>> - From around the globe, it's the cube covering data citizens, 21 brought to you by Collibra. >> Hello, everyone, John Walls here, As we continue our cube conversations here as part of data citizens, 21, the conference ongoing. Collibra at the heart of that, really at the heart of data these days and helping companies and corporations make sense. Although this data chaos that they're dealing with, trying to provide new insights, new analysis being a lot more efficient and effective with your data. That's what Collibra is all about. And their founder and their chief data citizen, if you will, Stan Christiaens joins us today. And Stan, I love that title, chief data citizen. What does that all about? What does that mean? >> Hey John, thanks for having me over. And hopefully we'll get to a point where the chief data citizen Titelist cleaves to you. Thanks by the way, for giving us the opportunity to speak a little bit about what we're doing with our chief data citizen. We started the company about 13 years ago, 2008. And over those years, as a founder I've worn many different hats from product to pre-sales to partnerships and a bunch of obvious things. But ultimately the company reaches a certain point a certain size where systems and processes become absolutely necessary if you want to scale further. And for us, this is the moment in time where we said, okay we probably need a data office right now ourselves, something that we've seen with many of our customers. So we said, okay, let me figure out how to lead our own data office and figured out how we can get value out of data using our own software at Collibra itself. And that's where the chief data citizen role comes in. On Friday evening, we like to call that drinking our own champagne moment morning, either eating our own dog food but, essentially this is what we help our customers do, build out the data offices. So we're doing this ourselves now, when we're very hands-on. So there's a lot of things that we're learning, again just like our customers do. And for me, at Collibra, this means that I'm responsible as a chief data citizen for our overall data strategy, which talks a lot about data products, as well as our data infrastructure, which is needed to power data products. Now, because we're doing this in the company and also doing this in a way that is helpful to our customers. We're also figuring out how do we translate the learnings that we have ourselves and give them back to our customers, to our partners, to the broader ecosystem as a whole. And that's why if you summarize the strategy, I like to sometimes refer to it as data office 2025, it's 2025. What is the data office look like by then? And we recommend to our customers to also have that forward looking view just as well. So if I summarize the, the answer a little bit and it's fairly similar to achieve that officer role but, because it has the external evangelization component, helping other data leaders, we like to refer to it as the chief data citizens. >> Yeah, and that, that kind of, you talked about evangelizing, obviously with that, that you're talking about certain kinds of responsibilities and obligations. And I, when I think of citizenship in general I think about privileges and rights and you know, about national citizenship. You're talking about data citizenship, So I assume that with that you're talking about appropriate behaviors and the most well-defined behaviors, and kind of keeping it between the lanes basically. Is that, is that how you look at being a data citizen or, and if not, how would you describe that to a client about being a data citizen? >> It's a very good point, as a citizen you have rights and responsibilities, and the same is exactly true for a data citizen. For us, starting with what it is, right for us, A data citizen is somebody who uses data to do their job. And we've purposely made that definition very broad because today we believe that everyone in some way uses data to do their job. You know, data is universal. It's critical to business processes and it's importance is only increasing. And we want all the data citizens to have appropriate access to data and the ability to do stuff with data but, also to do that in the right way. And if you think about it this is not just something that applies to you in your job but, also extends beyond the workplace because as a data citizen, you're also a human being, of course. So, the way you do data at home with your friends and family, all of this becomes important as well. And we like to think about it as informed privacy aware, data citizens should think about trust in data all the time, because ultimately everybody's talking today about data as an asset, and data is the new gold, and the new oil, and the new soil, and there is a ton of value in data but, as much as organizations themselves to see this, it's also the bad actors out there. We're reading a lot more about data breaches, for example. So, ultimately there's no value without risk. So, as a data citizen, you can achieve a value but, you also have to think about, how do I avoid these risks, and as an organization, if you manage to combine both of those, that's when you can get the maximum value out of data in a trusted manner. >> Yeah, I think this is pretty, an interesting approach that you've taken here because obviously there there are processes with regard to data, right? I mean, the, you know, that that's pretty clear but, there are also, there's a culture that you're talking about here that, that not only are we going to have an operational plan for how we do this certain activity and how we're going to analyze here, input here, action, or perform action on that, whatever but we're going to have a mindset or an approach mentally that we want our company to embrace. So, if you would walk me through that process a little bit in terms of creating that kind of culture, which is very different than kind of the X's and O's and the technical side of things. >> Yeah. That's I think when organizations face the biggest challenge, because, you know maybe they're hiding the best most unique data scientists in the world but, it's not about what that individual can do, right? It's about what the combination of data citizens across the organization can do. And I think it starts first by thinking as an individual about universal goal, golden rule, treat others as you would want to be treated yourself, right? The way you would ethically use data at your job. Think about that, There's other people at other companies, who you would want to do the same thing. Now, from our experience, in our own data office at Collibra, as well as what we see with our customers. A lot of that personal responsibility which is where culture starts, starts with data literacy. And, you know, we talked a little bit about Plymouth rock and the small statues in Brussels Belgium, where I'm from but, essentially here we speak a couple of languages in Belgium. And for organizations, for individuals data literacy is very similar. You know, you're able to read and write which are pretty essential for any job today. And so we want all data citizens to also be able to speak and read and write data fluently. If I, if I can express it this way. And one of the key ways of getting that done and establishing that culture around data, lies with the one who leads data in the organization, the chief data officer, or however the role is called. They play a very important role in this. In comparison, maybe that I always make there is think about other assets in your organization. You know, you're organized for the money assets, for the talent assets, with HR and a bunch of other assets. So let's talk about the, the money assets for a little bit, right? You have a finance department, you have a chief financial officer, and obviously their responsibility is around managing that money asset. But it's also around making others in the organization think about that money. And they do that through established processes and responsibilities like budgeting and planning but, also ultimately to the individual where, you know, through expense sheets that we all love so much, they make you think about money. So, if the CFO makes everyone in the company thinks about think about money, that data officer, or the data lead, has to think, has to make everyone think in the company about data assets, asset, just as well. And those rights, those responsibilities in that culture, they also change, right? Today, they're set this and this way because of privacy and policy X and Y and Z. But tomorrow, for example, as, as with the European union's new regulation around BI, there's a bunch of new responsibilities you'll have to think about. >> You mentioned security and about value and risk, which is certainly, they are part and parcel, right? If I have something important I've got to protect it because somebody else might want to, to create some damage, some harm and and steal my value, basically when that's, what's happening as you point out in the data world these days. So, so what kind of work are you doing in that regard in terms of reinforcing the importance of security culture, privacy culture, you know, this kind of protective culture within an organization so that everybody fully understands, you know, the risks but, also the huge upsides. If