(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: From around the globe, it's theCUBE! With digital coverage of IBM Think 2021. Brought to you by IBM. >> Well welcome everyone as theCUBE continues our IBM Think series. It's a pleasure to have you with us here on theCUBE. I'm John Walls, and we're joined today by Brian Loveys who is the Director of Offering Management for Customer and Employee Care Applications at IBM in the Data and AI Division. So, Brian, thanks for joining us from Ottawa, Canada. Good to see you today. >> Yeah, great to be here, John. And looking forward to the session today. >> Which, by the way, I've learned Ottawa are the home of the world's largest ice skating rink. I doubt we get into that today, but it is interesting food for thought. So, Brian, first off, let's just talk about the AI landscape right now. I know IBM obviously very heavily invested in that. Just in terms of how you see this currently in terms of enterprise adoption, what people are doing with it, and just how you would talk about the state of the industry right now. >> You know, it's a really interesting one, right? I think if you look at it, you know, different companies, different industries, frankly, are at different stages of their AI journey, right? I think for me personally, what was really interesting was, and we're all going through the pandemic right now, but last year with COVID-19 in the March timeframe, it was really interesting to see the impact, frankly, in the space that I play predominantly in around customer care, right? When the pandemic hit, immediately call centers, contact centers got flooded with calls, right? And so it created a lot of problems for organizations. But what was interesting to me is it accelerated a lot of adoption of AI to organizations that typically lag in technology, right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things, and trying to, you know, communicate out information. So it was really interesting to see those organizations, frankly, accelerate really, really quickly, right? And if you actually, you know, talk to those organizations now, I think one of the most interesting things to me in thinking about it and talking to them now is like, hey, you know, we can do this, right? AI is really not that complicated. It can be simplified, we can take advantage of it and all of those types of things, right? So I think for me, you know, I kind of see different industries at sort of different levels, but I think with COVID in particularly, you know, and frankly not just COVID, but even digital transformation alongside COVID is really driving a lot of AI in an accelerated manner. The other thing that I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right? There's a tremendous opportunity to innovate in this space. And I think we all know that, you know, data is continually being created every single day. And as more people become even more digitalized, there's more and more data being created. Like it's how do you start to harness that data more effectively, right, in your business every day. And frankly, I think we're just scratching the surface on it. And I think tremendous amount of opportunity as we move forward. >> Yeah, you really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disruptor, right, but in this case it was purely, or really largely environment, you know, that was driving this disruption, right, forcing people to make these adoption moves and transitions maybe a little quicker than they expected. Well, so because of that, because maybe somebody had to speed up their timetable for deployments and what have you, what kind of challenges have they run into then, where, because as you describe it, it's not been the more organic kind of decision-making that might be made sometimes, situation dictated it. So what have you seen in terms of challenges, you know, barriers, or just a little more complexity, perhaps, for some people who're just now getting into the space because of the environment you were talking about? >> I think a lot of this is like, you know, people don't know where to get started, right, a lot of the time, or how AI can be applied. So a lot of this is going to be about education in terms of what it can and cannot do. And then it all depends on the use cases you're talking about, right? So if I think about, you know, building out machine learning models and those types of things, right, you know, the set of challenges that people will typically face in these types of things are, you know, how do I, you know, collect all the data that I need to go build these models, right? How do I organize that data? You know, how do I get the skillsets needed to ultimately, you know, take advantage of all of that data to actually then apply to where I need it in my business, right? So a lot of this is, you know, people need to understand those concepts or those pieces to ultimately be successful with AI. And you know, what IBM is doing right here, and I'll kind of, this will be a key theme throughout this conversation today is, you know, how do you sort of lower the time to value to get there across that spectrum, but also, you know, frankly, the skills required along the way as well? But a lot of it is like, people don't know what they don't know at the end of the day. >> Well, let me ask you about your AI play then. A lot of people involved in this space, as you well know, competition's pretty fierce and pretty widespread. There's a deep bench here. In terms of IBM though, what do you see as kind of your market differentiator then? You know, what do you think sets you apart in terms of what you're offering in terms of AI deployments and solutions? >> No, that's a great question. I think it's a multifaceted answer, frankly. The first thing I'll kind of talk through a little bit, right, is really around our platform and our framework, right? We kind of refer to as our AI ladder, but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning a bit earlier, right? If you think about, you know, AI is really about supplying the right data into AI, and then being able to infuse it to where you need it to go, right? So to do that, you need a lot of the underlying information architecture to do that, right? So you need the ability to collect the data. You need the ability to organize the data. You need the ability to build out these models or analyze the data, right? And then of course you need to be able to infuse that AI wherever you need it to be, right? And so we have a really nice integrated platform that frankly can be deployed on any cloud, right, so we get the flexibility of that deployment model with that integrated platform. And if you think about it, we also have built, right, you know, sort of these industry-leading AI applications that sit on top of that platform and that underlying infrastructure, right? So Watson Assistant, right, our conversational AI which we'll talk probably a little bit more on this conversation, right? Watson Discovery focused on, you know, intelligent document processing, right, AI search type applications. We've got these sort of market-leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm, right, that continues to invest and funnel innovations into our product platform and into our product portfolio, right? I think many people are aware of Project Debater we took on some of the top debaters in the world, right? But research ultimately is very much tied, right, and even, you know, some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just- >> I'm sorry go ahead, please. >> Go ahead, sorry. >> No, no, you go, (laughs) I interrupted, you go ahead. >> Don't worry, I was just going to say, the other two things I'll say like, you know, I'm saying this right, but we've got a lot of sort of proof points in around it, right, so if you talk about the scale, right, the number of customers, the number of case studies, the number of references across the board, right, in around AI at IBM it is significant, right? And not only that, but we've got a lot of, sort of I'll say industry and third-party industry recognition, right? So think about most people are aware of sort of Gartner Magic Quadrants, right, and we're the leader almost across the board, right, or a leader across the board. So, you know, cloud AI developer service, insight engines, machine learning, go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well, if that makes sense. >> Yeah, sure does. You know, we hear a lot about conversational AI and, you know, with online chat bots and voice assistance, and a myriad applications in that respect. Let's talk about conversational right now. Some people think is a little narrow, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI element to what you're talking about at IBM and how that is coming into play. And perhaps is a pretty big growth sector in this space. >> Yeah, I think, again, I talk about scratching the surface, early innings, you'll see that theme a lot too. And I think this is another area around that, right? So, listen, let's talk about the broader side. Let's first talk about where conversational AI is typically applied, right? So you see it in customer service. That's the obvious place where I've seen the most deployments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. You can think about, you know, lead qualification for example, right. You know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions, how can I schedule console? All those things can be automated using, right, conversational AI, but organizations don't want these sort of points solutions across the customer journey. What they're ultimately looking for is a single assistant to kind of, you know, front that particular customer. So what if I do come on from a lead qual perspective, but really I'm not there for lead qual, I'm actually a customer, and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, right? So on the customer side where we see the conversational AI going is really sort of covering that whole gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine not just, you know, the website and the chat on the website, but also, right, across your messaging channels, across your phone, right? And not just that, but you also want to be able to have a really nice experience around, hey maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play, right? Maybe that's easier to sign up for a particular offer, or do some authentication, or whatever it might be, right? So to sort of be able to switch between the channels is really, really going to become more important in terms of a seamless experience as you do kind of go through it, right- >> So let's talk about customers- >> Oh, go ahead sir. >> Yeah, you talked about customers a little bit, and you mentioned case studies, but I hope we can get into some specifics, if you can give us some examples about people, companies with whom you've worked and some success that you've had in that respect. And I think maybe the usual suspects come to mind. I think about finance, I think about healthcare, but you said, "Hey buddy, but customer call issues, you know, service centers, that kind of thing would certainly come into play," but can you give us an idea or some examples of deployments and how this is actually working today? >> Oh, absolutely, right? So I think you were kind of mentioning, you were talking about sort of industries that are relevant, right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer side of it, right? So clearly in financial services, banks, insurance are clearly obvious ones. Telecommunication, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in, right? And so you'll see different use cases in those industries as well, right? So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to NatWest in Scotland. So they started out with customer service, right? So dealing with personal banking questions through their website. What's interesting, and you'll see this with a lot of these use cases is they will start small, right, with a single use case, but they'll start to expand from there. So for example, NatWest, right, they're starting with personal banking, but they're now expanding to other areas of the business across that customer journey, right? So that's a great example of where we've seen it. Cardinal Health, right, because we're not dealing with customers in terms of external customers, but dealing with internal customers, right, from an IT help desk standpoint. So it's not always external customers. Oftentimes, frankly, it can be employees, right? So they are using it through an IDR system, right? So through over the phone, right, so I can call, instead of getting that 1-800 number, I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their help desk. So, and they started really, really small, right? They started with, you know, simple things like password resets, but that represented a tremendous amount of volume that ultimately hit at their call centers. So NatWest is a great example. CIBC, another bank in Canada, Toronto, is a great example. And the nice thing about what CIBC is doing and they're a big, you know, we have four big banks here in Canada. What CIBC do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money, or all those types of things, or check your balance or whatever it might be. So putting a nice, simple interface on some of those common, transactional things that you would do with a bank as well. >> You know, before I let you go, I'd like to hit just a buzzword we hear a lot of these days, natural language processing, NLP. All right, so NLP, define that in terms of how you see it and how is it being applied today? Why does NLP matter, and what kind of differences is it making? >> Wow, natural language processing is a loaded term as a buzzword, I completely agree. I mean, listen, at the 50,000 foot level, natural language processing is really about understanding language, right? So what do I mean by that? So let's use the simple conversational example we just talked about. If somebody's asking about, you know, "I'd like to reset my password," right? You have to be able to understand, well what is the intent behind what that user is trying to do, right? They're trying to reset a password, right? So being able to understand that inquiry that user has that's coming in and being able to understand what the intent is behind it. That's sort of one key aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing, the importance of extracting certain things that you need to know. And again, using the conversational AI side, just for a minute, to give a simple example. If I said, "You know what, I need to reset my password." I know what the intent is, I want to reset a password, but, right, I don't know which password I'm trying to reset. Right, and so this is where sort of you have to be able to extract objects, and we call them entities a lot of the time and sort of the (indistinct) or lingo. But you got to be able to extract those elements. So, you know, I want to reset my ATM password. Great, right, so I know what they're trying to do, but I also need to extract that it's the ATM password that I'm trying to do. So that's one sort of key angle, natural language processing, and there's a lot of different AI techniques to be able to do those types of things. I'll also tell you though, there's a lot around the content side of the fence as well. So you can imagine how like a contract, right, and there were thousands of these contracts, and some of your terms may change. You know, how do you know, out of those thousands of contracts where the problems are, where I need to start looking, right? So another sort of key area of natural language processing is looking at the content itself, right? Can I look at these contracts and automatically understand that this is an indemnity clause, right? Or this is an obligation, right? Or those types of things, right, and being able to sort of pick those things out, so that I can help deal with those sort of contract-processing things. So that's sort of a second dimension. The third dimension I'll kind of give around this is really around, you can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and nouns, and those types of things, but maybe I want to know in an analytics use case with customers, you know, what is the sentiment and, you know, analyzing social media posts or whatever it might be, what's the sentiment that people have around my product or service. So natural language process, if you think about it at the real high level is really about how do I understand language, but there's a variety of sort of ways to do that, if that makes sense. >> Yeah, no sure, and I think there are a lot of people out there saying, "Yeah, the sooner we can identify exasperation (laughs) the better off we're going to be, right, in handling the problems." So, it's hard work, but it's to make our lives easier, and congratulations for your fine work in that space. And thanks for joining us here on theCUBE. We appreciate the time today, Brian. >> Thank you very much. >> You bet, Brian Loveys, he's talking to us from IBM, talking about conversational AI and what it can do for you. I'm John Walls, thanks for joining us here on theCUBE. (upbeat music) ♪ Dah, deeah ♪ ♪ Dah, dee ♪ (chimes ringing)

