanna own your data. We don't, it's a compliance and security nightmare. Yeah. >>Let's be, Real's the question. What do you optimize for? Great. And I think that's a fair, a fair bet. Given the fact that clients want to be more agile with their data anyway, and the more restrictions you put on them, why would that this only gets you in trouble? Yeah. I could see that being a and plus lock. In's gonna be a huge factor. Yeah. I think this is coming fast and no one's talking about it in the press, but everyone's like run to silos, be a silo and that's not how data works. No. So the question is how do you create siloing of data for say domain specific applications while maintaining a horizontally scalable data plan or control plan that seems to be kind of disconnected everyone to lock in their data. What do you guys think about that? This industry transition we're in now because it seems people are reverting back to fourth grade, right. And to, you know, back to silos. >>Yeah. I think, well, I think the companies probably want their silo of data, their IP. And so as they refine their models and, and we give them the ability to deploy it in their own stage maker and their own VPC, they, they retain and own it. They can actually get rid of us and they still have that model. Now they may have to build, you know, a lot of pipelines and other technology to support it. But well, >>Your lock in is usability. Exactly. And value. Yeah. Value proposition is the lock in bingo. That's not counterintuitive. Exactly. Yeah. You say, Hey, more value. How do I wanna get rid of it? Valuable. I'll pay for it. Right. As long as you have multiple value, step up. And that's what cloud does. I mean, think that's the thing about cloud. That's gonna make all this work. In my opinion, the value enablement is much higher. Yeah. So good business model. Anything else here at the show that you observed that you like, that you think people would be interested in? What's the most important story coming out of the, the holistic, if you zoom up and look at re Mars, what's, what's coming out of the vibe. >>You know, one thing that I think about a lot is we're, you know, we have Artis here, humanity hopefully soon gonna be going to Mars. And I think that's really, really exciting. And I also think when we go to Mars, we're probably not gonna send a bunch of software engineers up there. >>Right. So like robots will do break fix now. So, you know, we're good. It's gone. So services are gonna be easy. >>Yeah. But I, oh, >>I left that device back at earth. I just think that's not gonna be good. Just >>Replicated it in one. I think there's like an eight >>Minute, the first monopoly on next day delivery in space. >>They'll just have a spaceship that sends out drones to Barss. Yeah. But I think that when we start going back to the moon and we go to Mars, people are gonna think, Hey, I need this application now to solve this problem that I didn't anticipate having. And in science fiction, we kind of saw this with like how, right? Like you had this AI on this computer or this, on this spaceship that could do all this stuff. We need that. And I haven't seen that here yet. >>No, it's not >>Here yet. And >>It's right now I think getting the hardware right first. Yep. But we did a lot of reporting on this with the D O D and the tactile edge, you know, military applications. It's a fundamental, I won't say it's a tech, religious argument. Like, do you believe in agile realtime data or do you believe in democratizing multi-vendor, you know, capability? I think, I think the interesting needs to sort itself out because sometimes multi vendor multi-cloud might not work for an application that needs this database or this application at the edge. >>Right. >>You know, so if you're in space, the back haul, it matters. >>It really does. Yeah. >>Yeah. Not a good time to go back and get that highly available data. You mean highly, is it highly available or there's two terms highly available, which means real time and available. Yeah. Available means it's on a dis, right? >>Yeah. >>So that's a big challenge. Well guys, thanks for coming on. Plug for the company. What are you guys up to? How much funding do you have? How old are you staff hiring? What's some of the details. >>We're about 45 people right now. We are a globally distributed team. So we hire every like from every country, pretty much we are fully remote. So if you're looking for that, hit us up, definitely always look for engineers, looking for more data scientists. We're very, very well funded as well. And yeah. So >>You guys headquarters out, you guys headquartered. >>So a lot of us live in Columbus, Ohio that's technically HQ, but like I said, we we're in pretty much every continent except in Antarctica. So >>You're for all virtual. >>Yeah. A hundred percent virtual, a hundred percent. >>Got it. Well, congratulations and love to hear that Datadog story at another time >>Or DataBot >>Yeah. I mean data, DataBot sorry. Let's get, get all confused >>Data dog data company. >>Well, thanks for coming on and congratulations for your success and thanks for sharing. Yeah. >>Thanks for having us for having >>Pleasure to be here. It's a cube here at rebars. I'm John furier host. Thanks for watching more coming back after this short break.