you do enforce this responsibility and these good behaviors that that obviously the company can gain from, and then provide value to their client base. So how do you reinforce that within your clients to spread that culture, if you will, within their organizations? >> Spreading a culture is not always an easy thing, And especially a lot of organizations think about the value around data, but to your point, not always about the risks that come associated with it. Sometimes just because they don't know about it yet, right, there's new architectures that come into play, like the clouds and that comes with a whole bunch of new risks. That, that's why one of the things that we recommend always to our customers and to data officers in our customer's organizations, is that next to establishing that, that data literacy, for example, and working on data products is that they also partner strongly with other leaders in their organization. On the one hand, for example, the legal folks, where typically you find the the aspects around privacy and on the other hand, the information security folks, because if you're building up sort of map of your data, look at it like a castle, right, that you're trying to protect. If you don't have a map of your castle, with the strong points and the weak points, and you know where people can build, dig a hole under your wall or what have you, then it's very hard to defend. So, you have to be able to get a map of your data, a data map if you will, know what data is out there. Who its being used by, and why and how, and then you want to prioritize that data, which is the most important what are the most important uses and put the appropriate protections and controls in place. And it's fundamental that you do that together with your legal and information security partners because you may have as a data lead that you may have the data knowledge, the data expertise but, there's a bunch of other things that come into play when you're trying to protect, not just the data but, really your company on its data as a whole. >> No, you Were talking about 2025 a little bit ago, and I thought good for you, that's quite a crystal ball that you have it, you know looking to, you know, with the headlights that far down the road, but I know you have to be, you know that kind of progressive thinking is very important. What do you see in, in the long-term for number one, your kind of position as a chief data citizen, if you will, and then the role of the chief data officer, which you think is kind of migrating toward that citizenship, if you will. So, maybe put on those long-term vision goggles of yours again, and tell me, what do you see as far as these evolving roles and, and these new responsibilities for people who are CEOs these days? >> Well, 2025 is closer than we think right? Then obviously, my crystal ball is as fuzzy as everyone else's but, there's a few things, that trends that you can easily identify and that we've seen by doing this for so long at Collibra. And one is the, the push around data. I think last year, the years, 2020,` where sort of COVID became the executive director of digitalization. Forced everyone to think more about digital, and I expect that to continue. So, that's an important aspect. The second important aspect that I expect to continue for the next couple of years, easily in 2025 is the whole movement to the cloud. So these cloud native architectures become important, as well as the, you know, preparing your data around it, preparing your policies around it, etc.. I also expect that privacy regulations will continue to increase as well as the needs to protect your data assets. And I expected a lot of key data officers will also be very busy building out those data products. So if you, if you take that that trend then, okay data products are getting more important for key data officer's, then data quality is something that's increasingly important today to get right, otherwise, becomes a garbage in garbage out kind of situation, where your data products are being fed bad foods and ultimately their outcomes aren't very clear. So for us, for the chief data officers, I think it was about one of them in 2002, and then 2019 ish, let's say there were 10,000. So there's plenty of upsides for the chief data officer there's plenty of roles like that needed across the world. And they've also evolved in, in responsibility. And I expect that their position, you know, as it it is really a C-level position today in most organizations. Expect that, that trend will also continue to grow. But ultimately those chief data officers have to think about the business, right? Not just the defensive and offensive positions around data, like almost policies and regulations but, also the support for businesses who are today, shifting very fast and will continue to, to digital. So, those key data officers will be seen as key notes. Especially when they can build out the factory of data products that really supports the business. But at the same time, they have to figure out how to reaching all of the branch to their technical counterparts, because you cannot build a factory of data products in my mind at least, without the proper infrastructure. And that's where your technical teams come in. And then obviously the partnerships with your video and information security folks, of course. >> Well heroes, everybody wants to be the hero. And I know that's a, you painted a pretty clear path right now, as far as the chief data officer's concerned and their importance and the value to companies down the road. Stan, we thank you very much for the time today and for the insight, and wish you continued success at the conference. Thank you very much. >> Thank you very much. Have a nice day. Stay healthy. >> Thank you very much Stan Christiaen's joining us, talking about chief data citizenship, if you will, as part of data citizens, 21 the conference being put on by Collibra. I'm John Walls. Thanks for joining us here on the cube. (upbeat music)

>>It's my pleasure to be one of the hosts of the cube on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years, the cube has been following the trail of data. And with the relentless March of data growth, this idea of a single version of the truth has become more and more elusive. Moreover data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is many sued as the CTO and co-founder of Reltio Maneesh. Welcome to the program. >>Thank you, Dave. It's a pleasure to be here. >>Okay. Let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with, with data as a source of digital innovation. >>They, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011, there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making, uh, compute capabilities available at scale to solve large data problems was becoming real impossible. The second thing that we saw was, uh, this big trend of, uh, you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone. And, uh, we are seeing more of the best of breed application type of a landscape where even if you look within a specific function, let's say sales or marketing, you have more than a dozen applications that any company is using today. >>And that trend was starting to emerge where we knew very well, that the number of systems that we would have to work with would continue to increase. And, uh, that created a problem of where would you get the single source of truth or the single best version of a customer, a supplier, a product that you're trying to sell those types of critical pieces of information that are core to any business that's out there today. And, um, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of a capability and for us to provide this capability in the cloud as a software, as a service, uh, uh, offering. So that's where, uh, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos and create a unified view of the core critical information that these companies run on. >>Yeah. I mean, the cloud is this giant, you know, hyper distributed system data by its very nature is distributed. It's interesting what you were sort of implying about, you know, the days of the monolithic app are gone by my business partner years ago, John furrier and the cube said data is going to become the new development kit. And we've certainly seen that with the, the pandemic, but tell us more about Reltio and how you help customers deal with that notion of data, silo, data silos, data fragmentation, how do you solve that problem? >>So, data fragmentation is what exists today. And, um, you know, with the Reltio, uh, software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented, siloed, uh, applications or data sources that they have within their enterprise at the same time. Um, there's a lot of dependence on the third party data. You know, when you think about, uh, different problems that you're trying to solve, you have, uh, for B2B type of information that in Bradstreet type of data providers in life sciences, you have IQ via type of data providers. Um, you know, as you look at other verticals, there is a specialized third-party data provider for any, and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know, who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. >>Um, and that's where Reltio fits in as the only platform that can help stitch together, this kind