>>from >>Around the globe. It's the cube with digital coverage of IBM think 2021 brought to you by IBM >>Well welcome everyone is the cube continues or IBM Thanks series. It's a pleasure to have you with us here on the cube. I'm john walls and we're joined today by brian loves who is the director of offering management for customer and employee care applications in the at IBM in the data and AI division. So brian, thanks for joining us from Ottawa Canada, good to see you today. >>Yeah, great to be here john I'm looking forward to the session today >>which by the way I've learned Ottawa is the home of the world's largest ice skating rink. I doubt we'll get into that today, but it is interesting food for thought. Uh so brian first off, let's just talk about um the Ai landscape right now. I know IBM obviously very heavily invested in that uh just in terms of how you see this currently as in terms of enterprise adoption, what people are doing with it and and just how you would talk about the state of the industry right now, >>you know, it's a really interesting one, right? I think if you look at it, you know different companies, different industries frankly are at different stages of their Ai journey, right? Um I think for me personally what was really interesting was, and we're all going through the pandemic right now, but last year with covid 19 in the March timeframe, it was really interesting to see the impact, frankly in the space that I played predominantly in around customer care, right? When the pandemic hit immediately call centers, contact centres got flooded with calls, right? And so it created a lot of problems for organizations. But it was interesting to me is it accelerated a lot of adoption of ai to organizations that typically lag and technology. Right? So if you think about public sector, right, that was one area that got hit very, very hard with questions and those types of things and trying to communicate and communicate out information. So it was really interesting to see those organizations frankly accelerate really, really quickly, right? And if you actually talk to those organizations now, I think one of the most interesting things to me and thinking about it and talking to them now is like, hey, you know, we can do this right, AI is really not that complicated, it can be simplified, we can take advantage of it and all of those types of things. Right? So I think for me, you know, I kind of see different industries that sort of different levels, but I think with Covid in particularly, you know, and frankly not just Covid, but even digital transformation alongside Covid is really driving a lot of ai in an accelerated manner. The other thing I'll kind of I'll kind of talk to a little bit here is I still think we're very much in the early innings of this, right, there is a tremendous opportunity innovating in the space and I think we all know that you know data is continually being created every single day and as more people become even more digitalized, there's more and more data being created. Like how do you start to harness that data more effectively, right in your business every day? And frankly I think we're just scratching scratching the surface on it and I think tremendous amount of opportunity as we move forward. >>Yeah, he really is really raised an interesting point which I hadn't thought about in terms of, we think about disruptors, we think about technology being a disrupter, right? But in this case it was purely really, largely environment that was driving this disruption, right, forcing people to to make these adoption moves and transitions maybe a little quicker than they expected. So because of that, because maybe somebody had to speed up their timetable for deployments and what have you what what kind of challenges have they run into them? Where because, as you describe it, it's not been the more organic kind of decision making that might be made, sometimes situation dictated it. So what have you seen in terms of challenges, barriers or just a little more complexity perhaps for some people who are just not getting into the space because of the environment you were talking about? >>I think a lot of this is like people don't know where to get started, right, a lot of the time or how ai can be applied. So a lot of this is going to be a bad education in terms of what it can and cannot do, and then it all depends on the use cases you're talking about, right? So if I think about, you know, building a machine learning models and those types of things right? You know, this set of challenges that people will typically face in these types of things are, you know, how do I collect all the data that I need to go build these models? Right? How do I organize that data? Um you know, how do I get the skill sets needed to ultimately, you know, take advantage of all that data to actually then apply to where I needed in my business? Right, So a lot of this is, you know, people need to understand, you know, those concepts are those pieces um to ultimately be successful with AI and you know what IBM is doing right here and I'll kind of this will be a key theme through this conversation today, is how do you sort of lower the time to value, to get there across that spectrum, but also, you know, frankly the skills >>required along the way as >>well, but a lot of it is like people don't know what they don't know at the end of the day. Mhm. >>Well, let me ask you about about your AI play then, a lot of people involved in this space, as you well know, you know, competitions pretty fierce and pretty widespread, there's a deep bench here um in terms of IBM know, what do you see is kind of your market different differentiator then, you know, what what do you think set you apart in terms of what you're offering in terms of AI deployments and solutions? >>No, that's a great question. I think it's a multifaceted answer, frankly. Um the first thing I'll kind of talk through a little bit right, is really around our platform and our our framework, right? We could refer to as our air ladder, um but it's really an integrated, you know, sort of cohesive platform for companies around the journey to AI, right? So kind of what I was mentioning earlier, right? If you think about, you know, AI is really about supplying the right data into A I. And then being able to infuse it to where you needed to go. Right? So to do that, you need a lot of the underlying information architecture to do that, Right? So you need the ability to collect the data, you need the ability to organize the data, you need the ability to to build out these models, right? Or analyze the data and then of course you need to be able to infuse that ai wherever you need it to be. Right. And so we have a really nice integrated platform that frankly can be deployed on any cloud. Right? So we got the flexibility that deployment model with that in greater platform. And you think about it? We also have built right, you know, sort of these industry leading Ai applications that sit on top of that platform and that underlying infrastructure. Right? So Watson assistant, Right. Our conversational AI, which we'll talk probably a little bit more on this conversation. Right, Watson discovery focus on, you know, intelligent document processing, right. AI search type applications. We've got these sort of market leading applications that sit on top, but there's also other things, right? Like we have a very, very strong research arm right, that continues to invest and funnel innovations into our product platform and into our product portfolio. Right? I think many people are aware of project debater, we took on some of the top debaters in the world, right? But research ultimately is very much tied, right? And even some of the teams that I work with on the ground, we've got them tied directly into the squads that build these products, Right? So we have this really big strong research arm that continues to bring innovation around AI and around other aspects into that product portfolio. But it's not just go ahead, >>Please go ahead. three. No, no. You know, I interrupted you. Go ahead. >>No, I was just gonna say that the other two things, I'll say it like, you know, I'm saying this right, but we've got a lot of sort of proof points and around it. Right? So, if you talk about the scale right? The number of customers, the number of case studies, a number of references across the board, right? In around AI AT IBM It is significant, Right? Um, and not only that, but we've got a lot of sort of, I'll say industry and third party industry recognition. Right? So think about most people are aware of sort of Gartner magic quadrants, right? And we're the leader almost across the board, Right? Or a leader across the board. So cloudy I developer service inside engines, machine learning go down the line. So, you know, if you don't trust me, there's certainly a lot of third party validation around that as well. That makes sense. >>Yeah, it sure does. You know, we're hearing a lot about conversational AI and, you know, with online chat bots and voice assistance and a myriad applications in that respect. Let's talk about conversational right now. Some people think it's little narrow, but, but yet there appears to be a pretty broad opportunity at the same time. So let's talk about that conversational AI um, uh, element um, to what you're talking about at IBM and how that is coming into play and, and perhaps is a pretty big growth sector in this space. >>Yeah, I think again, I talked about scratching the surface early innings. You'll see that theme a lot too. And I think this is another area around that. So listen, let's talk about the broader side. Let's first talk about where conversation always typically applied. Right? So you see it in customer service, that's the obvious place we're seeing the most appointments in. But if you think about, it's not just really around customer service, right? There's use cases around sales and marketing. If you think about, you know, lead qualification, for example, right? How can, you know, I'm on a website, how can I get information about a product or service? How can I automate some of that information collection, answering questions? How can I schedule console? All those things can be automated using great conversationally. I, the organizations don't want these sort of point solutions across the customer journey. What we're ultimately looking for is a single assistant to kind of, you know, front right, that particular customer. So what if I do come on from a legal perspective, but really I'm not here for legal. I'm actually a customer and I want to get a question answered, right? You don't want to have these awkward starts and stops with organizations, Right? So on the customer side where we see the conversation like, hey, I going and it's really kind of covering that full gambit in terms of that customer journey, right? And it's not just the customer journey, but you also want to be across channels, right? So you can imagine right now, not just, you know, the website and the chat on the website, but also right across their messaging channels, right across your phone. Right. And not just that, but you also want to be a really nice experience around, hey, maybe I'm on a phone call with some automation, but I need to be able to hand them off to a digital play. Right? Maybe that's easier to sign up for a particular offer or do some authentication or whatever might be, right. So to sort of be able to sort of switch between the channels, it's really, really going to become more important in this sort of sort of seamless experience as you just kind of go through it. Right? >>So you're coming by customers. Yeah. >>You talked about customers a little bit and you mentioned case studies, but can we get, I hope we can get into some specifics. You can give us some examples about people, companies with whom you've worked and and some success that you've had that respect. And I think maybe the usual suspects come to mind about finance. I might health care, but you said anybody with customer call issues, service centers, that kind of thing would certainly come into play. But can you give us an idea or some examples of deployments and how this is actually working today? >>Oh, absolutely. Right. So I think you kind of mentioned you become sort of industries that are relevant. Right? So, you know, the ones that I think are most relevant that we've seen are the ones with the biggest sort of consumer sort of side to it. Right? So clearly in financial services, banks, insurance, and clearly obvious ones telecommunications, retail, healthcare, these are all sort of big industries with a lot of sort of customers coming in. Right? So you'll see different use cases in those industries as well. Right. So the obvious one, we've got a really good client, Royal Bank of Scotland, they've now changed their name to natwest Open Scotland. Um So they started out with customer service. Right? So dealing with personal banking questions through their website, what's interesting and you'll see this with a lot of these use cases is they will start small, right with a single use case that they'll start to expand from there. So, for example, >>natwest right there, starting with they started with personal banking, but they're not expanding to other areas of the business across that customer journey. Right. So it's a great example of where we've seen it. Cardinal Health Right. We're not dealing with customers in terms of external customers but dealing with internal customers right from the help that standpoint. So it's not always external customers. Oftentimes frankly it can be employees. Right? So they are using it right through an I. V. R. System. Right? So through over the phone. Right. So I can call instead of getting that 1 800 number. I'm going to get a nice natural language experience over the phone to help employees with common problems that they have with their health does so. And they started really, really small, right? They started with simple things like password resets but that represented a tremendous amount of volume but ultimately headed their cost cost centers. So not West is a great example. C I B C. Another bank in Canada Toronto is a great example and the nice thing about what CNBC is doing and there are big, you know, we have four big banks here in Canada, what have you seen do is really focusing a lot on the transactional side. So making it really easy to do interact transfers or send money or over those types of things or check your balance or whatever it might be. So putting a nice simple interface on some of those common transactional things that you >>would do with the bank as well, >>you know, before I let you go, uh I'd like to hit this of buzz where we hear a lot of these days natural language processing. NLP Alright, so, so NLP define that in terms of how you see it and and how is it being applied today? Why why does NLP matter? And what kind of difference is it making? >>Wow, that's a loaded natural language processing. There's a loaded term in a buzzword. I completely agree. I mean listen, at the 50,000 ft level, natural language processing is really about understanding length, Right? So what do I mean by that? So let's use the simple conversational example. We just talked about if somebody is asking about, I'd like to reset my password right? You have to be able to understand what is the intent behind what that user is trying to do right there? Trying to reset a password, right? So being able to understand that inquiry that the user has that's coming in and being able to understand what the intent is behind it. >>That's sort of one, you know, aspect of natural language processing, right? What is the intent or the topic around that paragraph or whatever it might be. The other sort of key thing around natural language processing the importance, extracting certain things that you need to know. And again using the conversational ai side, just for a minute to give a simple example if I said you know what I need to reset my password, I know what the intent is. I want to reset a password but Right I don't know which password I'm trying to reset. Right? So this is where you have to be able to extract objects and we call them entities a lot of time in sort of the ice bake or lingo but you've got to be able to extract those elements. So you know I want to reset my A. T. M. Password. Great. Right so I know what they're trying to do but I also need to extract that it's the A. T. M. Password that I'm trying to do. So that's one sort of key angle of natural language processing and there's a lot of different techniques to be able to do those types of things. I'll also tell you though there's a lot around the content side of the fence as well, right? So you can imagine having a contract, right? And there are thousands of these contracts and some of your terms may change. How do you know, out of those thousands of contracts where the problems are, where I need to start looking, Right? So another sort of keep key area of natural language processing is looking at the content itself. Can I look at these contracts and automatically understand that this is an indemnity clause, Right? And this is an obligation, right? Or those types of things, right? And be able to sort of pick pick those things out so that I can help deal with those sort of contract processing things. That's sort of a second dimension. The third dimensional kind of kind of give around this is really around. You can think about extracting things like sentiment, right? So we talked about, you know, extracting objects and downs and those types of things. But maybe I want to know and analytics use case with customers. Um you know, what is the sentiment and you know, analyzing social media posts or whatever it might be. What's the sentiment that people have around my product or service? So naturally this process, if you think about it, the real high level is really about how do I understand language? But there's a variety of sort of ways to do that if that makes sense? >>Yeah, sure. And I think there's a lot of people out there saying, yeah, the sooner we can identify exasperation, the better off we're going to be right and handling the problems. But it's hard work but it's to make our lives easier and congratulations for your fine work in that space. And thanks for joining us here on the cube. We appreciate the time. Today, brian, >>thank very much. >>You bet BRian Levine is talking to us from IBM talking about conversational Ai and what it can do for you. I'm john Walsh, thanks for joining us here on the cube. Mhm. >>Mhm.