(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)

from the cube studios in palo alto in boston bringing you data driven insights from the cube and etr this is breaking analysis with dave vellante predictions are all the rage at this time of year now on december 29th 2020 in collaboration with eric porter bradley of enterprise technology research etr we put forth our predictions for 2021 and the focus of our prognostications included tech spending remote work productivity apps cyber security ipos specs m a data architecture cloud hybrid cloud multi-cloud ai containers automation and semiconductors we covered a lot of ground now over the past several weeks we've been inundated with literally thousands of inbound emails pitching us on various predictions and trends in these and other areas here's my predictions folder and this is only a portion of the documents that i've received by email obviously printed them out killed a few trees sorry hello and welcome to this week's wikibon cube insights powered by etr in this breaking analysis we're going to review briefly each of our predictions for this past year 2021 and suggest a grade as to how we did we're going to do this as a little warm up for our 2022 predictions which we'll be doing in the next over the next couple of weeks now before we dig in i want to make an observation many of the predictions that we received they were observations of trends and sometimes not really predictions or you know or not surprising we got a lot of self-serving marketing statements you know predictions in our view they should be measurable so you can look back and say okay did they get it right now granted there are gray areas so that's why we'll use a grading system today now there are also many really well done and thought-provoking predictions and there's an example of one that we received that is strong it's from equinix cio milan waglay who said within the decade data centers will be powered by a hundred percent renewable energy okay so you know that's clear and we can measure that but anyway thanks to all the pr folks who sent along like i said literally thousands of predictions we tried to read them all but the volume over the past week or so was just so overwhelming and we'll try to scan them before we do our 2022 predictions but today we want to do that warm up by evaluating how we did in 2021 so let's get started our first prediction was that tech spending would increase by four percent this year coming off of what we had thought was a contraction in 2020 and depending on which data you look at you know best case maybe was flat we definitely correctly called the continuation into 2022 of the remote work trend and the positive impact it would have on pcs and the like but we underestimated the shape of that rebound that that spend back curve idc has tech spending wrote this year at five and a half percent so we feel like while we called the bounce back it was more pronounced than we had thought in fact you know we think that idc number is probably going to go up even higher and we'll address that in our 2022 predictions so so we'll give ourselves a b minus here okay next prediction was remote worker trends become fossilized settling in at an average of 34 percent by year end 2021. so on average 34 of the workers would be remote by the end of this year now you know we made the call but we missed delta no we missed omacrom we said 34 remote which would be 2x the historical norms now the etr data suggests it was 52 in september and it's probably going to be somewhere in the 40 to 45 range by by the end of this month into december and the thing is 75 of the workforce is probably still working either fully remote or in a hybrid model and hybrid work is probably going to be the dominant trend and we're going to have to revisit that framework or how we think about this whole structure and we'll do that again in our 2022 predictions so we'll give ourselves a c on that one we'll take some credit for the permanence of the trend but the percentage was well off the mark you know thanks to the variance as well as some cultural shifts that whole hybrid notion okay so hey not really a great start for eric and me but we rebound with the next one the productivity increases we said seen in 2020 will lead organizations to double down on the successes and certain productivity apps will benefit so to measure this we said let's take a look at the most recent quarterly earnings and gauge the revenue growth year on year as an indicator docusign was up 42 smartsheet who we also called up was up 46 in revenue twilio up 65 zoom growth was 35 down from 325 confirming our layup call the zoom growth would moderate it had nowhere to go but down and microsoft teams has never been more ubiquitous has never seen greater adoption with hundreds of companies having a hundred thousand or more users and thousands of companies with ten thousand users or more so we really feel like we nailed this one so we're gonna give us give ourselves an a plus okay so now on to cyber it's an area that we've been making calls in for a couple of years now and we're really pleased looking back here we said permanent shifts in cso strategies are going to lead to share shifts in network security now we said to give you more detail maybe that sounds like an easy one but we said specifically identity cloud security and endpoint security would continue to benefit and we specifically named crowdstrike octa zscaler and a few others that are targeting their growth rates now gartner has the security market growing at 11 percent octa and zscaler revenues last quarter grew at 62 percent year over year crowdstrike 63 illumia we also called out they raised 225 million dollars on a 2.75 billion valuation on the strength of its growth that was in september now akamai acquired guardiocor for 600 million dollars another company we called out that they would do it they did that as a ransomware protection play and they paid a huge revenue multiple for the company and it seems the guys listed on the last line are all talking about subscriptions sas arr remaining performance obligations or rpo so we feel very good about this look back we'll take an a on this one no it's not an a plus because we're too conservative on the growth of octa crowdstrike and zscaler topping at 50 they they blew that away by another 10 points or so 10 to 15. but look pretty good call nonetheless okay again the next one you might feel like is a layup but not really so we said the increased tech spend would drive even more ipos spax and m a according to spac analytics ipos were up 109 this year the spac attack continued up 109 percent in 2021 on top of a record 2020 and according to kpmg m a dollar volume was up 19 okay you might say uh that was easy call but there was much more underneath this prediction we called out uipass ipo which was a lock but also said automation anywhere would go public uipath did aa didn't we did correctly call the hashicorp ipo we said they'd either get go ipo or get acquired and cloud flare grew revenue 219 percent last quarter but akamai was not acquired so the