of, uh, information and create a 360 degree view that spans all the data silos and provides that for real-time use for BI and analytics to benefit from, for data science to benefit from. And then this emerging notion of, uh, data in itself is a, um, you know, key starting point that is used by us, uh, in order to make any decisions, just like, uh, we go, you know, if I, they wanted to look at information about you, I would go to places like LinkedIn, look up the information. And then our, my next set of decisions with that information, if somebody wanted to look up information on Reltio, they would go to, let's say Crunchbase as an example, and look up, uh, who are the investors? How much money have we raised all those details that are available? It's not a CRM system by itself, but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide, uh, as a part of the Reltio platform capabilities. >>Awesome. Thank you. And I want to get into the, to the tech, but before we do, maybe we just cut to the chase and maybe you can talk about some of the examples of, of Reltio and action. Some of the customers that you can talk about, maybe the industries that are, that are really adopting this. W what can you tell us there, Maneesh, >>Um, we work across a few different verticals, some of the key verticals that we work in our life sciences, um, and travel and hospitality and financial services, insurance, um, S uh, retail, as an example, those are some of the key verticals for us, but, uh, to give you some examples of, uh, the type of problems that customers are solving with Reltio as the data unification platform, um, let's take CarMax as an example, CarMax is a customer who's in the business of, uh, buying used cars, selling used cars, servicing those used cars. And then, um, you know, you as a customer, don't just transact with them. Once you, you know, you've had a car for three years, you go back and look at what can you trade in that car for, but in order for CarMax to provide a service to you that, uh, goes across all the different touch points, whether you are visiting them at their store location, uh, trying to test drive a car or viewing, uh, information about the various vehicles on their website, or just, uh, you know, punching in the registration number of your car, just to see what is the appraisal from them in terms of how much will they pay for your car? >>This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points and the type of information that they use, uh Reltio for aggregating, unifying, and then making available across all these touch points is all of the information about the customers, all of the information about, uh, the, uh, household, uh, you know, the understanding that they're trying to achieve because, uh, life events can, uh, be buying signals, uh, for, uh, consumers like uni, as well as, uh, who was the, um, associate who helped you either in the selling of a car buying of a car, because business is all about building relationships for the longer term lifetime value that they want to capture. And in that process, um, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, uh, there is a lot of information in order to price it, right, that needs to be gathered, uh, from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio, and then made available, uh, through API APIs or through other methods, and means to the various applications can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run end to end. Well, it sounds like >>That's come along. Sorry. >>I was just going to say it that's one example and, uh, you know, across other verticals that are other similar examples of how companies are leveraging, Reltio >>Just say, can come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and, and, you know, happy to dig into some other examples, but, but I wonder how does it work? I mean, what's the magic behind it? What's the, the tech look like, I mean, obviously you leveraging AWS, maybe you could talk about how so, and maybe some of the services there and some of your unique IP. >>Yeah. Um, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, uh, you know, if you think about, uh, the problem itself, uh, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. Um, you know, for example, I have been in this area was, uh, responsible for creating some of the previous generation capabilities and, uh, most of the friction in those previous generation MDM or master data management type of solutions, um, as the, you know, the technical term that is used to refer to this area, uh, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that, uh, customers want to capture, whether it is, uh, you know, about a patient or a product, or let's say a supplier that you're working well. >>Uh, there is always additional information that you can capture and, uh, you know, use to better inform the decisions for the next engagement and, uh, that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use at scale compute capabilities in the cloud, um, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information, just locking it in a data warehouse has been sort of the problem in the past. And you talked about the clickstream analysis, uh, analytics has a place, but most of the analytics is a rear view mirror picture of the, uh, you know, work that you have to do, versus everybody that we talked to, uh, as a potential customer, wanted to solve the problem of what can we do at the point of engagement, how can we influence decisions? >>So, you know, I'll give you an example. I think, uh, everybody's familiar with Quicken loans, um, as the mortgage lender and, uh, in the mortgage lending business, uh, Quicken loans is the customer who's using Reltio as the customer data, um, unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time window, um, you know, anywhere from 10 minutes to about an hour, where if somebody expresses an interest in refinancing or getting a mortgage, they have to close that, uh, business within that, uh, Hart window, the conversion ratios are exponentially better in that hot window versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage, uh, at. And, uh, they've been able to use this notion of real time data, where as soon as you come in through the website, or if you come in through the rocket mortgage app, or you're talking to a broker by calling the one 800 number, they are able to triangulate that it's the same person coming from any of these different channels and respond to that person, whether an offer, uh, ASAP so that, uh, there is no opportunity for the competition to get in and present you with a better offer. >>So those are the types of things where the time to, uh, conversion or the time to action is being looked at. And everybody's trying to shrink that time down, uh, that ability to respond in real time with the capabilities was sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities. And now customers are able to benefit from that. >>That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket, and when you experience that environment, it's totally different than anything you've ever seen before. So it's helpful to hear you explain, like what's behind that because it's, it's truly disruptive. And I, and I'll tell you, the other thing that, that sort of triggered a thought was that we use the word realtime a lot, and we try to develop years ago. We said, what does real-time really mean? And the, the answer we CA we landed on was before you lose the customer, and that's kind of what you just described. Uh, and that is what gives as an example, a quick and a real advantage again, having experienced it firsthand. It's, it's pretty, pretty tremendous. So that's a nice, that's a, that's a nice reference. Um, so, and the other thing that struck me is that what I wanted to ask you, how it's different from sort of legacy master data management solutions, and you sort of described that they've seized to me, they got to take their, their traditional on-prem stack, rip it out, stick it in the cloud is okay, we got our stack in the cloud. >>Now your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a, from an CTO's perspective, what's your, >>Yeah. The clean sheet of paper is the luxury that we have, you know, having seen this movie before having, um, you know, looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, um, you know, across all of our customers, we are today managing, um, uh, about 6.5 billion consolidated profiles of people, organizations, product locations, um, you know, assets, uh, those kinds of details. And these are, these are the types of, uh, crown jewels of the business that every business runs on. You know, for example, if you wanted to, um, let's say you're a large company, like, uh, you know, Ford and you wanted to figure out how much business are you doing, where the, uh, you know, another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. >>It's been a very difficult answer to understand what is the total book of business that they have with that other, um, big, uh, customer and, uh, you know, being able to have the right, uh, unified, uh, relevant, rich clean as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, uh, you know, drive, uh, any kind of, uh, conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. Um, you have to have that foundation of clean data to work