(upbeat techno music) >> Announcer: From New York City, it's theCUBE, covering New Relic FutureStack 2019, brought to you by the New Relic. >> Hi, I'm Stu Miniman and this is theCUBE's exclusive coverage of New Relic's Futurestack 2019 here in New York City, seventh year of the show. Our first year here, about 600 or so in attendance, and real excited, because we've had some of the users here to help kick off our coverage. And joining us, first time guest on the program, Josh Biggely is a senior engineer of Enterprise Monitoring, with Cardinal Health coming to us from a little bit further north and east than I do, Prince Edward Island, thank you so much for coming here to New York City and joining me on the program. >> Yeah, thanks for having me Stu, I'm excited to be here. I haven't been in New York, it's probably been more two decades. So it's nice to be back in a big city, I live in a very small place. >> Yeah, so if you go to Times Square, it's now Disneyland, is what we call it. It's not the 42nd street that it might've been a couple of decades ago. I grew up about 45 minutes from here, so it's gone through a lot, love the city, especially gorgeous weather we're having here in the fall. >> I'm excited for it. >> All right, so Josh, Cardinal Health, health is in the name so we think we understand a little bit about it, but tell us a little bit about the organization itself and how it's going through changes these days. >> Sure, so Cardinal Health is a global healthcare solutions provider. We are essential to care, which means we deliver the products and solutions that your healthcare providers need to literally cure disease, keep people healthy. So we're in 85% of the hospitals in the United States, 26,000 pharmacies, about 3,000,000 different home healthcare users receive products from us. Again we're global, so we're based in Dublin, Ohio, just outside of Columbus. But obviously, I live in Canada so I work for the Cardinal Health Canada Division. We've got acquisitions around the world. So yeah, it's an exciting company. We've recently gone through a transformation not only as a company, but from a technology side where we've shifted one of our data centers entirely into the cloud. >> All right, and Josh, your role inside the company, tell us a little bit about, you said it's global, what's under your purview? >> So my team is responsible for Enterprise Monitoring, and that means that we develop, deploy, support and integrate solutions for monitoring both infrastructure applications and digital experience for our customers. We have a number of tools, including New Relic, that we use. But it's a broad scope for a small team. >> Stu: Okay, and you've talked about that transformation. Walk us through a little bit about that, what led to, as you said, some big moves into public cloud? >> Yeah, our team is part of an overall effort to allow Cardinal Health to be more adaptive, to be more agile. The move to cloud allows teams that are developing applications and platforms to make a decision how to respond to the needs of their customers more rapidly. Gone are the days of, "I need a new server, "I need to predict six months from now "that I'm going to need a new server, "put the order in, get it delivered, "get it racked, get it wired." We watch a lot of people, the provision on demand. I mean, our senior vice president, or my senior vice president, likes to say, "I want you to fail fast, fail cheap." He does not say fail often. Although sometimes I do that, but that's okay. As long as you recognize that you're failing and can roll that back, redeploy, It's been really transformative for my team in particular, who was very infrastructure focused when I started with the company five years ago. >> Stu: All right, and can you bring us inside from your application portfolio, was it a set of applications, was it an entire data center? What moved over, how long did it take, and can you share what cloud you're using? >> Sure, so it's been about a two year journey. We're actually a multicloud company. We've got a small footprint in Azure, small footprint in AWS, but we're primarily in Google Cloud. We are shutting down one data center, we are minimizing another data center, and we've moved everything. We've moved everything from small bespoke applications that are targeted on team to entire ecommerce platforms and we've done everything from lift and shift, which I know you don't like to hear. But we've done lift and shift, we've done rehosting, we've done refactoring and we have re-architected entire platforms. >> Yeah, so if you could expand a little bit when we say lift and shift, I'm fine with lift and shift as long as there's another word or plan after that which I'm expecting you do have. >> Josh: Yeah, absolutely. So the lift and shift was, "Hey, let's move from our data centers into GCP. "Let's give teams the visibility, the observability "that they need so that they can make the decisions on "what they need to do best." In a lot of cases, or in fact, in 15% of the 6,500 severs that we touch, we actually full out decommed the instance. Teams had them, they were running at our data centers but they weren't actually providing any value to the company. >> So you said your team before was mostly concerned about infrastructure and a lot of what you did is now on GCP so you fired the entire team and you hired a bunch of PhDs to be able to manage Google environments? >> Absolutely not. (laughter) The principals of enterprise monitoring as a practice still apply in a cloud. We are, at heart, data geeks. And I would fair say that we're actually data story tellers. Our job is to give tools and methodologies to application teams who know what the data means in context, but we give the tools to provide that data to them. >> Stu: All right, love that. I believe I've actually seen data geek shirts at the the New Relic shows itself. But data story tellers, that was kind of thing that you heard, "I have a data scientist "that's going to help us to do this." Is that data scientist in New York or are you actually enabling who is able to tell those data stories today? >> So that is the unique part. Data story telling is not a data science. I wish that I could be a data scientist, I like math, but I'm not nearly that good at it. A data story teller takes the data and the narrative of the business, and weaves them together. When you tell someone, "Here's some data." They will look at it and they will develop their own narrative around it. But as a story teller you help craft that narrative for them. They're going to look at that data and they're going to feel it, They're going to understand it and it's going to motivate them to act in a way that is aligned with what the business objectives are. So data story tellers come in all forms. They come as monitoring engineers, they're app engineers, but they're also people who are facing the customer, they're business leaders, they're people in our distribution centers who are trying to understand the impacts of orders in their order flow, in their personnel that they have. It is a discipline that anyone can engage in if we're willing to give them the right tools. >> All right, so Josh, you got rid of a data center, you're minimizing a data center, you're shifting to cloud, you're making a lot of changes and now being able to tell data stories. Can you tell us organizationally everything goes smoothly or are their anythings that you learned along the way that maybe you could share with your peers to help them along that journey? And any rough spots, with hindsight being what it is, that you might be able to learn from? >> Yeah, so hindsight definitely 20/20. The one thing that I would say to folks is get your data right. Metadata, trusting your data is key, it's absolutely vital. We talk a lot about automation and automation is one of those things that the cloud enables very nicely. If you automate on garbage data, you are going to automate garbage generation. That was one of our struggles but I think that every organization struggles with data fidelity. But teams need to spend more time in making sure that their data, specifically their metadata, around, "Hey is this prod, is it non-prod, "what stack is this running, who built it?" Those things definitely need to be sorted out. >> Okay, talk about the observability and the monitoring that you do, how long have you been using New Relic and what products? And tell us a little about that journey. >> Sure, so we've been using New Relic for about two years. It was a bit of a slow run up to its adoption. We are a multi-tool company so we have a number of tools. Some of them are focused primarily on our network infrastructure, our on-prem storage. Although Cardinal had moved predominantly to the cloud, we have distribution centers, nuclear pharmacies all around the world. And those facilities have not gone into the cloud. So you've got network connectivity. New Relic for us has filled our cloud niche and observability, as Lou announced, is going to give us context to things that we're after. You hear the term dark data, we call them obs logs. It's data that we want to have, we only need it for a very short period of time to help us do post-op or RCAs as well as to look at, overall in our organization, the performance of the applications. For us, New Relic is going to give us an option to put data for observability. Observability is really about high fidelity data. In its world of cloud, everyone wants everything right now. And they also want it down to the millisecond. A platform that can pull that off, that's a remarkable thing. >> Yeah, Veruca Salt had it right, "I want it now." So are you using New Relic One yet? >> We have been using New Relic One for at least a couple of months going back into March this year. It's exciting, we're one of those companies that Lou talked about in his key note, we have hundreds of sub accounts. And we did so very intentfully, but it was a bit of a nightmare before we got to New Relic One. That ability for a platform team to see across multiple sub accounts, really powerful. >> Okay, so you saw a lot of announcements this morning. Anything particular that jumped out, you were excited? Because Lou kept saying over and over, and if you're using New Relic One, "This is free, this is free, this is free." That platform where it's all available for you now. >> I think the programmability is one of the things that really got me excited. One of the engineers on my team had a chance to go and sit with Lou and team, two weeks ago, and was part of that initial Hackathon. Made some really interesting things. That's exciting so shout out to Zack and the work he did. Logging, for me, is something that is huge. I know we've got data that we should have in context. So that Lou announced five terabytes of ingestion for free, all I could do was tap my fingers together and think, "Oh, okay. You're asking for it, Lou. Challenge accepted." (laughter) >> Stu: That's exciting, right. So you feel that you're going to be building apps, it sounds like already, at the FutureHack. That you're starting to move down that path. >> Definitely, and I'm really excited. Not to necessarily give it to my team. We build the patterns for teams that needs patterns, but there are so many talented individuals at Cardinal Health who, if we give them the patterns to follow, they're just going to go execute. Open sourcing that is a brilliant idea and really crowd sourcing development is the way to go. >> Yeah, I think you bring up a really interesting point. So even though your team might be the one that provides the platform, you're giving that programmability, sensibility to a broader audience inside the team and democratizing the data that you have in there. >> Yes, you keyed in on one of the things I love to talk about which is democratized access to data. Over and over again you'll hear me preach that, "I know what I know but I also know what I don't know "and more particular I don't know what I don't know. "I need other people to help me recognize that." >> We've really talked about that buzzword out there about digital transformation. When it is actually being happened, it goes from, "Oh, somebody had an opinion," to, "Wait, I actually now can actually get to the data, "and show you the data and leverage the data "to be able to take good actions on that." >> That's right, data driven decision making is not just just an idiom. It's not something that is a buzzword, it is a practice that we all need to follow. >> Stu: All right, so Josh, you're speaking here at the show. Give our audience just a quick taste, if you will, about what you're going to be sharing with your peers here at the show. >> We've actually talked about a lot of it already so I hope that people are not going to watch this session before my session later. But it really is around the power of additional transformation, the power of observability, what happens when you do things right, and the way the cloud makes teams more nimble. I won't give you it all because then people won't watch my session on Replay but, yeah, it'll be good. >> Well, definitely they should check that out. I'm hoping New Relic has that available on Replay. Give the final word here, what you're really hoping to come out of this week. Sounds like your team's deeply engaged, you've done the Hackathon, you're working with the executive teams. So FutureStack 2019, what are you hoping to walk away with? >> For me, it's about developing patterns. My team, in addition to our enterprise architecture team, is responsible for mapping out what we're going to do and how we're going to do it. Teams want to go fast and if we're not going to lay down the foundation for them to move quickly, especially in the realm of enterprise monitoring, they're going to try do it themselves. Which may or may not work. We don't want to turn teams away from using specific tools if it fits, but if there's a platform that will allow them to execute and to keep all that data centralized, that is really the key to observability. Having that high fidelity data, but then being able to ask questions, not just of the data you put in, but the data that put in maybe by a platform team or by a team that supported Kubernetes or PCF. >> All right, well, Josh Biggely, thank you so much for sharing all that you've been going through in Cardinal Health's transformation. Great to talk to you. >> Thanks so much, Stu. >> All right, lots more here at New Relic's FutureStack 2019. I'm Stu Miniman and as always, thank you for watching theCUBE. (light techno music)