degree of difficulty on the overall prediction wasn't high but the automation anywhere in akamai events we made those calls that didn't happen and those were you know obviously tougher calls so we think this still deserves a b grade all right as you know data is one of our favorite subjects and we've reported extensively in the successes and failures of so-called big data we said next in the next prediction that in the 2020s 75 percent of large organizations will re-architect their big data platforms and we said this would occur you know in earnest over the next four to five years now again you may say duh dave but you have to evaluate the prediction based on the underlying comments here the jury is still out on things like snowflakes data cloud but we absolutely believe that it's the right direction but then you have then you have data bricks coming in taking a different approach they're coming at the problem from a data science angle trying to take on traditional bi and then you get snowflake coming from the analytics space and moving into ai and data science and you know we asked at aws aws re invent we asked benoit dejaville on the cube if there needs to be a semantic layer to bring these two worlds together and he said yes and that's what he claims snowflake is building meanwhile you got the big whales like oracle they continue to invest in their capabilities to try to eliminate data movement and then there's aws taking a totally different approach to data where it gives customers maximum optionality of offerings and database and other services and you can't forget microsoft and google so many customers might not take the steps that we predicted because they're comfortable where they are specifically we're talking about here a shift toward domain ownership and data product thinking and the reorganization of hyper-specialized technical teams many of the principles put forth by data mesh and we've said this change is going to take a number of years to play out four to five years so we start noticing in 2021 that that's clearly been the case as we reported on parts of jpmorgan chase uh rethinking its data architecture hellofresh and many others so this is still an incomplete the professor we'll give ourselves an incomplete on this one but we think it's trending in the right direction okay the next one is always fun discussion that's the battle to define hybrid and multi-cloud we said that's going to escalate in 2021 and we'll create bifurcated cio strategies now here we go aws sees the world as bringing its apis and primitives and model to the edge and the data center to aws is just another edge node and the company says that in still believes in the fullness of time that all data will be in the cloud however that's defined and aws awareness would say all this talk about hybrid of connecting on-prem to a cloud they would flat out say adam silipsky told us this that's not cloud is what he said then on the other side of the table you have the likes of cisco dell hpe etc saying hold on cloud is an operating model it's not a place and aws might say yeah and aws along with its customers is defining that operating model and these other guys would say no actually you're not we are with our customers and this battle 100 percent escalated in 2021 with the launch of apex by dell hp e double down on green lake cisco's as the service models and then of course oracle which actually announced a true same same public to on-prem hybrid capability two years before aws announced outpost and of course oracle's executing on that strategy in earnest in 2021 and the other nuance here is a concept that we introduced called super cloud which refers to the notion that look something like for example multi-cloud is not about running within a respective cloud it's not about cloud compatibility rather it's about abstracting the complexity of the underlying cloud primitives and building value on top of those cloud services on top of the investments in capex that the hyperscalers have made now some people didn't like the term super cloud maybe uber cloud would be a better term we're going to continue to use it to describe this capability we think it has meaning and we're seeing new examples like goldman sachs's financial cloud running on top of aws so a super cloud is not as an application or a suite of applications running on a single cloud now if those applications span multiple clouds like like snowflake is trying to do okay that's a service that could span multiple clouds or in the case of goldman sachs it's a portfolio of data tools and software that's made accessible as a service that floats on top of a single or even multiple clouds regardless we feel that this was a correct call given the evidence and we'll give ourselves an a minus taking points off for the somewhat anecdotal and observational measurement system that we apply to look back at this prediction okay the next prediction was we made was cloud containers ai and ml automation uh are gonna power that those big four are gonna power 2021 spending here's a graphic we use to predict that it plots survey data for the various technologies within the etr taxonomy net score or spending momentum on the vertical axis and market share or presence in the data set it's a pervasive measurement on the horizontal axis the one that matters here is the vertical that dotted line of 40 percent anything above that is considered highly elevated and these four areas have held served this year based on recent etr survey data that we're not showing here we'll we'll bring that into our 2022 prediction so this prediction came in correctly for the most recent survey data and that's our measurement system on this one so we're going to take an a for this one too now on the penelope ultimate prediction here we came back to automation saying that the automation mandate accelerates in 2021 uipath and automation anywhere we said would go public but microsoft remains a threat to these pure play rpa vendors well we gave ourselves a b on this one doubling down on automation anywhere going public you know that was wrong but we definitely saw this year companies leaning hard into automation and microsoft despite the fact that it doesn't have as feature rich a product and offering as uipath and automation anywhere microsoft remains a very large presence you know we spoke to a lot of customers at the uipath forward four event in october in las vegas physical event and they confirmed you know this is true but at the same time so they're using power automate from microsoft but also using in this case uipath so they've kind of confirmed that yeah it's not the same we use that for some of our productivity we're an azure customer it's easy for us but they're still leaning heavily and investing heavily into uipath and i think the same can be said for automation anywhere but autom but power automate shows up as a big time leader in the magic gartner magic quadrant so it can't be ignored but clearly the two leaders in rpa have a sizable product advantage relative to the legacy software players now if you look at the comment on pega systems