with in order to get to those answers. >>Nice. Uh, and then I had questions on just the model is this, it's a SAS model. I presume, how, how is it priced? Do you have a, do you have a freemium? How do I get started? Maybe you could give us some color. >>Yeah, we are a SAS provider. We do everything in the cloud, uh, offer it as a SAS offering, um, for customers to leverage and benefit from our pricing is based on the volume of, uh, uh, consolidated profiles. And the, I use the word profiles because this is not the traditional, uh, data model where you have rows columns, foreign keys. This is a, you know, a profile of a customer, regardless of attribution or any other details that you want to capture. And, um, you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Uh, customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, uh, you know, off these different types of data domains, customer, patient provider, uh, product, uh, asset, those types of details. But, uh, then they grow and some of the customers, uh, HP Inc, as a customer is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use the single source of truth capabilities provided by Reltio. >>And your relationship with AWS you're, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >>Yeah. AWS has been a key partner for us, uh, since the very beginning, uh, we are now on the marketplace. Uh, customers can start with the free version of the product, um, and start to play with the product, understand it better, uh, and then move into the paid tier, um, you know, as they bring in more data, uh, into Reltio. And, uh, you know, we also, uh, have, uh, the partnership with AWS where, uh, you know, customers can benefit from the relationship where they are able to, um, uh, use the, the spend against Reltio to offset the commitment credits that they have for AWS, um, you know, as a cloud provider. So, uh, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >>Nice that love, love, those credits, um, company update, uh, you know, head count funding, revenue trajectory, what kind of metrics are you comfortable sharing? >>So, uh, we are currently, uh, at about, um, you know, slightly North of 300 people, uh, overall at rail queue, we will, uh, grow from 300 to about 400 people this year, uh, itself. Uh, we are, uh, uh, you know, we just put out a press release, uh, where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are, uh, looking at, uh, crossing the a hundred million dollar ARR, um, uh, threshold, uh, later this year. So we're on a great growth trajectory and, uh, the businesses, uh, performing really well. And we are, uh, looking at working with more customers and helping them solve this, uh, uh, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >>That's some impressive growth. Congratulations, w w we're, I'm sure adding a hundred people you're hiring all over the place, but where we get some of your priorities. >>So, um, you know, the, as the business is growing, we are spending equally both on the R and D side of the house, uh, investing more there, but at the same time, also on our go to market, uh, so that we can extend our reach, make sure that, uh, more people know about, uh, Reltio and can start leveraging the benefit of, uh, the technology that we have built on top of, uh, AWS. >>Yeah. I mean, it sounds like you've obviously nailed product market fit, and now you're, you know, scaling and scaling the go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, why, what was prompted that move >>Problems of luxury, uh, you know, as I like to call them, uh, once you know, that you're on a great growth trajectory and, uh, the business is performing well, it's all about, uh, figuring out ways of, uh, you know, making sure that you can drive harder and faster towards that growth, uh, milestones, uh, that you want to achieve. And, uh, you know, for us, uh, the story is no different. Uh, the team has done a wonderful job of, uh, making sure that we can build the right platform, um, you know, work towards this opportunity, that PC, which by the way, um, they just to share with you, uh, MDM or master data management has always been underestimated as a, uh, you know, yes, there is a problem that needs to be solved, but the market sizing was, uh, in a, not as clear, but some of the most recent, uh, estimates from analysts like Gartner, but the, uh, you know, sort of the new incarnation of, uh, data unification and master data management at about a $30 billion, uh, you know, uh, Tam or this market. >>So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, uh, I looked at, uh, you know, how could we scale the business faster and have the right team to work, uh, help us maximize the opportunity. And that's why, uh, you know, we decided, uh, that it was the right point in time for me to bring in somebody who's, uh, worked, uh, at, uh, the stretch of, you know, taking a company from just a a hundred million dollars in ARR to, uh, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, uh, you know, has had that experience and having him take on the CEO role, uh, really puts us on a tremendous, uh, our path to tremendous growth and achieving that, uh, with the right team. >>Yeah. And I think I appreciate your comments on the Tam. I love to look at the Tam and to do a lot of Tam analysis. And I think a lot of times when you define the future Tam based on sort of historical categories, you sometimes under count them. I mean, to me, you guys are in the, the, the digital business business. I mean, the data transformation, the company transformation business, I mean, that could be order of magnitude even bigger. So I think the future is bright for your company. Reltio Maneesh. And thank you so much for coming on the program really appreciate. >>Well, thanks for having me, uh, really enjoyed it. Thank you. >>Okay. Thank you for watching. You're watching the cubes startup showcase. We'll be right back.

(upbeat music) >> It's my pleasure, to be one of the hosts of theCUBE on cloud and the startup showcase brought to you by AWS. This is Dave Vellante and for years theCUBE has been following the trail of data. And with the relentless match of data growth this idea of a single version of the truth has become more and more elusive. Moreover, data has become the lifeblood of a digital business. And if there's one thing that we've learned throughout the pandemic, if you're not digital, you're in trouble. So we've seen firsthand, the critical importance of reliable and trusted data. And with me to talk about his company and the trends in the market is Manish Sood the CTO and co-founder of Reltio. Manish, welcome to the program. >> Thank you, Dave. It's a pleasure to be here. >> Okay, let's start with, let's go back to you and your co-founders when you started Reltio it was back in the early days of the big data movement, cloud was kind of just starting to take off, but what problems did you see then and what are enterprises struggling with today, especially with data as a source of digital innovation. >> Dave, if you look at the changes that have taken place in the landscape over the course of the last 10 years, when we started Reltio in 2011 there were a few secular trends that were coming to life. One was a cloud compute type of capabilities being provided by vendors like AWS. It was starting to pick up steam where making compute capabilities available at scale to solve large data problems was becoming real and possible. The second thing that we saw was this big trend of you know, you can not have a wall to wall, one single application that solves your entire business problem. Those visions have come and gone and we are seeing more of the best of breed application type of a landscape where even if you look within a specific function let's say sales or marketing, you have more than a dozen applications that any company is using today. And that trend was starting to emerge where we knew very well that the number of systems that we would have to work with would continue to increase. And that created a problem of where would you get the single source of truth or the single best origin of a customer, a supplier, a product that you're trying to sell, those types of critical pieces of information that are core to any business that's out there today. And, you know, that created the opportunity for us at Reltio to think about the problem at scale for every company out there, every business who needed this kind of capability and for us to provide this capability in the cloud as a software, as a service offering. So that's where, you know, the foundation of Reltio started. And the core problem that we wanted to solve was to bridge the gap that was created by all these data silos, and create a unified view of the core critical information that these companies run on. >> Yeah, the cloud is this giant, you know hyper distributed system, data by its very nature is distributed. It's interesting what you were sort of implying about you know, the days of the monolithic app are gone, but my business partner years ago John Furrier at theCUBE said, data is going to become the new development kit. And we've certainly seen that with the pandemic but tell us more about Reltio and how you help customers deal with that notion of data silos, data fragmentation, how do you solve that problem? >> So data fragmentation is