(upbeat music) >> Male Voiceover: Live, from San Diego, California it's theCUBE covering Cisco Live US 2019 brought to you by Cisco and its ecosystem partners. >> Hey welcome back to theCUBE Lisa Martin with Stu Miniman. We are day one of our coverage of Cisco Live from San Diego. We're going to be here for three days of coverage but a great day so far and we're pleased to welcome back one of our CUBE alumni Kent Christensen the Practice Director from Insight with the Cloud & Data Center at Transformation Group. Kent, welcome back! >> Thank you. It's been a little while. >> It has been a little while. So give our audience a little overview of Insight your partnership with Cisco and some of the history of how you got to Insight. >> Yeah so you remember us as Data Link we were a smaller company than we are now. Focusing on Cloud and data center transformation. We've talked at Dell events, CFC events things like that. But we were a Cisco partner for about 10 years and recently we were acquired and we did what the name sounds like, Cloud and data center transformation. We've talked about Cloud on the channel and all these other things. Insight acquired us. Insight has kind of four major service solution sets if you would. Some people look at them as a supply chain company and it's a great, large supply chain company. Microsoft's largest global partner. Some people understand it for the device and use the devices that's called Connective Workforce. Each of these are pretty big businesses you know, compared to where we are. What was Data Link is now what's called Cloud and Data Center Transformation. So we're helping people with the journey to the Cloud and the Hybrid Cloud and all that other stuff. And Cisco is right dead center in the middle of that and then the fourth one is really exciting. It's called Data and Digital Innovation and that's a couple of companies. Blue Metal, Cardinal etc. Again, a thousand people. Microsoft ILT and AI partner of the year. So all of that is a pretty large channel organization if you would. >> That's great stuff Kent. We love to talk to the channel as the folks in Wall Street do. It like you know, we do a channel check. Okay, You know, Cisco's got a few areas that have you know, stronger growth in the market over all. Security's doing well, a few other spaces on that are you know growing faster over all than the market and helping >> Kent: Absolutely >> grow where Cisco's going, so give us the reality. What's happening with your customers? What's driving you know the most growth in your business and you know, where is Cisco kind of leading the pack? >> So we're doing really well with Cisco and I don't know if it's because we're helping clients build solutions that truly lead to business outcomes. We're not order takers. So we're actually moving up we're now Cisco's fourth largest partner. We're growing well high single digits growth which is pretty phenomenal on such a big number. We're talking a billion dollars now in growing that level and there's a number of reasons. You know, some of it is there's a lot of great technology we can get into some of those. We see the economy as being pretty good not bad yet. You know everybody's worried about what might happen. You mentioned security, we can get into a little bit of that. That's driving a lot of network refresh and stuff like that. You know and a little bit of intra-company you know that word getting our stuff together so this large company with 15000 customers acquires a company with 2000 customers and now we're getting introduced into the 15000 with less friction. So that's helping us and that's helping our Cisco Business. >> Lisa: See here we are at Cisco Live. The thirtieth time that they had done a customer partner event. The network has not only changed dramatically since their first event in '89 which was called Networkers I believe. >> KENT: Yeah. >> But networking technology has also massively changed you mentioned security. And now in this multi-cloud world no longer can you just put a firewall around a data center right? Obviously that doesn't work. We have this core Cloud edge very amorphous environments. Proliferation of mobile, of mobile data traversing the networks. Talk to us about when you're talking with customers who need to transform their data centers where do you start from a networking conversation perspective? Where automation comes in, where security comes in? >> You know, a lot of the Cloud native transformation tends to be the edge of the network. You know conversion, infrastructure, stuff like that that's on the edge. The network security guys which I'm not, you know, I work with them very closely but we almost separate ourselves out from a data center networking and security. But security's end to end to your point, right? I've got software to find access. I've got mobile access points. I've got you know, Tetration. I've got all of these products that are helping people that in the past they were just patching holes in the dyke. You know, hey this happened let's put this software product in. This happened, let's put this in. We actually built a security practice like the last 3 or 4 years ago, it's growing. You know the number of people that are, whether it's regulation, compliance, you know. "I got some real problem. I think I've got a problem and I don't know what it is." Our ability to come back and sit down and say let's evaluate what your situation is. So I was talking to the networking guys and said wow. Enterprise networking's up, way up. What's driving that, the need to transform or is that, you know what is it? And they're like a lot of times it's something along security that's making them step back and re-evaluate and then sometimes that translates into an entire network refresh. >> Stu: So Kent you mentioned Cisco Tetration and that's one I've heard a number of times having some growth. What else, what are some of the you know hot products out there in your customer base? >> ISE, Software to Find, SD Wan, SD Access. >> Stu: Yeah, so one of the things I just want to understand Cisco actually has a few solutions in some of those areas. Any specific products that you call out or you know or that'd be mentioned? >> Kent: In the enterprise networking I wouldn't go through each and every individual one. I think, this is my view as the laymen right? 'Cause I'm the data center guy and here's the security guy and here's the networking guy. I think when Cisco started acquiring all these security companies 3 years ago and you know watched it and it looked like a patchwork quilt and said this stuff doesn't fit together? Now it fits together that story is really solid. And so we've got clients that had the luxury of either saying I'm going to do a refresh because I don't want to keep plugging holes and maybe my technology was ready for it anyway. And there's a lot of reasons to refresh right? My technology's due. Digital transformation, I need to get my network ready for IoT etc. But I keep hearing security over and over right? I've got compliance and regulations and all of this other stuff. >> Yeah but in your core space the data center world and any products that are kind of leading the charge right now? >> You know one of the things that's happening in data center from a Cisco perspective 'cause they're babies right? Ten years old in data center. They didn't really have data center before that. And we were there at the beginning and that's really how CDCT built our data center practice so you know when you talk multi-cloud at the end of the day even if I'm Cloud first I'm going to end up with some of these mission-critical workloads. They might be boring but they're running the company. They're not the innovative Dev-Ops, IoT, AI thing that seems cool. They're running the company and that's still a converged or a hyper-converged play. And some of those you know there's a lot of opportunities we've been talking about all day with the Cisco BU's. Some of those are ready for refresh right so there's a great opportunity to just to go in and say okay what's next? You know, we've added you know the latest server technology. We've added all these things in the server technology. Obviously all flash and the storage technologies and all of that so that's huge. And then you know Cisco continues to innovate in data center solutions with things like HyperFlex which we've talked a little bit about. And it started off a little slow because again just like they were in servers why are they here? Why are they in hyper-converge? So I get it. And now that product is fully improved and improved and improved and we're seeing tremendous growth there and I think the luxury they have on a data center solution is that some of the other guys have to do a or. "Hey, I'm the leading hyper-converge technology but it's me or everybody else." Right? And then Cisco's an end that I can connect those things together. >> So let's talk about some customer examples you can feel free to anonymize these. I'm seeing a smile on your face. When you come into an organization whether it's a 100 year old bank or it's a born of the Cloud or maybe a smaller more nimble organization that needs to undergo transformation data center transformation. What is the conversation like with respect to helping them take all of these disparate presumably disparate solutions? Whether they're 10-15 different security solutions. How does Insight come in and help them I don't want to say integrate but almost plug these things in together to extract value and help them make sure that what they're implementing from a technology perspective is necessary and also an accelerator of their business? >> Yeah, there's a lot there. So we have this... A year ago everybody wanted to talk about Cloud and then you had the security guys but now you have a lot of change agents with transformation in their title right? And so we have this belief. You're not going to digitally transform. Now there are people that are born digital but companies that were buying Cisco 10 years ago need to go through a digital transformation and you can't go through a digital transformation until you have a data center transformation or an IT transformation. So we've done studies. What slows people down? What makes these fail? Legacy stuff, security concerns I mean these are the top 3 things right. Budget. I was just running the company. And so we start there. Where do you want to get to? And then most of it is let's understand what you have. What your objectives are as an organization. "I want to get to this. I want to get to that." Well before we start talking about technologies. It's very, it's very services oriented. I can't just go in there and throw you a bomb and say this is going to fix your problem 'cause everybody's different. So it is very custom and very services oriented. >> Lisa: But you're saying... >> Stu: I was just going to say it's a pattern I've seen quite a bit for the last couple of years. Step 1 is modernize the platform and then step 2 you can worry about your data and application story on top of that in that multi-cloud world that you live in. >> And step 1 admit you have a problem. >> Yeah. >> (Lisa laughs) >> So we actually did a study you know we do this and we're like. Why does everybody keep stalling why have we been stuck in this nobody's refreshing things and stuff like that? Well there's a lot of new technology they don't get it. But you know do you want to digitally transform? Understand what you need to do. But we ask questions like rate your IT infrastructure just rate it B-minus. Across a lot of large companies that was the grade they gave themselves. So there's a lot of opportunity to say: Okay where do you want to be and where do we start? >> Yeah, 90 percent of people think they are above average drivers. So... >> Drivers? But they think they have a B-Minus in IT infrastructure and it's like Do you consider that a problem? >> Yeah. >> So once you as we wrap here in the next minute or so. Once you get them to admit yeah there's problems here that Insight and other partners come in and improve. Data center transformation, modernizing that infrastructure but it's got to be concurrent with starting to modernize and transform other areas right? >> Absolutely. So you know there's so many places you could start. Sometimes you just go and say well what's your appetite? Every once in a while you get somebody who's ready to go through an entire transformational process. You know 20 million dollars or more of whatever and we get those opportunities those are awesome. Now we get to start back and figure out where you want to be and how to get there most efficiently. A lot of people have to pick and choose. You know, what's your concern right now? And so we'll help them figure that out and again it could be security it could be you know how many people... We have over a thousand enterprise customers running Sequel 2008. That's a problem right? Because that's end of support within a year. That's a problem that's an opportunity. You know so they are still trying to figure out these things. And then a picture of where I want to get to. Which we've kind of always said and that's where that Digital Innovation Group they've got all these AI projects and as we sit here and talk about those things that are kind of born in the Cloud but they're coming towards the infrastructure. It was easy to get a GPU in the Cloud but I'm going to have to start... And so we have actually have all the latest Cisco technology and storage technology of AI stuff in our labs and stuff like that so there's a lot going on. Our CEO would say "It's a really exciting time to be in this business." >> It sounds like it! I wish we had more time to start digging through that but you'll have to come back Kent. >> Okay. >> Alright thanks for joining us. >> Yeah. Thank you. >> With Stu Miniman, I'm Lisa Martin. You're watching theCUBE live. Day 1 of our coverage of Cisco Live from San Diego. Thanks for watching.