they cooled off a bit as measured by their stock price their revenue grew 13 percent last quarter on a year-on-year basis but perhaps we overestimated the tailwind effect and the company's momentum so we'll take a b on this prediction correct call on the automation trend and the big software vendors piling in ibm et cetera but the chance we took on automation anywhere again was a miss so we'll dig ourselves on that and our last prediction for 2021 was 5g rollouts push new edge iot workloads and necessitate new system architectures now much of this prediction you can see in the underlying bullets here really related to the observation that arm was dominating at the edge it would find its way into the mainstream enterprise workloads and we've been asking a lot of the mainstream you know companies the oems you know what do you what do you see with with arm in the enterprise and they say yeah we don't see it yet but very clearly this came into focus in 2021 is aws announced graviton 3 now and new inference and new training silicon these are different types of workloads that are emerging in the enterprise these are all based on arm microsoft google alibaba oracle and others are now shipping or readying arm-based systems for the enterprise when you look at new storage network and security appliances and other systems they're very offering and often including arm-based processors to assist with the offloads and look intel is definitely under product under pressure as we've predicted many times not just in our predictions post even pat gelsinger has admitted this is a turnaround it's going to take at least five years that's kind of new and recent data that he's made public so we're going to take an a minus on this one we're going to take off some points for the fact that you know 5g rollouts in edge are evolving and this is a longer term trend but the underlying points that we made on this slide are still pretty solid now if we use the following scale where a plus is a hundred out of a hundred a minus is a 90 a b is an 85 a b minus is an 80 and a c is a 75 out of 100 and we exclude that incomplete prediction on data architectures we average out to an 87.8 so that's a solid b plus and so the professor in us said hey little yellow sticky good effort as most of the predictions could be quantified and or you know we tried to object objectively score them there were some layups in there so yeah maybe we'll try to take more risks uh you know or not you know we we we'll see we like winning and so you know you always have to couch some of these things with some obvious ones but but really try to give some detail underneath that's maybe non-obvious um and we'll try to keep it down in the legs we did this year to one or two multi-year predictions so what's next well eric bradley and i were working on our 2022 predictions we're going to release those in the next couple of weeks so stay tuned for that you know what do you think how did we do you know we're grading ourselves here love to know you know for we're off base on base we're too hard on ourselves too easy give us your feedback don't forget these episodes are all available as podcasts wherever you listen all you do is search breaking analysis podcast check out etr's website at etr dot plus remember we also publish a full report every week on wikibon.com and siliconangle.com you can always get in touch with email david.velante at siliconangle.com you can dm me at divalante or comment on our linkedin posts this is dave vellante for the cube insights powered by etr have a great week everybody stay safe be well we'll see you next time [Music] you

(bright upbeat music) >> Hello everyone. And we're back at AWS Re:Invent. You're watching theCUBE and we're here, day two. Actually we started Monday night and we got wall-to-wall coverage. We going all the way through Thursday, myself. I'm Dave Volante with the co-host, David Nicholson. Lisa Martin is also here. Of course, John Furrier. Partners, technologists, customers, the whole ecosystem. It's good to be back in the live event. Of course we have hybrid event as well a lot of people watching online. Anshu Sharma is here. He is the co-founder and CEO of Skyflow, new type of privacy company, really interested in this topic. Great to see you. Thanks for coming on. >> Thank you, thanks for bringing me here. >> It's timely, you know. Privacy, security, they're kind of two sides of the same coin. >> Yes. >> Why did you found Skyflow? >> Well, the idea for Skyflow really comes from my background in some ways. I spent my first nine years at Oracle, six years at Salesforce. And whether we were building databases or CRM products, customers would come to us and say, "Hey, you know, I have this very different type of data. It's things like social security numbers, frequent flyer card numbers, card numbers. You know, can you secure it better? Can you help me manage things like GDPR?" And to be honest, there was never a clear answer. There's a lot of technology solutions out there that do one thing at a time, you can walk around the booths here, there's like a hundred companies. And if you use all those hundred things correctly, maybe you could go tell your board that maybe a social security number is not going to be lost anymore. And I was like, "You know, we've simplified everything else. Why is it so hard to protect my social security number? It should be easy. It should be as easy as using Stripe or Twilio." And this idea just never went away and kept coming back till a few years ago, we learned about the Facebook privacy challenges, the Equifax challenges. And I was like, boy, it's the time. It's time to go do it now. >> You started the company in 2019. Right? >> Yes. >> I mean, your timing was pretty good, right? So what are the big sort of Uber trends that you're seeing? Obviously GDPR, the California Consumer Privacy Act. I heard this morning. Did you hear this? That like, if you post a picture on social media now without somebody's permission, you're now violating their privacy. It's like, you can see the smiles on Anshu's face. >> Its like every week, we're like every week, there's a new story that could be like, well, Skyflow. The new story is the question, the answer is Skyflow. But honestly I think what's happened is, the issue is put very simple. You know all we're trying to do is protect people's social security numbers, phone numbers, credit card numbers, things we hold dear. At the same time, it's complex. Like what does it mean to protect your social security number let's say? Does that mean I don't get to use it for filing your taxes? Well, I need your credit card number to process a payment. And we were like, this is just too complicated. Why, how do companies like Apple do it? How do companies like Netflix manage not have as many breaches as my hotel that barely has any data. And the answer is those companies actually have evolved to a completely different architecture, the zero trust data architecture. And that was our inspiration for starting this company. >> Yeah. I mean. How many times have you been asked to give your social security