what exists today. And, with the Reltio software as a service offering that we provide, we allow customers to stitch together and unify the data coming from these different fragmented siloed applications or data sources that they have within their enterprise. At the same time, there's a lot of dependence on the third party data. You know, when you think about different problems that you're trying to solve, you have for B2B type of information that in Bradstreet type of data providers, in life sciences you have IQVIA type of data providers. You know, as you look at other verticals that is a specialized third party data provider for any and every kind of information that most of the enterprise businesses want to combine with their in-house data or first party data to get the best view of who they're dealing with, who are they working with, you know who are the customers that they're serving and use that information also as a starting point for the digital transformation that they want to get to. And that's where Reltio fits in as the only platform that can help stitch together this kind of information and create a 360 degree view that spans all the data silos and provides that for real-time use, for BI and analytics to benefit from, for data science to benefit from, and then this emerging notion of data in itself is a, you know, key starting point that is used by us in order to make any decisions. Just like we go, you know, if I they wanted to look at information about you, I would go to places like LinkedIn, look up the information, and then on my next set of decisions with that information. If somebody wanted to look up information on Reltio they would go to, let's say crunchbase as an example and look up, who are the investors? How much money have we raised? All those details that are available. It's not a CRM system by itself but it is an information application that can aid and assist in the decision-making process as a starting point. And that user experience on top of the data becomes an important vehicle for us to provide as a part of the Reltio platform capabilities. >> Awesome, thank you. And I want to get into the tech, but before we do maybe we just cut to the chase and maybe you can talk about some of the examples of Reltio and action, some of the customers that you can talk about, maybe the industries that are really adopting this. What can you tell us there Manish? >> We work across a few different verticals some of the key verticals that we work in are life sciences and travel and hospitality and financial services, insurance retail, as an example. Those are some of the key verticals for us. But to give you some examples of the type of problems that customers are solving with Reltio as the data unification platform, let's take CarMax as an example,. CarMax is a customer who's in the business of buying used cars, selling used cars servicing those used cars. And then, you know, you as a customer don't just transact with them once, you know, you've had a car for three years you go back and look at what can you trade in that car for? But in order for CarMax to provide a service to you that goes across all the different touch points whether you are visiting them at their store location trying to test drive a car or viewing information about the various vehicles on their website, or just you know, punching in the registration number of your car just to see what is the appraisal from them in terms of how much will they pay for your car. This requires a lot of data behind the scenes for them to provide a seamless journey across all touch points. And the type of information that they use relative for aggregating, unifying, and then making available across all these touch points, is all of the information about the customers, all of the information about the household, you know, the understanding that they are trying to achieve because life events can be buying signals for consumers like you and I, as well as who was the associate who helped you either in the selling of a car, buying of a car, because their business is all about building relationships for the longer term, lifetime value that they want to capture. And in that process, making sure that they're providing continuity of relationship, they need to keep track of that data. And then the vehicle itself, the vehicle that you buy yourself, there is a lot of information in order to price it right, that needs to be gathered from multiple sources. So the continuum of data all the way from consumer to the vehicle is aggregated from multiple sources, unified inside Reltio and then made available through APIs or through other methods and means to the various applications, can be either built on top of that information, or can consume that information in order to better aid and assist the processes, business processes that those applications have to run and to end. >> Well, sounds like we come along, (indistinct). >> I was just going to say that's one example and, you know across other verticals, that are other similar examples of how companies are leveraging, Reltio >> Yeah, so as you say, we've come a long way from simple linear clickstream analysis of a website. I mean, you're talking about really rich information and you know happy to dig into some other examples, but I wonder how does it work? I mean, what's the magic behind it? What's the tech look like? I mean, obviously leveraging AWS, maybe you could talk about how, so, and maybe some of the services there and some of your unique IP. >> Yeah, you know, so the unique opportunity for us when we started in 2011 was really to leverage the power of the cloud. We started building out this capability on top of AWS back in 2011. And, you know, if you think about the problem itself, the problem has been around as long as you have had more than one system to run your business, but the magnitude of the problem has expanded several fold. You know, for example, I have been in this area was responsible for creating some of the previous generation capabilities and most of the friction in those previous generation MDM or master data management type of solutions as the you know, the technical term that is used to refer to this area, was that those systems could not keep pace with the increasing number of sources or the depth and breadth of the information that customers want to capture, whether it is, you know, about a patient or a product or let's say a supplier that you're working with, there is always additional information that you can capture and you know use to better inform the decisions for the next engagement. And that kind of model where the number of sources we're always going to increase the depth and breadth of information was always going to increase. The previous generation systems were not geared to handle that. So we decided that not only would we use add scale compute capabilities in the cloud, with the products like AWS as the backbone, but also solve some of the core problems around how more sources of information can be unified at scale. And then the last mile, which is the ability to consume such rich information just locking it in a data warehouse has been sort of the problem in the past, and you talked about the clickstream analysis. Analytics has a place, but most of the analytics is a real view mirror picture of the, you know, work that you have to do versus everybody that we talk to as a potential customer wanted to solve the problem of what can we do at the point of engagement? How can we influence decisions? So, you know, I'll give you an example. I think everybody's familiar with Quicken loans as the mortgage lender, and in the mortgage lending business, Quicken loans is the customer who's using Reltio as the customer data unification platform behind the scenes. But every interaction that takes place, their goal is that they have a very narrow time vendor, you know anywhere from 10 minutes to about an hour where if somebody expresses an interest in refinancing or getting a mortgage they have to close that business within that hot vendor. The conversion ratios are exponentially better in that hot vendor versus waiting for 48 hours to come back with the answer of what will you be able to refinance your mortgage at? And they've been able to use this notion of real time data where as soon as you come in through the website or if you come in through the rocket mortgage app or you're talking to a broker by calling the 1800 number they are able to triangulate that it's the same person coming from any of these different channels and respond to that person with an offer ASAP so that there is no opportunity for the competition to get in and present you with a better offer. So those are the types of things where the time to conversion or the time to action is being looked at, and everybody's trying to shrink that time down. That ability to respond in real time with the capabilities were sort of the last mile missing out of this equation, which didn't exist with previous generation capabilities, and now customers are able to benefit from that. >> That is an awesome example. I know at firsthand, I'm a customer of Quicken and rocket when you experience that environment, it's totally different, than anything you've ever seen before. So it's helpful to hear you explain like what's behind that because, it's truly disruptive