>> Live from San Diego, California It's the queue covering Sisqo live US 2019 Tio by Cisco and its ecosystem, Barker's >> Hey, welcome back to the Cube. Lisa Martin with steam in a man's way are Day one of our coverage of Cisco lie from San Diego. We're gonna be here for three days of coverage, but a great day so far. And we're pleased to welcome back one of our Cube alumni, Kenny Christiansen, the practice director from Insight with the Cloud and Data Center transformation group. Kitt, welcome back. >> Thank you for a little while. >> It has been a little while. So give our audience a little overview of inside your partnership with Cisco and some of the history of how you got to Insite. >> Um, yeah, so you remember US. Data like way were smaller company than we are now. Focus on Cloud Davidson transformation. We've talked it della vincey and see events. Things like that way We're Cisco partner for about 10 years and recently we were acquired and we did with name sounds like cloud and Data Center transformation. We've talked about cloud in the channel and all these other things um inside acquired us Insight has kind of four major service solution sets, if you would. Some people look at them is a supply chain company, and it's a great large supply chain company, Microsoft Largest global partner. Some people understand it for the device in use devices that's called connected workforce. Each of these air pretty big businesses, you know, compared to what we are. What was Data link is now what's called Cloud David Senate transformation. Um, so we're helping people with the journey to the cloud and the hybrid cloud and all that other stuff. Francisco right, Dead center in the middle of that and then the 4th 1 is really excited to go diddle diddle innovation. And that's a couple of companies Blue Metal, Cardinal, etcetera again 1,000 people. Microsoft I'll Tee and aye, aye, partner of the year. So all of that is a pretty large channel organization. If you want. >> That's great stuff can. And we always. We love to talk to the channel as the folks on Wall Street to It's like you know we do. A channel check is okay. You know, Cisco's got a few areas that have, you know, stronger growth in the market overall, security's doing well. A few other spaces that are, you know, growing faster overall than the market helping grow where we're Cisco's going. So give us the reality. What's happening with your customers? What's driving, you know, since the most growth in your business. And you know where is where is Cisco kind of leading the pack? >> So we're doing really well a system, and I don't know if it's because we're helping clients build solutions that truly lied to business outcomes. We're not order takers, so we're actually moving up. We're now 54th largest partner. We're growing well, high single digits growth, which is pretty phenomenal and such a big number. We're talking $1,000,000,000 now and growing that level on DH. There's a number of reasons, you know, some of it is there's a lot of great technology and get into some of those way. See, the economy is being pretty good. Not bad. Yet you know everybody for it. Worried about what might happen. You mentioned security. We could get into a little bit of that. That's driving a lot of network refreshed and stuff like that. Um, you know, a little bit of Inter company, you know that we're getting our stuff together. So this large company with 15,000 customers, you know, acquires a company with 2,000 customers, and now we're getting introduced into the 15,000 with less friction. So that's helping us. And that's helping Francisco business. >> So here we are at Cisco Live, 30th time that they've done a customer partner. Event network has not only changed dramatically since their first event in 89 which was called networkers, I believe. But networking technology has also massively changed. You mentioned security, and now in this multi cloud world, no longer can you just put a firewall around Data Senate, right? Obviously, that the work we have, this core cloud edge very a Morpheus environments proliferation of mobile of mobile data traversing the network's talk to us about when you're talking with customers who need to transform their data centers. Where do you start from? A networking conversation perspective, where automation comes in where security comes in, >> you know, a lot of the cloud names. Their transformation says to me the edge of the network, you know, converts, infrastructure, stuff of that that's on the edge. The network security guys, which I'm not. You know, I work with them very closely, but there we almost separated, sells out from the data center. Networking security. But security's in the end to your point, right? I've got software to find access. I've got mobile access points I've got, you know, te Trae Shin. I've got you know, all of these products that are helping people that in the past they were just patching holes in the dyke, you know? Hey, this happened. Let's put this off for product. This happened. Let's put this in. We actually built a security practice like the last three or four years ago. It's growing. You know, the number of people that are, whether it's regulation compliance. You know, I got some real problem. I think I've got a problem and I don't know what it is. Our ability to come back and sit down and say, Let's evaluate what your situation is. So I was talking to the networking guys, so wow, enterprise network is up way up. What's driving that I need to transform or is that you know what isn't there like a lot of times it's something our long security that's making them step back and reevaluate. And then sometimes that draft transfer translates into entire network refresh. >> So you mess in Cisco te Trae Shin? That's one I've heard a number of times having some growth. What? What else? What are some of the, you know, hot products out there in your >> eyes based software to find FT. When hefty access. >> So one of the things I just don't understand Cisco actually has a few solutions and some of those areas any specific products that you call out or, uh, you know, the >> enterprising, that working I wouldn't go through each and every individual one. I think this is my view of the layman, right, Because I'm the data center guy and here's the security guy hears them working. Got I think Francisco started acquiring all these security companies three years ago and you watched it. It looked like a patchwork quilt and said, This doesn't fit together now. It fits together. That story is really solid. And so we've got clients that have had the luxury of either salmon. I'm going to do a refresh because I don't want to keep plugging hole, and maybe my technology was ready for it anyway because there's a lot of reasons to refresh right. My technology do digital transformation. I need to get my network ready for Io ti etcetera. But I keep hearing security over and over, right. I've got compliance and regulation and all of this other stuff. >> But in your core space, the data center world, you know, and any products that are kind of leading the leading the charge right now, >> you know, one of the things that's happening in data center from a Cisco perspective because their babies, right, 10 years old in data centers, they didn't really have data center before that we were there at the beginning. And that's really how CDC t built our David Senate practice. So you know, when you talk multi cloud at the end of the day, even if I'm cloud first, I'm going to end up with some of these mission critical work clothes. They might be boring the running the company right there, not the innovative Deva Coyote. I think that seems cool running the company, and that's still a converged or a hyper converse play. And some of those you know, there's a lot of opportunities. We've been talking about all day with the Sisko be used. You know, some of those are ready for refresh, right? So there's a great opportunity that's going and say, OK, what's next? You know, we've added, you know, the latest server technology. We've had all these things in the server technology, obviously all flashing the storage technologies in all of that. So that's you. And then, you know, Cisco continues to innovate in data center solutions with things like Hyper flex, which were, you know, talked a little bit about getting started off a little slow, because again, just like they weren't servers. Why are they here? Why are they in hyper converts like get it? And now that product has slowly improved and improved and improved, and we're seeing tremendous growth there. And I think luxury they have on a data center solution is that some of the other guys have to do. Ah or hey, I'm the leading hyper converts technology. But it's me or everybody else, right? Um, and then this goes in and write that I could connect those things together. >> So let's talk about some customer examples you can feel free to anonymous days. I'm seeing a smile on your face when you come into an organization, whether it's 100 year old bank or it's a one of the cloud orders, maybe a smaller, more nimble organization that needs to undergo transformation did isn't a transformation. What was the conversation like with respect to helping them take all of these disparate, presumably to sprint solutions, whether they're 10 15 different security solutions, how does insight come in and help them? I want to say integrate, but almost plug these things in together to extract value and help them make sure that what they're implementing, much technology perspective is necessary and also an accelerator of their business. >> Yeah, lose a lot there. So we have this, you know. So a year ago, everybody wanted to talk about Cloud, and then they had the security guys. But now you have a lot of change. Agents of transformation, their title right? And so we have this belief you're not going to digitally transform Now. There are people that are born digital, but companies that were buying Cisco 10 years ago need to go through a digital transformation, and you can't go through a digital transformation and tell you have a data center transformation, wherein I transformation. So we've done studies. What slows people down? What makes he failed legacy stuff? Security concerns. I mean, these are the top three things, right? Budget. I was just running the pretty and so we start there that says, Where do you want to get to? And then most of it is Let's understand what you have, what? Your objectives, ours, an organization. I want to get to this. I want to get to that Well, before we start talking about technologies and it's very it's very services or even write. I can't just go in there and throw your bomb and say, This is going to fix your problem because everybody's different. So it is very custom and very services, or >> you're saying >> I was just going to say It's a pattern I've seen quite a bit for the last couple of years is step one is modernized the platform and then step two. You can worry about your data and application story on top of that in that multi cloud world. >> Step one, admit you have a problem. Yeah. So we actually did a study? Yeah. You know, we do this All right? Well, why does everybody keep stalling? Why we've been stuck in this. Nobody's refreshing things and stuff like that. Well, there's a lot of new technology. They don't get it. But, you know, do you want a digitally transform? Understand what you need to do, but we ask questions like rate your infrastructure just raided B minus across a lot of large companies. That was what the grade they gave themselves. So there's a lot of opportunities. Say, Okay, where do you wanna be? Yeah, and where do we >> start? 90% of people think they are above average drivers, so >> drivers, but they think they have a B minus in infrastructure and is like to consider that a problem. >> So once you as we wrap here in the next minute or so, once you get them to admit, yeah, there's there's problems here that incite other partners come and come in and improve data center transformation, modernizing that infrastructure, but it's got to be concurrent, was starting to modernize and transform other areas, right? >> Absolutely so you know, there's so many places you could start. Sometimes you just go and say, Well, what's your appetite Every once in a while, you get somebody who's ready to go through an entire transformational process, you know, $20,000,000 arm or whatever, and we get those opportunities. Those are awesome. Now we get to start back and figure out where you want to be and how to get there most efficiently. A lot of people have to pick up juice. You know? What's your concern right now on DH? So we'll help them figure that out again. It could be security. It could be. You know how many people we have over 1,000 enterprise customers around X equal two thousand eight? That's a problem, right? Because that's in the support within a year, right? That's a problem. That's, you know, opportunity. So they are still trying to figure out these things and then, ah, picture on where I want to get to what you kind of always said. And that's where that digital innovation group they've got all these Aye aye projects. And as we sit here and talk about those things that kind of born in the cloud, but they're common part of the infrastructure. It was easy to give the GPO in the cloud, but I'm going to have to start. So we actually have all the latest Cisco technology and storage technology of A I stuff in our labs and stuff like that. So there's a lot going on is our CEO said would say, It's a really exciting time to be in this business. >> It sounds like it. I wish we had more time to start digging through there, but you'll have to come back. Okay. All right. Thanks for joining us. >> Thank you >> for student a man. I'm Lisa Martin. You're watching the Cube live day one of our coverage of Sisqo live from San Diego. Thanks for watching.