number? And you're like, why? why do you want it? What are you going to do with it? How do you protect it? And they go, "I don't know." >> You know, what's even, my favorite is like, you give your social security number to say TurboTax, how many days of the year do they need to use it? One. How many days of the year do they have it? And the thing is, it's a liability for those CTOs too. >> Yeah right. >> The CTO of Walgreens, the CTO of Intuit. They don't really want that social security number just so they can process your card once a year, or your social security number once a year. It's almost like we're forcing them to hold onto data. And then they have to bear the burden of having these stories. Like, you know, everybody wants to prevent a New York Times story that says, what Robin Hood had a breach, Twitter had a breach. >> So walk us through how Skyflow would address something like that. So take the, you know, take the make a generic version of TurboTax, social security members. There they are right now, they're sitting in a database somewhere. Hopefully there's some security wrapped around it in some way or another. What would you advise a customer like that to do? And what are you actually doing for them? >> So, look, it's very simple. You are not going to put your username passwords in a generic database. You're going to use something like OD Zero or Octa to do it. We're living in a world where we have polyglot data stores. Like there's a key value store. There's a time series database. There is a search database like Elastic. There's a log database like Splunk. But PII data, Somehow we think just fine. If it's in a hundred places and our answer is that we should do the same thing that companies like Apple, Netflix, Google, everybody, does. They take this data. They completely isolate it from the databases. And it gets stored in a custom data store in our case, that would be Skyflow. And essentially we'd give you encrypted tokens back and you can use these encrypted tokens that look like fake social security number. It's called a Format Preserving Encryption. So if you think about all the breakthroughs we've had in homomorphic encryption, on secure elements, like the way your phone works, the credit card number is stored in a secure element. So it's the same idea. There's a secure part of your data stack, which is Skyflow. That basically keeps the data always protected. And because we can compute and search on encrypted data, this is important, everybody can encrypt data at rest. Skyflow is the first company that's come out and said, "Look, you can keep your phone number and social security number, encrypted while I can run an aggregation query." So I can tell you what's the balance of your customer's account balance. And i can run that query without decrypting, a single row of data. The only other company I know that can do that internally is a certain Cupertino based company. >> So think about it. Anybody can walk something up to a certain degree, but allowing frictionless access at the same time. >> While it's encrypted. So how do you make that? Are you, is a strategy to make that a horizontal service? That I can put into my data protection service or my E-commerce service or whatever. >> It's a cloud-based service that runs on AWS and other clouds. We basically given instance just like, you'll get an instance of a post-grad store or you get an API handled to OD Zero. You basically instantiate Skyflow of what gets created. It can be in your AWS environment, dedicated VPC. So it's private to you and then you have a handle and then basically you just start using it. >> So how, how do you, what's the secret sauce? How do you do that? >> The secret source. Well, now that we filed the patents on it, I can reveal the secret sauce. So the holy grail of encryption right now, if you go talk to people at a leading company, is there's something called Fully Homomorphic Encryption. That's fundamentally the foundation on which things like Bitcoin are built actually. But the hard part about Fully Homomorphic Encryption is it works. You can actually do mathematical computations on it without decrypting the data, but it's about a million times slower. >> Yes slower, right. >> So nobody uses it. My insight was that we don't need to do multiplications and additions on phone numbers. You never take my phone number and divide by your social security number. (Dave laughing) These numbers are not numbers, they are data structures. So our insight was if you treat them as specialized data structures, we're all talking about basically about 80 different types of data across the globe. Every human being has an ID, date of birth, height, color of eyes. There's not that many fields. What we can do then is create specialized encryption schemes for each data type. We call this polymorphic data encryption. Poly means multiple. As a result of that, we can actually store the data encrypted and build indexes on it. Since we can index interpret data, it's kind of like, imagine you can run real-time queries on data that's encrypted. Every other data store, When you encrypt the data, it becomes invisible to database. And that's why we had to build this as a full stacked service. Just like the Snowflake guys had to start with the foundation of storage, rethink indexing, and build Snowflake. We did the same thing, except we built it for encrypted indexes Whereas they built it for encrypted, for regular data stores. >> So thinking, if you think about today's tech stack, it's evolving, right? The data protection and security are coming together. Where does this fit? Is it sort of now becoming a fundamental part of the-- >> We think every leading company, whether you're building a new brokerage application or you are the largest bank in the world, and we're talking to some of them right now. They're all going to have an internal service called a PII wall. This wall just like Apple and Google have their own internal walls. You're going to have a wall service in your service oriented architecture, essentially. And it's going to basically be the API. Every other application and database in your company is not going to store my social security number. The SSNs don't belong in 600 databases at a leading bank. They don't belong inside your customer support system. Think about what happened with Robinhood two weeks ago, right? Someone tricked one call center guy into giving the keys up, which is fine happens. But why did the call center guy have access to like a million email addresses? He's never used going to use that. So we think if you isolate the PII, every leading company is going to end up with a PII Wall, as part of their core architecture. Just like today, we have an Alt API, you have a Search API, you have a Logging API, you're going to have a PII API. And that's going to be part of your modern data stack. >> So okay. So this is definitely not a bolt on, right? It's going to be a fundamental company, just like security is, just like backup is. It's now, you got to have it. It's-- >> Yes. I mean, if you think about it, it just logically makes sense. Like you