and I'll tell you the other thing that sort of triggered a thought was that we use the word realtime a lot and we try to develop years ago. We said, what does real-time really mean? And the answer we landed on was, before you lose the customer, and that's kind of what you just described. And that is what gives as an example a quick and a real advantage again, having experienced it firsthand. It's pretty, pretty tremendous. So that's a nice reference. So, and the other thing that struck me is, I wanted to ask you how it's different from sort of legacy Master Data Management solutions and you sort of described that they've since to me they've got to take their traditional on-prime stack, rip it out, stick it in the iCloud, it's okay we got our stack in the cloud now. Your technical approach is dramatically different. You had the advantage of having a clean sheet of paper, right? I mean, from a CTO's perspective, what's your take? >> Yeah, the clean sheet of paper is the luxury that we have. You know, having seen this movie before having, you know looked at solving this problem with previous generation technologies, it was really the opportunity to start with a clean sheet of paper and define a cloud native architecture for solving the problem at scale. So just to give you an example, you know, across all of our customers, we are today managing about 6.5 billion consolidated profiles of people, organizations, product, locations, you know, assets, those kinds of details. And these are the types of crown jewels of the business that every business runs on. You know, for example, if you wanted to let's say you're a large company, like, you know, Ford and you wanted to figure out how much business are you doing, whether, you know another large company, because the other large company could be a global organization, could be spread across multiple geographies, could have multiple subsidiaries associated with it. It's been a very difficult to answer to understand what is the total book of business that they have with that other big customer. And, you know, being able to have the right, unified, relevant, ready clean information as the starting point that gives you visibility to that data, and then allows you to run precise analytics on top of that data, or, you know drive any kind of conclusions out of the data science type of algorithms or MLAI algorithms that you're trying to run. You have to have that foundation of clean data to work with in order to get to those answers. >> Nice, and then I had questions on just analysis, it's a SAS model I presume, how is it priced? Do you have a freemium? How do I get started? Maybe you could give us some color on that. >> Yeah, we are a SAS provider. We do everything in the cloud, offer it as a SAS offering for customers to leverage and benefit from. Our pricing is based on the volume of consolidated profiles, and I use the word profiles because this is not the traditional data model, where you have rows, columns, foreign keys. This is a profile of a customer, regardless of attribution or any other details that you want to capture. And you know, that just as an example is what we consider as a profile. So number of consolidated profiles under management is the key vector of pricing. Customers can start small and they can grow from there. We have customers who manage anywhere from a few hundred thousand profiles, you know, off these different types of data domains, customer, patient, provider, product, asset, those types of details, but then they grow and some of the customers HPInc, as a customer, is managing close to 1.5 billion profiles of B2B businesses at a global scale of B2C consumers at global scale. And they continue to expand that footprint as they look at other opportunities to use, the single source of truth capabilities provided by Reltio. >> And, and your relationship with AWS, you're obviously building on top of AWS, you're taking advantage of the cloud native capabilities. Are you in the AWS marketplace? Maybe you could talk about AWS relationship a bit. >> Yeah, AWS has been a key partner for us since the very beginning. We are now on the marketplace. Customers can start with the free version of the product and start to play with the product, understand it better and then move into the paid tier, you know as they bring in more data into Reltio and, you know be also have the partnership with AWS where, you know customers can benefit from the relationship where they are able to use the spend against Reltio to offset the commitment credits that they have for AWS, you know, as a cloud provider. So, you know, we are working closely with AWS on key verticals, like life sciences, travel and hospitality as a starting point. >> Nice, love those credits. Company update, you know, head count, funding, revenue trajectory what kind of metrics are you comfortable sharing? >> So we are currently at about, you know, slightly not at 300 people overall at Reltio. We will grow from 300 to about 400 people this year itself we are, you know, we just put out a press release where we mentioned some of the subscription ARR we finished last year at about $74 million in ARR. And we are looking at crossing the hundred million dollar ARR threshold later this year. So we are on a great growth trajectory and the business is performing really well. And we are looking at working with more customers and helping them solve this, you know, data silo, fragmentation of data problem by having them leverage the Reltio capability at scale across their enterprise. >> That's some impressive growth, congratulations. We're, I'm sure adding hundred people you're hiring all over the place, but where we are some of your priorities? >> So, you know, the, as the business is growing we are spending equally, both on the R and D side of the house investing more there, but at the same time also on our go to market so that we can extend our reach, make sure that more people know about Reltio and can start leveraging the benefit of the technology that we have built on top of AWS. >> Yeah, I mean it sounds like you've obviously nailed product market fit and now you're, you know, scaling the grip, go to market. You moved from CEO into the CTO role. Maybe you could talk about that a little bit. Why, what was prompted that move? >> Problems of luxury, you know, as I like to call them once you know that you're in a great growth trajectory, and the business is performing well, it's all about figuring out ways of, you know making sure that you can drive harder and faster towards that growth milestones that you want to achieve. And, you know, for us, the story is no different. The team has done a wonderful job of making sure that we can build the right platform, you know work towards this opportunity that we see, which by the way they've just to share with you, MDM or Master Data Management has always been underestimated as a, you know, yes there is a problem that needs to be solved but the market sizing was in a, not as clear but some of the most recent estimates from analysts like Gartner, but the, you know, sort of the new incarnation of data unification and Master Data Management at about a $30 billion, yeah, TAM for this market. So with that comes the responsibility that we have to really make sure that we are able to bring this capability to a wide array of customers. And with that, I looked at, you know how could we scale the business faster and have the right team to work help us maximize the opportunity. And that's why, you know, we decided that it was the right point in time for me to bring in somebody who's worked at the stretch of, you know taking a company from just a hundred million dollars in ARR to, you know, half a billion dollars in ARR and doing it at a global scale. So Chris Highland, you know, has had that experience and having him take on the CEO role really puts us on a tremendous path or path to tremendous growth and achieving that with the right team. >> Yeah, and I think I appreciate your comments on the TAM. I love to look at the TAM and to do a lot of TAM analysis. And I think a lot of times when you define the the future TAM based on sort of historical categories, you sometimes under count them. I mean, to me you guys are in the digital business. I mean, the data transformation the company transformation business, I mean that could be order of magnitude even bigger. So I think the future is bright for your company Reltio, Manish and thank you so much for coming on the program. Really appreciate it. >> Well, thanks for having me, really enjoyed it. Thank you. >> Okay, thank you for watching. You're watching theCUBEs Startup Showcase. We'll be right back. (upbeat music)