>> fly from San Francisco. It's the Cube covering Google Cloud next nineteen Rodeo by Google Cloud and its ecosystem partners. >> Welcome back to San Francisco, everybody. This is the Cube, the leader in live tech coverage. And we hear it. Mosconi Center, Google Cloud. Next twenty nineteen. Hashtag Google. Next nineteen. I'm Dave, along with my co host student, Amanda's Day two for us. Anthony Lives here. Senior vice president, general manager of the Cloud Data Services Business Unit That net app Cuba Lawman Louis Versi. Who's senior cloud engineer at Cloud Health. Gentlemen. Welcome, Cardinal. Help that I got cloud in the brain. Gentlemen, welcome to the Cube. Thank you much for coming on, Luis. Let's start with you. Uh, a little bit about Cardinal Health. What you guys air are all about. Tell us about the business. Sure. >> Uh, Cardinal Health is a global supply chain medical products services company. We service hospitals, pharmacies throughout the world. We're drivers are delivering cost effective solutions to our two patients right throughout the world. >> Awesome. We're gonna get into that, Anthony, you've been in the Cube a couple times here almost a year since we were last at this show. it's grown quite a bit. Good thing Mosconi is new and improved. He's got all these new customers here. Give us the update. On what? Look back a year, What's transpired? One of the highlights for you. >> Open it up. You know, we've achieved a tremendous amount. I mean, you know, we were a Google partner of the year, which was quite nice. Wasn't even award for the hard work? You know, we have a very special relationship with Google. We actually engineer directly into the Google console, our services that their products that are sold by Google, which gives us a very unique value proposition. We just keep adding, you know, we have more services and we had more regions on. We continue to sort of differentiate the basic services that that customers are now using for secondary workloads and increasingly very large primary work. Look all >> right, we're going to get into it and learn more about the partnership. But but thinking about what's going on, a cardinal health question for you, Lewis is one of the drivers in your business that are affecting your technology strategy and how you're dealing with those. >> Sure, there's a few things on. I'm sure this is the same in many industries, right? We're facing cost pressures. We need to deliver solutions at a lower cost than we have been in the past. We need to move faster. We need to have agility to be able to respond to changes in the market place. So on Prem doesn't didn't give us a lot of that flexibility to turn those lovers in any of those three areas that those three things have really driven our push into the cloud. All >> right, Louis, let let's dig into that a little bit. You could kind of Do you still have on Prem as part of your solution way? Still have >> some eso We've been working over the past two years to my great work loads out of our data center into the cloud. We're about eighty percent of the way there. There's gonna be some workloads. I Siri's doesn't run in the cloud. Very well. You know, we've got Cem >> Way. Were just joking about that earlier today. Yes, yes, yes. Lots of things. But in the back corner somewhere, I've got that icier running or the day working on that Anthony way. >> Blessed with blessed. You know, this is a customer of ours, and way enabled him to run some, you know, pretty heavy on Prem workloads that required NFS can now run, you know, production on Google clouds. So >> yeah, and you're basically trying to make that experience Seamus Wright A cz muchas. You can wait. Talk about that. That partnership with Google, What are the challenges that you guys are tryingto tackle? I'm just going to refer to your >> question. I mean, you know, what we see is that there's a sort of a pivot with the clouds that traditional i t people thought horizontally and they try and sort of you had a storage team and you had a security team and you had a networking team in the cloud. It's sort of pivots ninety degrees, and you have people who don't work clothes on the workload. People are experts in every single thing, and so they go to the cloud, assuming that the cloud itself will take care of a lot of that problem for So we worked with Google and we built a service. We didn't We didn't build it for a storage guy tow, configure. And you know it undo the bolts and nuts way built it like dial tone. That there is. The NFS is always on in Google Cloud and you come and provisioned an end point and you just tell us how much capacity you want and how much performance. And that's it. It takes about eight seconds to establish a volume in Ghoul Cloud that may take through, you know, trouble tickets, and I t capital purchases about six months to do. >> Yeah, Anthony. Actually, one of my favorite interviews last year is I talked to Dave Hits at your event, and he talked about when we first started building it. We build something that storage people would love, and you shot him down and said, No, no, no, This needs to be a cloud first Clouds absolution. Louis, I want to poke at you. You actually said Price is a main driver for cloud agility. Absolutely. But bring this inside a little bit. I know you're speaking at the show a year. You know, people always say, it's like, Hey, you know, cloud isn't easy. Is it cheap? Well, you know, Devil's in the details there. So would love to hear your experience there. And you know how you know less expensive translates in your world? Sure. >> So when we were looking for something, we tried to get away from Nasim. We're moving to the cloud and we just can't do it right There's way have a lot of cots, applications, a lot of processes that you just have to have known as right and we're looking for something Is Anthony described that with a click of a button are developers Khun spin up their own storage. The price point was lower than then. Frankly, you could get just provisioning the type of disk that you need in the cloud fur, and that was acceptable for most of our workloads. The the the ability to tear right. There's through three classes of storage and in the cloud volume services. Most of our workloads are running on the standard tear, but we've got some workloads where they've got higher performance and we provisioned them right on the standard. And when that you're doing, they're testing like, hey, we need a little bit more with a click of a button there at a higher tier of storage. No downtime, no restarting, no moving storage. It's I just worked. So the cost, the agility were getting all of that out of the solution to >> manage those laces, that sort of, ah, sort of automated way or you sort of monitoring things. And what's the process for for managing, which slays the slaves on the different tiers of storage. If >> we provide him, Yeah, we're not. We're not money for s. >> So it's all automated. >> Run it. And we stand by guarantees throughput guarantees on we take the pain away. You know, I always like to say, you know, what people want to do in the public cloud is innovate, not administrator. And generally, you know. So when when people say clouds cheaper, it's because I think they've decided that they're better use of the dollar is in application development, data science, and then they can retire people and put application developers into the business. So what ghoul does, I think incredibly well as it has infrastructure to remove the sort of the legacy barrier and the traditional stuff. And then it has this wonderful new innovation that, you know, maybe a few companies in the world could decide could use it. But most people couldn't afford to put TP use or GP use in their data center, so they know he was really two very strong Valley proposition. >> And maybe what they're saying is when they say the cloud is cheaper, maybe is better are why I'm spending money elsewhere. That's give me a better return. >> I do things that make you different. Not the same, right, >> right, right. So storage strategy. I mean, I'm sure there should be such a thing anymore. Work illustrated back in the day when used to work A DMC was II by AMC for Block Net out for file Things have changed in terms of how you run a strategy. Think about your business. So what is your strategy when you think about infrastructure and storage and workloads? >> So we really don't want to have to focus on an infrastructure strategy, right? Right now we're mostly running traditional workloads in the cloud running on PM's. We're working towards getting a lot of work loads into geeky, using that service and in Google Cloud platform, >> so can you just step back for a second? How do you end up on Google? Why'd you choose them versus some of the alternative out there. >> So we started our cloud journey a couple of years ago. Started out with really the main cloud player in town, like most people have. Um, and about a year in, not all of our needs were being met. You know, they that company entered decided to enter our business segment. S O, you know, starts asking some questions. People start asking some questions there. So that prompted us to do an r f p to try to see technologically really, were we on the right cloud cloud platform? And we compared the top three cloud providers and ended up on GP from a technological decision, not just a business decision. It gave us the ability to have a top level organization where we could provisioned projects to application teams. They could work autonomously within those projects, but we still had a shared VPC, a shared network where we could put Enterprise Guard rails in place to protect the company. >> Dominic Price was on earlier with Google and he was saying some nice things about net happened. I'd like to hear your perspective is why Ned App What's unique about Nana. What's so special about net app in the cloud. Sure, a few of the >> things that Anthony talked about were really differentiators for us. We didn't have to go sign a Pio with another company, and we didn't need to commit to a certain amount of storage. We didn't need to build our own infrastructure. Even in the cloud, the service was just there. You do a little bit of up front, set up to connect your networking and weaken prevision storage whenever we want. We can change the speed the through. Put that we're getting on that storage at any point in time. We congrats. That storage with no downtime. Those are all things that were really different and other solutions that were out there. >> I mean, it's interesting infrastructure. Tio was really still even in a cloud. It's kind of like a bunch of Lego blocks on what we always said it was. You know, people want to buy the pirate ship, you know, they don't want to, like, have to dig in all these bins. And so we sort of said, Let's build storage, Kind of like a pirate ship that you just know that the end result is a pirate ship and I don't have to understand how to pick a ll Those pieces. Someone's done that for me. So, you know, we're really trying, Teo. I was I'd say we like to create easy buns. You know, people just hit the easy button and go. Someone else is going to make sure it's there. Someone else is going to make sure it performs. I am just a consumer off it, >> Anthony Wave talkto you and Ned app. You play across all the major cloud providers out there and you've got opinion when it comes to Kerber Netease, Help! Help! Help! Give us the you know where what you think about what you've heard this weekend. Google. You know, I think how they differentiate themselves in the market. >> You know, I think it's great, you know, that Google, I think open source community. So I think that was a ninja stry changing event. And, you know, I think community's really starts to redefine application development. I think portability is obviously a big thing with it, But But for an application, developer of the V. M. Was something that somebody added afterwards, and it was sort of like, Oh, no way overboard infrastructure. So now we'Ll virtual eyes it But the cost of virtual izing things was so expensive, you know, you put a no s in a V m and communities was, was built and was sort of attracted to the developer. And so the developers are coding and re factoring, and I just You just look around now and you just see the ground swell on Cuban cnc f is here, and the contributions that were being made to communities are astonishing. It's it's reached a scale way bigger than Lennox. The amount of innovation that's going into cos I think is unstoppable. Now it's it's going to be the standard if it isn't already >> Well, Louis, I'd love you to expand. You said it sounded like you moved to the cloud first, but now you're going down that application modernization, you know, how does Cooper Netease fit into that? And what what other pieces? Because it's changing the applications and get me the long pole in the tent and modernization. So >> cardinal took the approach of we need to get everything into the cloud. And then we can begin modernizing our applications because if we tried to modernize everything up front, would take us ten to fifteen years to get to the cloud, and we couldn't afford to do that. So lifting and shifting machines was about seventy eighty percent of our migration to the cloud. What we're looking at now is modern, modernizing some of her applications R E commerce solution will be will be running on Cooper. Nettie is very shortly on DH will be taking other workloads there in the future. That's definitely the next step. The next evolution >> Okuda Cloud or multi Cloud? That is the question way >> are multi cloud. There are, you know, certain needs that can only be met in certain clouds, right? So Google Cloud is our primary cloud provider. But we're also also using Amazon for specific >> workloads and used net up across those clouds erect. Okay, so is that What's that like? Is that nap experience across clouds so still coming together? Is it sort of highly similar? What's experience like? >> So it's it's using that app in both solutions is the same. I think there's some stuff that we're looking forward to, that where where things will be tied together a little bit more and >> that brings me to the road map Question. That's Please get your best people working on that. >> Oh, yeah. No, no. I mean, I So, look, I think storages that sort of wonderful business because, you know, data is heavy, it's hard, it doesn't like to be moved, and it needs to be managed. It's It's the primary asset of your business these days. So So we have we have, you know, we released continuously new features onto the service. So, you know, we've got full S and B nfs support routing an FSB four support routing a backup service. We're integrating NFS into communities, which is a very frequently asked response. A lot of companies developers want to build ST collapse and Block has a real problem when the container failed. NFS doesn't So we're almost seeing a renaissance with communities and NFS So So you know, we just we subscribe to that constant innovation and we'll just continue to build out mohr and more services that that allow I think cloud customers to, as I said, to sort of spend their time innovating while we take care of the administration for them >> two thousand six to floor. And I wrote a manifesto on storage is a service. Yeah, I didn't know it. Take this long, but I'm glad you got there. Last question, Lewis. Cool stuff. You working on fun projects? What's floating your boat these days? >> My time these days is, uh, the cloud. As I said, we went to the cloud for cost for cost savings. You can spend more money than you anticipate in the cloud. I know it's a shocker. So that's one of the things that I'm focusing our efforts on right now is making sure that way. Keep those costs under control. Still deliver the speed and agility. But keep an eye on those things >> that they put a bow on. Google next twenty nineteen. Partner of the year. That's awesome. Congratulations. Thank >> you. Uh, you know, I would say, you know, to put in a bone it's great to see Thomas again. You know, I went to Thomas that Oracle for about six and a half years. He's an incredibly bright man on DH. I think he's going to do a lot of really good things for Google. As you know, I work for his twin brother, George on DH. They are insanely bright people and really fun to work with. So for me, it was great to come up here and see Thomas and I shook hands when we won the award, and it was kind of too really was like, you know, we're both in a Google event. >> Yeah, it was fun. I'm gonna make an observation. I was saying the studio in the Kino today. They were both Patriots fans. So Bill Bala check. He has progeny. Coaches leave. They try to be him. It just doesn't work. Thomas Curie is not trying to be Larry. I'm sure they, you know, share a lot of the same technical philosophies and cellphone. But he's got his own way of doing things in his own style. So I really it's >> a great Haifa. Google great >> really is. Hey, guys, Thanks so much for coming to the cure. Thank you. Keep right, everybody Day Volante with student meant John Furry is also in the house. We're here. Google Next twenty nineteen, Google Cloud next week Right back. Right after this short break