should be isolating this data. You don't keep your money and gold around at home. You put it either in a locker or a bank. I think the same applies for PII. We just haven't done it because companies would pay off a fine for $10,000 or a million dollars. And. >> Yeah. So you've recently raised $45 million to expand your efforts. Obviously that means that people are looking at this and saying there's opportunity, right? What does that look like when you think of growth, where during your go to market strategy at first you're convincing people that it's a good idea to do it. Do you think or hope for, hope one day that there's an inflection point where it's not that people are thinking, you know, let's do this because it's a good idea, but people are like, I have to do this because if I don't, it's irresponsible and I'm going to be penalized for not having it. It becomes something that isn't really a choice. It's something where you just do it. >> So, you know, when we were starting the company, we didn't even have a word to explain what we were trying to do. We would say things like what if there was a cloud service for XYZ. And, but over the last one year, I don't want to take credit for creating this market, but this market has been created in the last year and a half. And you know, we get tons of people, including some of the largest institutions emailing us, saying, "I'm looking to build a PII wall, API service inside my company. Can you tell me why your product meets that need?" And I thought that would take us three to five years to get there. And, you know, we've ended up creating a category, basically just like other companies have. And I think, you know, you don't get, I believe in market permission. You don't get to create a category. The market gives somebody the permission to create a category. Saying, "Look, this makes sense. Something like this should emerge." And if you're there at the right time, like you said. >> Yep. >> You get to take the opportunity. >> So where are you at as a company say for some, some capital is great. When do you scale? >> We're scaling now? So we just doubled our headcount in the last nine to 10 months. We're now 75 people. We think we'll be about 150 to 200 people in the next year. We are hiring across all regions. We just hired a head of Asia pack from segment.com. We just hired our first, you know, lead on international expansion. And in the US, we have an office in Palo Alto. We have an office in Bangalore. We just announced a data residency solution for Europe, data residency solution for India and emerging markets. Because data residency is another one of those things that's just emerging right now. And irrespective of whether you believe in security and privacy. Data residency is one of those things that you are mandated to implement. >> And where are you hiring? Is it combination to go to market? Tell me about your go to market. >> The go to market. We are direct sales organization, but we work with partners. So we haven't announced some of these partnerships, but you're working with some of the companies here who either are large database companies, large security companies. We think there is a win-win relationship between us and some of the partner. >> You're a partner model, partner channel model. >> So, direct sales but partner assisted. >> Yeah. Right. All right. We got to go. Hey, awesome story. Congratulations. Best of luck. >> Very interesting. >> Love to have you back and track the progress. >> Thank you, thank you so much. >> Okay. Thank you for watching theCUBE, the leader in and high-tech coverage. We're at Re-Invent 2021. Be right back (upbeat music)

(upbeat music) >> Welcome back, everyone, to theCUBE's live coverage, day one wrap-up. I'm John Furrier, with Dave Vellante. We have Jerry Chen, special guest who's been with us every year on theCUBE since inception. Certainly every AWS re:Invent, nine years straight. Jerry Chen, great to see you for our guest analyst's wrap up VC general partner, Greylock partners, good to see you. >> John, Dave, it's great to see you guys. Thanks for having me again. It wouldn't be re:Invent without the three of us sitting here and we missed last year, right, because of COVID. So we have to make up for lost time. >> John: We did a virtual one- >> Dave: we did virtual stuff= >> John: wasn't the same as in-person. >> Dave: Definitely not the same. >> Jerry: Not the same thing. So, it's good to see you guys again in person, and less than 6 feet apart. >> Cheers, yeah. >> And 7,000 people here, showing that the event's still relevant. >> Jerry: Yeah. >> Some people would kill for those numbers, it's a bad year for Amazon, down from 60,000. >> Jerry: Yeah. >> So, ecosystem's booming. Okay, let's get to it. Day one in the books, new CEO, new sheriff in town, his name's Adam Selipsky. Your take? >> Well, Adam's new, but he's old, right? Something, you know, like something new, something old, something blue, right? It's so, Adam was early Amazon, so he had that founding DNA. Left, you know, CEO of Tableau, acquired by Salesforce, came back few months ago. So I think it was a great move, because one, he's got the history and culture under Jassy, so he's definitely the Bezos Jassy tree of leadership, but yet he's been outside the bubble. Right? So he actually knows what it means to run a company not on the Amazon platform. So, I think Adam's a great choice to lead AWS for what we call it, like maybe act two, right? Act one, the first X years with Jassy, and maybe this is the second act under Adam. >> Yeah. And he's got- and he was very technical, hung around all the techies, James Hamilton, DeSantis, all the engineers, built that core primitives. Now, as they say, this cloud next gen's here, act two, it's about applications. >> Jerry: Yeah. >> Infrastructure as code is in place. Interesting area. Where's the growth come from? So, look, you know, the ecosystem has got to build these super clouds, or as you say, Castles on the Cloud, which you coined, but you brought this up years ago, that the moats and the value has to be in there somewhere. Do you want to revise that prediction now that you see what's coming from Selipsky? >> Okay, well, so let's refresh. Greylock.com/castles has worked out, like we did, but a lot of thought leadership and the two of you, have informed my thinking at Castles in the Cloud, how to compete against Amazon in the cloud. So you'd argue act one, the startup phase, the first, you know, X years at Amazon was from 2008 to, you know, 2021, the first X years, building the platform, digging the moats. Right? So what did you have? You have castle the platform business, economies of scale, which means decreasing marginal costs and natural network effects. So once the moat's in place and you had huge market share, what do you for act two, right? Now the moats are in place, you can start exploring the moats for I think, Adam talked about in your article, horizontal and verticals, right? Horizontal solutions up the stack, like Amazon Connect, CRM solutions, right? Horizontal apps, maybe the app layer, and verticals, industrials, financials, healthcare, et