(upbeat music) >> We're here theCUBE on Cloud Startup Showcase brought to you by AWS. And right now we're going to explore the next frontier for privacy, you know, security, privacy, and compliance, they're often lumped together and they're often lumped on as an afterthought bolted on to infrastructure, data and applications. But, you know, while they're certainly related they're different disciplines and they require a specific domain knowledge and expertise to really solve the challenges of today. One thing they all share is successful implementations, must be comprehensive and designed in at the start and with me to discuss going beyond compliance and designing privacy protections into products and services. Justin Antonipillai, who is the founder and CEO of WireWheel, Justin awesome having you on the AWS Startup Showcase. Thanks for being here >> Dave, thanks so much for having me. It's a real honor, and I appreciate it. Look forward to the discussion. >> So I always love to ask founders, like, take us back. Why did you start this company? Where did your inspiration come from? >> So Dave, I was very lucky. I had the honor of serving in president Obama's second term as an Acting Under Secretary for Economic Affairs. So I ran the part of the government that includes the U.S. Census Bureau and the Bureau of Economic Analysis. So core economic statistical bureaus. But I helped lead a lot of the Obama administration's, outreach and negotiations on data privacy around the world. Including on something called the EU-U.S. Privacy Shield. So at the time the two jobs I had really aligned with what our discussion is here today. The first part of it was, I could see that all around the world in the U.S. and around the world, data privacy and protecting privacy, had become a human rights issue. It was a trade issue. You could see it as a national security issue and companies all around the world were just struggling with how to get legal, how to make sure that I do it right, and how I make sure that I'm treating my customer's data, in the right way. But when I was also leading the agency, a lot of what we were trying to do was to help our U.S. citizens, our folks here around the country solve big public problems by ethically and responsibly using government data to do it. And I can talk about what that meant in a little while. So the inspiration behind why WireWheel was, we need better more technically driven ways to help companies get compliance, to show their customers that they're protecting privacy and to put customers, our customers onto a path where they can start using the customer data better, faster and stronger, but most importantly, ethically. And that's really what we try to tackle at WireWheel. >> Right, excellent. Thank you for that. I mean, yeah you know, in the early days of social media, people kind of fluffed it off and oh there is no privacy in the internet, blah, blah, blah. And then wow, it became a huge social issue and public policy really needed to step in but also technology needs this to help solve this problem. So let's try to paint a picture for people as to really dig into the problem that you solve and why it's so complicated. We actually have a graphic. It's a map of the U S that we want to pull up here. Explain this. >> Yeah, I mean, what you're saying here is that every one of your, our viewers today is going to be looking at privacy laws moving across the country Dave but there's a lot of different ones. You know, if you're a company that's launching and building your product, that you might be helping your customers your consumer facing. The law, and you're even let's assume you want to do the right thing. You want to treat that customer data responsibly and protect it. When you look at a map like this and you can see three States have already passed different privacy laws, but look at the number of different States all across the country that are considering their own privacy laws. It really could be overwhelming. And Virginia, as you can see is just about to pass it's next privacy law but there's something like 23,24 States that are moving them through. The other thing Dave, that's really important about this is, these are not just breach laws. You know, I think years ago we were all looking at these kinds of laws spreading across the country and you would be saying, okay, that's just a breach law. These laws are very comprehensive. They have a lot to them. So what we have been really helping companies with is to enable you to get compliant with a lot of these very quickly. And that's really what we've tried to take on. Because if you're trying to do the right thing there should be a way to do it. >> Got it. Yeah, I can't even imagine what the it had been so many permutations and complexities but imagine this, if this were a globe we were looking at it says it gets out of control. Okay, now you guys well you use a term called phrase beyond compliance? What do we mean by that? >> There are a couple of things. So I'd say almost every company taking a product to market right now, whether you're B2C or B2B you want to make sure you can answer the customer question and say, yes, I'm compliant. And usually that means if you're a B2C company it means that your customers can come to your site. Your site is compliant with all of the laws out there. You can take consents and preferences. You can get their data back to them. All of these are legal requirements. If you're a B2B company, you're also looking at making sure you can create some critical compliance records that's it, right? But when we think beyond compliance, we think of a couple of basic things. Number one, do you tell the story about all the trust and protection you put around your data in a way that your customers want to do business with you? I mean Dave, if you went to CES the last couple of years and you were walking into the center or looking at a virtual version of it, on every billboard, the top five, top 10 global companies advertise that they take care of your data and they're onto something, they're onto something. You can actually build a winning strategy by solving a customer's problem and also showing them that you care, and that they're trustworthy. Because there are too many products out there, that aren't. The second thing, I'm sorry, go ahead. >> No, please carry on. >> No, I mean the second thing, and then I think I'd say is going beyond compliance also means that you're thinking about how you can use that data for your customer, to solve all of their problems. And Dave, what I'd say here is imagine a world right now, in which, you know you trusted that the data that you gave to companies or to the government, was protected and that if you changed your mind and you wanted it back that they would delete it or give it back to you. Can you imagine how much more quickly we would have solved getting a COVID vaccine? Can you imagine how much data would have been available to pharmaceutical companies to actually develop a vaccine? Can you imagine how much more quickly we would have opened the economy? The thing is companies can't solve every problem that they could for a customer because customers don't trust that the data is going to be used correctly and companies don't know how to use it in that way and ethically. And that's what we're talking about when we say getting beyond compliance which is we want to enable our customers to use the data in the best way and most ethical way to solve all of their customer's problems. >> Okay, so I ask the elephant in the room question. If you asked most businesses about personal information, where it's stored, you know who has access to it, the fact is that most people can't answer it. And so when they're confronted with these uncomfortable questions. The other documents and policies that maybe check some boxes, why is that not a good idea? I mean, there's an expense to going beyond that but so why is that not just a good idea to check it off? >> Well look, a lot of companies do need to just check it off and what I mean, get it right, make sure you label and the way we've thought about this is that when you're building on a backbone like AWS, it does give you the ability to buy a lot of services quickly and scale with your company. But it also gives us an ability to comply faster by leveraging that infrastructure to get compliant faster. So if you think about it, 20 years ago whenever I wanted to buy storage or if I wanted to buy servers and look we're a company that built in the cloud, Dave it would have been very difficult for us to buy the right storage and the processing we needed, given that we were starting. But I was able to buy very small amounts of it until our customer profile grew. But that also means my data moved out of a single hard drive and out of a single set of servers, into other places that are hosted in the cloud. So the entire tech stack that all of our customers are building on means they're distributing personal data into the cloud, into SAS platforms. And there's been a really big move through integration platforms as a service to allow you to spread the personal data quickly. But that same infrastructure can be used to also get you compliant faster, and that's the differentiation. So we built a platform that enables a company to inventory their systems, to track what they're doing in those systems and to both create a compliance record faster by tracking what they're doing inside the cloud and in SAS systems. And that's the different way we've been thinking about it as we've been going to market. >> So, okay. So what actually do you sell, you sell a service? Is it a subscription? >> Yeah. >> And AWS is underneath that, maybe you could put down a picture for us. >> Sure, we're a cloud hosted software as a service. We have two core offerings. One is the WireWheel Trust Access Consent Solution. So if you go to a number of major brands, and you go to their website, when they tell you here's the data we're collecting