>> Live from Las Vegas, it's theCUBE covering AWS re:Invent 2018. Brought to you by Amazon Web Services, Intel, and their ecosystem partners. >> And welcome back here on the Sands as we're at the AWS re:Invent day one of our coverage here. We're here Tuesday, Wednesday, and Thursday live here on theCUBE as we continue our coverage from the show. We're Hall D again, if you're in the area, come on by, say hi to Justin Warren and myself. Along with Justin, I'm John Walls. We're joined by Andy Langsam, who's the COO of N2WS. Say Andy, good to see you today. >> Good to see you too. >> Thanks for being here. And Danny Allan, who's the Vice President of Product Strategy at Veeam Software. Danny, good afternoon to you. >> Thank you very much. >> Now we could talk about a lot of things, Canadian citizenship, fractional ownership, a lot of great conversation. So let's talk about data. And of course, the paramount need these days, right? Everybody's got to know I'm alright, I'm secure, I've got this big warm blanket around me. What are the two of you doing to give people with those kind of concerns the ability to sleep at night peacefully, knowing their data's safe? >> Well, you know N2W was founded on the premise of not to worry, that was the founder's vision. And if you could convince somebody that was doing the backup in disaster recovery not to worry, that was a great way to get started. But we're excited today, we've announced N2WS Version 2.4 and it's focused on taking your EC2 snapshots and putting them into S3's storage to lower your cost by up to 40% and 50% and so that's one of the things that we're talking about today. >> Danny. >> Yeah and so if you expand on that, so this is data protection for the cloud and one of the things historically we've focused on as well is data protection in the data center. So that brings the two together and gives you data protection holistically, across wherever your environment happens to be, and goes beyond that, not just data protection but how can I take the data and do more with it? And so we're excited and it seems to be resonating with customers. We have, what, 189% year over year growth on the cloud side. It's just huge, it's a booming business. >> I would assume that you don't have any problem getting people's attention these days, I would assume. >> No we don't, you know, at the booth, it's just amazing, you know, eight, nine thousand sign up batch scans and people all wanting demos and wanting trials of the software. You know, any time you can talk about cost reduction from five cents a gig on EC2's storage to two cents on S3, it's a tremendous savings for our customer base and so they're very excited. We did a survey recently and over 50% of our customers spent over $10,000 a month on storage cost in AWS. So if you think about that and if they can save 40% on that, that's real savings, more than the cost of the software alone. >> Sure. >> Yeah. >> One thing about cloud that often sort of went past people because they were used to the data center and they were used to how they protected their data in the data center. And cloud kind of changed the way that you had to do that and you have think about them in a slightly different way. So clearly N2WS is part of the solution to that. But when you have people who have a bit of data in both of those systems, how do you help them understand which techniques they should use for data which is in the cloud compared to data that's in their data center? Or am I able to just use the same techniques and just go, "You know what? "I'll take care of you and we'll just "turn it on and it'll magically work for you"? >> It's not the same techniques but it's the same platform. And the reason I say that is in the cloud, here in AWS for example, you don't have access to the hypervisor so you can't do a snapshot of the hypervisor, you have to call an API and say, "Gimme a copy of the data." If you're in your own data center, you say, "Take a snapshot of the storage "level or at the hypervisor level." So there's different techniques but at the end of the day, it's still data protection, and with a single platform, that's what's so exciting about this release, Backup and Recovery 2.4, is you have a single platform that you can manage data protection both on and off premises so that you can leverage where is the best place, location, for this workload, and I can protect it across no matter where it chooses to live. >> Yeah, that is something that we've been hearing all day today here at theCUBE is that people are talking about putting their data wherever they want it to live. It could be in the cloud, it could be on their own data site, it could be out at the edge. So whatta you see as the vision, like, where are customers going with this, where do we want to put data? We heard for a long time that we should migrate all of our applications into the cloud. Clearly there are a lot of organizations who are doing that. There are some who have put some things into the cloud and they're actually taking them back out again. >> Sure. >> Where are you seeing customers moving their data around? >> Well, the answer to that, of course, is it depends. There's no single answer for everything. What I say is the cloud is excellent for certain things like variable based workloads or you need a mass amount of compute for a certain amount of time. What people have tried to do sometimes is just lift and shift, take what's on premises and move it to the cloud, and sometimes what ends up happening is they put it back on premises 'cause they realize hey, the cloud's not a charity, they're actually putting in margin there for that brick load. >> They're good. >> So there's use cases for all of this. I think actually what gets exciting is as people design for the cloud, use Lambda and serverless-type functionality, that will become a lot more sticky and so our focus is wherever the customer chooses to run the workload, we're not going to dictate it one way or the other. In fact, one of the great things that we enabled is portability. If you choose to be in point A today, you can move it to point B and back again, so we give that portability that ultimately allows the customer to solve what their business need is. >> You mentioned the customer growth, I think it was like 189% you were saying, is that net new customers to Veeam completely, is that Veeam customers who are growing into using this new product and putting their data in the cloud, where is growth coming from? >> So that growth, that growth has been since we've been acquired by Veeam back in December, it's almost been a year now we were acquired by Veeam and we've been, being acquired has allowed us to focus on the customer and innovation versus going out and raising money from investors as a small company, right? And so we've had 189% growth in our business in terms of revenue since we've been acquired. And it's really accelerating both on the growth side in all sizes of customers. We've got customers recently like Notre Dame and Cardinal Health. And then we have people getting into the cloud, you know, for the very first time and they go to the Amazon Marketplace, they search through the catalog, they find the N2W products, they download it and, well, they provision it and onward they go. >> Yeah, you mentioned Cardinal Health. >> Yep. >> Let's talk about the sector in general. I mean, very unique concerns, obviously, when it comes to whether it's protecting imaging or patient information or whatever it might be. What have you seen in terms of addressing the needs of that sector because obviously this is an area that's growing, there's more capability than ever, and yet our concerns in it are growing with that. So I mean, what do you guys see in that space? >> Yeah so I think, you know, in the health care sector in general, I think what they're really concerned about is the compliance requirements. It's not just backing up the data but it's the requirement that you have a back up and can restore and you can recover from a disaster or from internal hacking or from whatever, an outage, whatever it might be, and if they don't do it, the repercussions are very, very high. And I think that the whole world with GDPRS and things like that are all coming together to dramatically raise the requirement to be more secure than ever and your backup and disaster recovery strategy is paramount to them. They won't be talking about, "We're going to do this." Some customers say, "We're going to do this ourselves, "we'll write our own code." We won't see that in the health care space or the financial space. >> So I see kind of three interesting areas. One is, they typically will have very specific applications like APEC and Meditech that they need you to protect that are aware of that type of application, so that's one part of it. The second is, there's a lot of certifications required to deliver health care services, so you HIPAA and HITECH and, you know, BAA certifications and all these things, and that certainly comes into play when you're talking about the cloud, so you need to have that conversation. And then lastly, ransomware comes up a lot because there's been a lot of ransomware attacks and malware attacks specifically directed at the healthcare industry. So those are the three kind of areas that we have probably the most conversations about. >> Right, yeah malware has been the best advertisement for backup and recovery, ever. It's kind of fabulous, in a way, in a scary way and we don't actually want to encourage this kind of behavior, but for those of us who have lived and breathed backup for awhile, it's like, "Finally, "people can take this seriously." So that's something that people have realized that, okay, I need to have this. What are they looking at next? Where are customers looking to Veeam and to N2WS, what are they looking for you to add next? >> So I'd say the next kind of big step, so to date we've been very much reactive as an industry, right? "Help me protect my data." "Let me get it back" when they recover to the cloud or move from one cloud to another cloud. Now we're getting customers saying, "You have all this data, you understand the context of everything that I own, help me get smarter in my business so that I can drive the business to make decisions more quickly." So, "Give developers a copy of the data "so that they can iterate on it more quickly." "Give a copy of the data to my GDPR experts 'cause "they need to analyze the data and do something with it." And so we're moving away from just being reactive to business needs to being proactive and driving the business forward. And I think where it gets really interesting, as we go down the road and now this is buzz words, I admit, but around machine learning and artificial intelligence, we're actually, we leveraged a lot of the algorithms that are existing in clouds like AWS to help analyze the data and make decisions that they don't even know that they need to make. And that decision could be, "Hey, you need to "run this analysis at two in the morning "'cause the instances are cheaper." That type of predictive analysis helps the customer reduce cost but also drives the business forward. >> Yeah, so how do you move into that kind of advisory space from a more traditional that we'll protect your data. How do, do customers come to you and say, "Actually, you have our data anyway, "why don't you do this for us?" or are you going to customers proactively and saying, "Hey, we can do this for you, "we have access to this data and we can tell you that, "we can provide these insights to you, "would you like some more of this?" Which way does that conversation tend to go? >> It's a bit of a mix, what I'd say is that the data protection face or the storage, you know, the traditional IT person becomes kind of the help desk and then because they've enabled self service recovery, file level recovery, item level recovery, these other areas of the business come in and say, "Hey, can I use that self service to do X and Y?" So it's a new buyer, it's a new constituent, but they're actually looking to IT to enable them to do more stuff with the data. >> Okay, so it's basically, "I want to interact with you "in a similar way that I'm already doing it, "and you've proven your work in this area, "maybe you could do it over here as well." >> Exactly. >> Sounds like a great opportunity for growth. >> And not just on legacy, I mean, one of the interesting things with the N2W software is we enabled, for example, data protection on DynamoDB. So people think of databases and they think SQL Server and Oracle but we can do this, even in cloud RDS-type workloads with DynamoDB, to help them drive cloud hosted workloads faster for the business as well. >> Well, you mentioned Notre Dame, can we have any connections on the playoff ticket situation, can we -- (laughter) >> I wish. >> Just want to make sure. Gentlemen, thanks for being with us and let's get back in maybe three or four weeks, we'll talk about that, okay? >> It'll be great, yeah, it'll be interesting to see who the final four are going to be. >> That's for certain. Thank you both -- >> Thank you. >> Find the information, really enjoyed the conversation. Back with more here from AWS re:Invent, we are live in Las Vegas, Nevada. (electronic music)