cetera. So, I think Jassy did a foundation of the castle and now we're seeing, you know, what Adam and his generation would do for act two. >> So he's, so there's almost like an act one A, because if you take the four hyperscalers, they're about, maybe do 120 billion this year, out of, I don't know, pick a number, it's many hundreds of billions, at least in infrastructure. >> Jerry: Correct. >> And those four hyperscalers growing at 35% collectively, right? So there's some growth there, but I feel like there's got to be deeper business integration, right? It's not just about IT transformation, it's about deeper- So that's maybe where this Connect like stuff comes, but are there enough of those? You know, I didn't, I haven't, I didn't hear a lot of that this morning. I heard a little bit, ML- >> Jerry: Sure. >> AI into Connect, but where's the next Connect, right? They've got to do dozens of those in order to go deeper. >> Either, Dave, dozens of those Connects or more of those premise, so the ML announcement was today. So you look at what Twilio did by buying Segment, right? Deconstruct a CRM to compete against Adam Selipsky's old acquire of Salesforce.com. They bought Segment, so Twilio now has communicates, like texting, messaging, email, but all the data come from Segment. >> Dave: With consumption-based pricing. >> With consumption-based pricing. So, right? So that's an example of kind of what the second act of cloud looks like. It may not look like full SaaS apps like Salesforce.com, but these primitives, both horizontally vertically, because again, what does Amazon have as an asset that other guys don't? Install based developers. Developers aren't going to necessarily build or consume SaaS apps, but they're going to consume things like these API's and primitives. And so you look around, what's cloud act two look like? It may not be VM's or containers. It may be API's like Stripe and Billing, Twilio messaging, right? Concepts like that. So, we'll see what the next act at cloud looks like. And they announced a bunch of stuff today, serverless for the data analytics, right? So serverless is this move towards not consuming raw compute and storage, but APIs. >> What about competition? Microsoft is nipping at the heels of AWS. >> Dave: John put them out of business earlier today. [John and Dave Laugh] >> No, I said, quote, I'll just- let me rephrase. I said, if Amazon goes unchecked- >> Jerry: Sure. >> They'll annihilate Microsoft's ecosystem. Because if you're an ISV, why wouldn't you want to run on the best platform? >> Jerry: Sure. >> Speeds and feeds matter when you have these shifts of software development. >> Jerry: You want them both. >> So, you know, I mean, you thought about the 80's, if you were at database, you wanted the best processor. So I think this Annapurna vertical integrated stacks are interesting because if my app runs better and I have a platform, prefabricated or purpose-built platform, to be there for me, I'm going to build a great SaaS app. If it runs faster and it cost less, I'm going to flop to Amazon. That's just, that's my prediction. >> So I think better changes, right? And so I think if you're Amazon, you say cheaper, better, faster, and they're investing in chips, proprietary silicon to run better, faster, their machine learning training chips, but if you're Azure or Google, you got to redefine what better is. And as a startup investor, we're always trying to do category definition, right? Like here's a category by spin. So now, if you're Azure or Google, there are things you can say that are better, and Google argued their chips, their TensorFlow, are better. Azure say our regions, our security, our enterprise readiness is better. And so all of a sudden, the criteria "what's better" changes. So from faster and cheaper to maybe better compliance, better visibility, better manageability, different colors, I don't know, right? You have to change the game , because if you play the same game on Amazon's turf, to your point, John, it- it's game over because they have economies of scale. But I think Azure and Google and other clouds, the superclouds, or subclouds are changing the game, what it means to compete. And so I think what's going on, just two more seconds, from decentralized cloud, being Web 3 and crypto, that's a whole 'nother can of worms, to Edge compute, what Cloudflare are doing with R2 and storage, they're trying to change the name of the game. >> Well, that's right. If you go frontal against Amazon, you're got to get decimated. You got to move the goalposts for better. And I think that's a good way to look at it, Dave. What does better mean? So that's the question that's on the table. What does that look like? And I think that's an unknown, that's coming. Okay, back to the start-ups. Category definition. That's an awesome term. That to me is a key thing. How do you look at what a category is on your sub- on your Castles of the Cloud, you brought up how many categories of- >> Jerry: 33 markets and a bunch of submarkets, yeah. >> Yeah. Explain that concept. >> So, we did Castle in the Clouds where my team looked at all the services offered at Azure, Google, and Amazon. We downloaded the services and recategorized them to like, 30 plus markets and a bunch of submarkets. Because, the reason why is apples to apples, you know, Amazon, Google, Azure all have databases, but they might call them different things. And so I think first things first is, let's give developers and customers kind of apples to apples comparisons. So I think those are known markets. The key in investing in the cloud, or investing in general, is you're either investing in budget replacement, replacing a known market, cheaper, better database, to your point, or a net new market, right? Which is always tricky. So I think the biggest threat to a lot of the startups and incumbents, the biggest threat by startups and incumbents, is either one, do something cheaper, better in a current market, or find a net new market that they haven't thought about yet. And if you can win that net new market before the rest, then that's unbelievable. We call it the, you know, the blue ocean strategy, >> Dave: Is that essentially what Snowflake has done, started with cheaper, better, and now they're building the data cloud? >> Jerry: I think there's- it's evolution, correct. So they said cheaper, better. And the Castle in the Cloud, we talked about, they actually built deep IP. So they went a known category, data warehouses, right? You had Teradata, Redshift, Snowflake cheaper, better, faster. And now let's say, okay, once you have the customers, let's change the name of the game and create a data cloud. And it's TBD whether or not Snowflake can win data cloud. Like we talked about Rockset, one of my investments that's actually move the goalpost saying, oh, data cloud is nice, but real time data is where it's at, and Snowflake and those guys can't play in real time. >> Dave: No, they're not in a position to play in real time data. >> Jerry: Right. >> Dave: I mean, that's right. >> So again, so that's an example of a startup