>> Narrator: Live from Washington, D.C., it's theCUBE covering .NEXT conference. Brought to you by Nutanix. >> Welcome back to Washington, D.C. everybody. This is theCUBE, the leader in live tech coverage. My name is Dave Vellante. I'm here with Stu Miniman, this is day two of our coverage of .NEXT Conf #NEXTConf. Wendy M. Pfeiffer is here. She's the relatively new CIO of Nutanix. Wendy, thanks for coming on theCUBE. >> Thanks for having me, good to be here. >> Okay, you got my attention. You said there's a reason for it. >> Reason for the M? >> For the M. >> Yeah, absolutely. It's my mom's middle initial, her middle name is Michelle. My middle name is Michelle and my ten-year-old daughter Holly's middle name is Michelle and we sort of pass along our female heritage. I send Holly a message whenever I do anything publicly that it's a shout out to her. She gets to lead, she gets to be proud of her feminine heritage as well as her family heritage. >> I love that, that is fantastic. Quick aside, I'm going to make you laugh. We're at the race track one day and there was this one guy, and he was winning and I wasn't winning so I said, it's like the eighth race, How are you doing this? Well his last name began with an M. He goes, I'm just betting on all the horses with an M in it. >> That could be another good reason. Thanks for the tip. >> Anyway, welcome to theCUBE and welcome to Nutanix. Five months in on the job, you got a really strong IT background. GoPro, Yahoo, both companies of senior leadership. Robert Half, I think, was on the resume as well. >> Yeah, CISCO Systems, Exodus Communications. >> You've seen it all. >> Which means I'm old. I've been around a long time. Any company, I would work anywhere. >> Not as old as I am, honey. So, what's the experience been like at Nutanix? Tell us about the onboarding. >> It is a playground, I love it. Nutanix, I was hoping that they would have the technology that I love and they do. It's one of the first places I've worked where it doesn't matter if I need server storage, we have that. It's pretty cool. I have a really amazing team and then the leadership there is fantastic. It's also the first time in my career where I'm working for a company that sells to CIO's and so my opinion of our product matters. I get to be customer number one, drink our champagne, that sort of thing. In fact, I'm on that path, we call it Eat Your Own Dog Food, when I came on board and I said, I don't want the dog food. We're going to be drinking our own champagne. I want the good stuff. I'm getting to play and just experience the product and experience that process and then people care what I think, people who are developing product care what I think and that's great. >> Are the sales guys dragging you into situations as well? >> They are totally dragging me into situations. I'm not that compelling in direct sales but I have been giving them some tips on how to sell to CIO's. Just letting them know how to approach us, and some of the things that we care about and don't care about. What's great as well is, I'm not very good at being fake, so when I talk about using our product and when I'm excited about our product, it's pretty, you know, it's genuine. If I don't like something, you know that too. >> Well CIO's, you're part of a network. >> We are. >> And that network is sort of immutable, in my opinion. >> It's a secret cabal. It really is, we get together in treehouses and exchange the password. >> But there's a code, right? >> There is. >> You're not going to give another one of your peers some bad advice, even if you are a CIO of a company that's trying to sell to them. >> That's right. It's a small circle. I do belong to some groups that get together and talk about some of our common challenges and one of our cardinal rules is that no vendors are allowed and there's no selling. We do, if we have some expertise, we'll share that but we really don't cross that line. So when I do give advice, they know it's genuine, as much as possible. >> Wendy, we always like to ask CO's, what's challenging you today? Typical IT, we always said for years, it was like, Okay, your headcount next year is going to be flat, your budget's going to be declining. What do you see when you're talking to your peers? What are some of the biggest challenges that they see? >> It's a few things. One thing is, the transformation that's happening around digital technologies and moving into the cloud. It's requiring a transformation of skill sets as well. We really have a challenge, first of all, in deciding, if we have traditional IT folks, how do we transform their skill sets? How do you make an infrastructure guy or gal someone who writes code? That's one thing and just a dearth of talent. There aren't enough people entering the workforce. That's one thing. Another thing is, really just about the pace of innovation. By nature, when you get to a senior executive level, you're almost less innovative than you might've originally been but we're supposed to be the paragons of innovation and new ideas and so we struggle with that. We struggle to keep it fresh and reinvent ourselves. I left a fairly traditional career to go to GoPro, just because of that desire to reinvent myself and try something hard and new. We've got that struggle as well. I'd think as well, just the changing business models, too. There's a lot, we're always balancing CapEx, OpEx, a lot of us have a big investment in OpEx and in SaaS and then trying to balance that with CapEx. We've always got those challenges. I think that's a lot of it. >> Wendy, we're 10 years into this journey of what cloud and how it's going to affect it and the role of the CIO is something that's been in the center of it. Does the CIO become irrelevant? Does he become a broker of services? You talked a little bit about some of the changing roles. How was your viewpoint on cloud, has it changed over the last few years in some of your different roles and I'm curious inside of Nutanix, how public cloud fits into what you use. >> I think there's a couple of layers. One layer that doesn't go away is operations. Whether it's taking operational expertise and transforming that into code for DevOps, or whether it's transforming it into process for on-premise infrastructure, you have to have that knowledge and you have to have that leadership so I don't think the need for leadership is ever really going away. I think the center of leadership is changing over time and has sort of moved from place to place but ultimately, we have to have folks who understand how to build whatever it is, to scale, who understand how to flex, who understand how to deal with crisis. Then also, there's some fundamentals towards architecture and building blocks. Yes, we're architecting differently. We're architecting with code in the cloud but the principles underlying those things are relatively the same. I don't think that the functions, the need for leadership, is going away at all but I do think that we have to be flexible in our thinking. I will say the title CIO it's actually never kind of been right. Chief Digital Officer or Chief AWS Officer. All of those things are not exactly right. We need to not be so precious about titles and just go back to thinking and leading and innovating and let the titles take care of themselves. >> I got to still ask you about this emergent role of the Chief Data Officer. We can all agree data's important, whatever bromide you want to use, data's the new oil and so forth and so on. Many of the chief data officers that we've talked to are individuals that maybe do a lot of governance, lot of things that CIO's generally aren't responsible for. Yet at the same time, data is becoming this new competitive advantage and it's so important to information technology. What are your thoughts on data, helping companies become data-driven and what is the role of the CIO in that context? >> First of all, data is really, really important. How a company deals with its data is a gigantic differentiator. Obviously, we have all this opportunity in the areas of machine learning and potentially AI and so on. When I was at Yahoo, one of the things I worked on was our privacy initiatives and even back then, we had the ability to ingest a lot of data about our users and we had the ability, algorithmically, to do behavioral targeting. But we had to make some ethical decisions and some compliance decisions about how we used that data and so, the technology has been available for some time, but where we haven't caught up is in policy. I think that Chief Data Officer is really at the nexus of creating policy, understanding capabilities and deciding how we apply those things. We've always needed that role. Sometimes it's the CIO, sometimes it's the Chief Privacy Officer, we've always needed that role but the role is a little bit different, I think, with data because of the power of the data. I do think there's a need for some knowledge of the law, GDPR is coming down from Europe and there's a key factor there. Ultimately, data needs to be treated like an asset. It's product as much as anything else. I think someone who's akin to a Chief Product Officer needs to handle the company's data and that data needs to imbue the product, it needs to go to market plans. It also can be a reflection of the culture of the company, as well. Even collecting data on ourselves and how we operate and how our employees move through their cycles is very, very powerful. Always with ethics, though. That's the thing that, if you leave data in the hands of pure engineers or pure technologists, then you need some sorts of checks and balances as well because sometimes we're overcome by the possibilities of the technology, without thinking through the possibilities that affect human beings. We need that balance. >> I've always felt like the CIO is the field general and should be implementing the data strategy but he or she shouldn't be necessarily responsible for, Okay, how are we going to monetize the data? Who has access to data? What are the data policies? That seems like a full-time job but there is overlap, though. >> It's messy, right? A lot of times it has to do with, I mean at that sea level, those are all board-level positions, right? Ultimately, we're responsible for the financial health of the company >> Sure. >> At that level. Really, we're playing to our strengths. Sometimes we come to the table and we understand how to monetize data. Sometimes we come to the table and we know how to efficiently manage operations. There's usually a mix. There's somebody with a CTO or a CPO or a CIO title or a Chief Data Officer title, but it's less about the title and more about those strengths that show up around the executive table but there needs to be somebody, or maybe a combination of a couple of somebodies, who are hungry for the value that they can derive from that data and accrue that to value to the company. >> It's some notion of swim lanes for accountability but recognizing there's some overlap. We got to talk about women in tech, but go ahead. >> Just two things, Wendy. >> Did you notice I'm a girl? >> As a technology leader, I'm curious if you see differences between yourself being a technology leader in Silicon Valley and those outside the Valley and the second one, just curious if you've had any learnings working now for a company that sells to the enterprise versus being on the consumer side of the house at GoPro and some of the others? >> Silicon Valley is a bubble. We all breathe our own oxygen. We think we're pretty cool. We tend to be libertarian as a group and therefore, we have libertarian policies that are embodied in how we develop code, how we create product and we're creating our own little culture but we're not in sync with a lot of the rest of the world. Luckily, one of the pieces of our culture is about building things that are open and so people can repurpose our technologies in ways that make sense for them. The other thing is, even more profound, is the effect of millennials on both Silicon Valley and outside of Silicon Valley. Millennials are changing how we develop code, how we organize our companies, et cetera. Your other question, can't remember. >> Consumer versus selling to the enterprise. >> I think the difference really is just internally, my job it was a different sport, working for a consumer company because people weren't generally smarter than me around my technology. In the consumer company. But they are a lot smarter than me. I am not the technical expert in the room at Nutanix. All of them know more than I do. >> No offense, but I'll bet. >> That was a little intimidating. I had to think twice, do I want to go back to being in junior high? >> Got to ask you, your journey. 17% of the IT industry's employment comprises women. Just so happens that 17% of the guests on theCUBE are women. We really try and go overboard on it. >> Hard to find us. >> There's a clear disparity in pay, it's well-documented. What was your journey to get here? >> It's only now that I'm old and wise and at a senior level that people are making a big thing about me being female. I've been female my entire career. >> Never heard boo. >> I never traded on it. I will tell you that throughout my career, I have been given advice that would seem ridiculous if it were given to a male. As an example, I've been told that I use too many words. That I'm too emotional. I've been told, can you imagine? If I said, Hey Bob, could you button up that top button of your shirt, there? When you sit down, don't spread your legs because I'm drawn to looking at Girls, women, we get that advice from senior advisors. We're told, Be less emotional. I've always ignored that advice. I'm a mom, I have the blonde 1980's hair. There's not much I can do about that. Being genuinely myself, it was all I could figure out how to be. It just so happens that now I'm in my 50's and I'm a CIO, so suddenly that's a thing. It's never been a thing. It's been something where my entire career, I've had to just keep my own counsel and be genuine and the fact that I'm female and feminine and a mom, doesn't diminish the fact that I'm also a brilliant technologist, that I'm good at leading people. I can feel empathy and care in my heart for a person, at the same time that I'm firing them for non-performance. I can be multifaceted. I think that's women's superpower. I think when we try to be just one thing or we try to be more like the traditional male in leadership, then it's like being Jerry Rice and walking onto the field with your legs tied together. My unfair advantage, to quote John Madden, I got to use my unfair advantage. My unfair advantage is that I think in a multifaceted way. >> Wendy M., thanks so much for coming. I'm glad we could make time for you, I'm glad you could make time for us. Thank you. >> Thank you, appreciate it, it was fun. >> Keep it right there, buddy. We'll be back to wrap. This is theCUBE in D.C. at Nutanix .NEXT. Right back.