moving the goalpost on what previously was a startup that moved the goalpost on an incumbent. >> Dave: And when you think about Edge, it's going to be real-time AI inferencing at the Edge, and you're right, Snowflake's not set up well at all for that. >> John: So competition wise, how do the people compete? Because this is what Databricks did the same exact thing. I have Ali on the record going back years, "Well, we love Amazon. We're only on Amazon." Now he's talking multicloud. >> So, you know, once you get there, you kind of change your tune cause you've got some scale, but then you got new potential entrants coming in, like Rockset. >> Jerry: Correct. >> So. >> Dave: But then, and if you add up the market caps of just those two companies, Databricks and Snowflake, it's much larger than the database market. So this, we're defining new markets now. >> Jerry: I think there's market cap, especially Snowflake that's in the public market, Databricks is still private, is optimism that there's a second or third act in the database space left to be unlocked. And you look at what's going on in that space, these real-time analytics or real-time apps, for sure there's optimism there. But, but to John's point, you're right, like you earn the right to play the next act, but it's tricky because startups disrupt incumbents and become incumbents, and they're also victims their own success, right? So you're- there's technical debt, there's also business model debt. So you're victims of your own business model, victims of your own success. And so what got you here may not get you to the next phase. And so I think for Amazon, that's a question. For Databricks and Snowflake, that's a question, is what got them here? Can they play to the next act? And look, Apple did it, multiple acts. >> John: Well, I mean, I think I- [Crosstalk] >> John: I think it's whether you take shortcuts or not, if you have debt, you make it a little bit of a shortcut bet. >> Jerry: Yeah. >> Okay. That's cool. But ultimately what you're getting at here is beachhead thinking. Get a beachhead- >> Jerry: Correct. >> Get in the market, and then sequence to a different position. Classic competitive strategy, 101. That's hard to do because you want to win the beachhead- >> I know. >> John: And take a little technical debt and business model debt, cheat a little bit, and then, is it not fortified yet? So beachhead to expansion is the question. >> Jerry: That's every board meeting, John and Dave, that we're in, right? It's called you need a narrow enough wedge to land. And it is like, I don't want the tip of the spear, I want the poison on the tip of a spear, right? [Dave and John Laugh] >> You want, especially in this cloud market, a super focused wedge to land. And the problem is, as a founder, as investor, you're always thinking about the global max, right? Like the ultimate platform winner, but you don't get the right to play the early- the late innings if you don't make it out of the early innings. And so narrow beachhead, sharp wedge, but you got to land in a space, a place of real estate with adjacent tan, adjacent markets, right? Like Uber, black cars, taxi's, food, whatever, right? Snowflake, data warehouse, data cloud. And so I think the key with all startups is you'll hit some ceiling of market size. Is there a second ramp? >> Dave: So it's- the art is when to scale and how fast to scale. >> Right. Picking when, how fast, in which- which best place, it was tough. And so, the best companies are always thinking about their second or third act while the first act's still going. >> John: Yeah. And leveraging cloud to refactor, I think that's the key to Snowflake, was they had the wedge with data warehouse, they saw the position, but refactored and in the cloud with services that they knew Teradata wouldn't use. >> Jerry: Correct. >> And they're in. From there, it's just competitive IP, crank, go to market. >> And then you have the other unnatural things. You have channel, you have installed base of customers, right? And then you start selling more stuff to the same channel, to the same customers. That's what Amazon's doing. All the incumbent's do that. Amazon's got, you know, 300 services now, launching more this week, so now they have channel distribution, right? Every credit card for all the developers, and they have installed base of customers. And so they will just launch new things and serve the customers. So the startups had to disrupt them somehow. >> Well, it's always great to chat with Jerry. Every year we discover and we riff and we identify, in real time, new stuff. We were talking about this whole vertical, horizontal scale and kind of castles early on, years ago. And now it's happened. You were right. Congratulations. That's a great thesis. There's real advantages to build on a cloud. You can get the- you can build a business there. >> Jerry: Right. >> John: That's your thesis. And by the way, these markets are changing. So if you're smart, you can actually compete. >> Jerry: I think you beat, and to Dave's earlier point, you have to adapt, right? And so what's the Darwin thing, it's not the strongest, but the most adaptable. So both- Amazon's adapt and the startups who are the most adaptable will win. >> Dave: Where are you, you guys might've talked about this, where do you stand on the cost of goods sold issue? >> Jerry: Oh, I think everything's true, right? I think you can save money at some scale to repatriate your cloud, but again, Wall Street rewards growth versus COGS, right? So I think you've got a choice between a dollar of growth versus a dollar reducing COGS, people choose growth right now. That may not always be the case, but at some point, if you're a company at some scale and the dollars of growth is slowing down, you definitely have to reduce the dollars in cost. And so you start optimizing cloud costs, and that could be going to Amazon, Azure, or Google, reducing COGS. >> Dave: Negotiate, yeah. >> John: Or, you have no visibility on new net new opportunities. So growth is about new opportunities. >> Correct. >> If you repatriating things, there's no growth. >> Jerry: It's not either, or- >> That's my opinion. >> Jerry: COGS or growth, right? But they're both valid, definitely, so you can do both. And so I don't think- it's what's your priorities, you can't do everything at once. So if I'm a founder or CEO or in this case investor, and I said, "Hey, Dave, and John, if you said I can either save you 25 basis points in gross margin, or I can increase another 10% top line this year", I'm going to say increase the top line, we'll deal with the gross margin later. Not that it's not important, but right now the early phase- >> Priorities. >> Jerry: It's growth. >> Yeah. All right, Jerry Chen, great to see you. Great to have you on, great CUBE alumni, great guest analyst. Thanks for breaking it down. CUBE coverage here in Las Vegas for re:Invent, back in person. Of course, it's a virtual event, we've got a hybrid event for Amazon, as well as theCUBE. I'm John Furrier, you're watching the leader in worldwide tech coverage. Thanks for watching. (Gentle music)