about you, when they collect your consents and preferences, when they collect a request for data correction or deletion of the data, all the way from the request to delivery back to the consumer, we have an end to end system that our customers use with their customers, a completely cloud hostable in a subscription. So enables even very small startups, to build that experience into their website and into their products, from the very beginning, at a cost efficient point. So if you want to stand up a compliant website or you want to build into your product that Trust Access Consent Solution, we have a SAS platform, and we have developer tools and our developer portal to let you do it quickly. The second thing we do is we have a privacy operations manager. So this is the most security center but for privacy operations. It helps you inventory your systems, actually create data flow maps and most critically create compliance records that you need to comply with, you know the European law, the Brazilian law, and that whole spectrum of U.S. privacy laws that you showed a few minutes ago. And those are the two core offerings we have. >> I love it. I mean, it's the cloud story, right? One is you don't have to spend a millions of dollars on hardware and software. And the second is, when you launch you enable small companies, not just the biggest companies you give them the same, essentially the same services. And that's a great story. Who do you sell to Justin? What does a typical customer engagement look? >> Yeah, we, in many of our customers and in the AWS say startup environment, you often don't have companies that have like a privacy officer. They often don't even have a general counsel. So we sell a package that will often go to whoever is responsible at the company for privacy compliance. And, you know, interestingly Dave in some startups that might be a marketing officer, it might be a CLO, it might be the CTO. So in startups and sort of growing companies, we've put out a lot of guidance, and our core WireWheel developer portal is meant to give even a startup all they need to stand up that experience and get it going, so that when you get that procurement imagine you're about to go sell your product, and they ask you, are you compliant, then you have that document ready to provide. We also do provide this core infrastructure for enormous enterprises. So think telecoms, think top three global technology companies. So Dave, we get excited about is we've built a core software platform privacy infrastructure that is permanently being used by some of the largest companies in the world. And our goal is to get that infrastructure at the right price point into every company in the world, right? We want to enable any company to spend and stand up the right system, that's leveraging that same privacy infrastructure that the big folks have, so that as they scale, they can continue to do the right thing. >> That's awesome. I mean, you mentioned a number of roles of marketing folks. I can even see a sales, let's say sales lead saying, okay we got this deal on the table. How do we get through the procurement because we didn't check the box, all right. So, let me ask you this. We talked a little bit about designing privacy in a and it's clear you help do that. How do you make it, you know fundamental to customer's workloads? Do they have to be like an AWS customer to take advantage of that concept? Or how did they make it part of their workflow? >> Yeah, so there's a couple of critical things. How do you make it part of the workflow? The first thing is, you go to any company's website right now, they have to be compliant with the California law. So a very straightforward thing we do is we can for both B2B and B2C companies stand up an entire customer experience that matches the scale of the company that enables it to be compliant. That means you have a trust center that shows the right information to your customers, it collects the consents, preferences, and it stands up with a portal to request data. These are basics. And for a company that's standing up the internal operations, we can get them app collecting that core record and create a compliance record very fast. With larger companies, Dave you're right. I mean, when you're talking about understanding your entire infrastructure and understanding where you're storing and processing data it could seem overwhelming, but the truth is, the way we onboard our customers is we get you compliance on your product and website first, right? We focus on your product to get that compliance record done. We focus on your website so that you can sell your product. And then we go through the rest of the major systems where you're handling personal information, your sales, your marketing, you know, it's like a natural process. So larger enterprises we have a pretty straightforward way that we get them up and running, but even small startups we can get them to a point of getting them compliant and starting to think about other things very, very quickly. >> And so Justin, you're a government so you understand big, but how I talk about the secret ingredient that allows you to do this at scale and still handle all that diversity, like what we showed in that graphic, the different locations, different local laws, data sovereignty, et cetera. >> Yeah, there's a couple things on the secret source. One is, we have to think about our customers every day. And we had to understand that companies will use whatever their infrastructure is to build. Like you've seen, even on AWS there are so many different services you can use. So number one, we always think with an engineering point of view in mind. Understand the tools, understand the infrastructure in a way that brings that kind of basic visibility to whoever it is that's handling privacy, that basic understanding. The second is, we focused on core user experience for the non-technical user. It's really easy to get started. It's really easy to stand up your privacy page and your privacy policy. It's really easy to collect that and make that first record. The third is, and you know, this is one of those key things. When I was in the government, I met with folks in the intelligence community at one point day, and this always stuck with me. They were telling me that 20 years ago, you know to do the kind of innovation that you have going on now, you would have had to have had a defense contract. You would have had to have invested an enormous amount of money to buy the processing and the services and the team. But the ability for me as a startup founder, to understand the big picture and understand that companies need to be compliant fast, get their website compliant fast, get their product compliant fast, but build on a cloud infrastructure that allowed me to scale was incredible. Because it allows us to do a lot with our customers that a company like ours would have been really challenged to do without that cloud backbone. >> Love this, the agility and the innovation. Last question, give us the company update Justin, you know where are you? What can you share with us, fundraising, head count, are you generating revenue? Where you are? >> Oh yeah, we're excited as I mentioned, we are already the privacy platform of choice of some of the larger brands in the world, which we're very excited about. And we help them solve both the trust, access consent problem for their customers, and we help with the privacy operations management. We recently announced a new $20 million infusion of capital, led by a terrific venture capital fund, ForgePoint Capital. We've been lucky to have been supported by NEA, Sands Capital, Revolution Capital, Pritzker Capital, PSP. And so we have a terrific group of investors behind us. We are scaling, we've grown the company a lot in the last year. Obviously it's been an interesting and challenging year with COVID, but we are really focused on growing our sales team, our marketing team, and we're going to be offering some pretty exciting solutions here for the rest of the year. >> The timing was unbelievable, you had the cloud at your beck and call, you had the experience in government. You've got your background as a lawyer. And it all came in, and the legal come into the forefront of public policy, just a congratulations on all your progress today. We're really looking forward to seeing you guys rocket in the future. I really appreciate you coming on. >> Dave, thanks so much for having me, really enjoyed it. And I look forward to seeing you soon. >> Great, and thank you for watching everyone is Dave Vellante for theCUBE on cloud startups. Keep it right there. (upbeat music)

>> Live from Bahrain, it's theCUBE, covering AWS Summit, Bahrain. Brought to you by Amazon Web Services. >> Okay, welcome back everyone. We are here live in Bahrain for Amazon's Web Service Summit in the Middle East, really built around the big announcement around their region coming which would open up in Q1 2019. And Amazon full force here and really bringing together a combination of cloud-computing, cloud-native, together with the community and entrepreneurship here. And of course we wanted to save the best for last of the day interview, the entrepreneurs themselves are going to tell a straight scoop what's happening 'cause it's a lot of action here. Alharith Alatawi, who is the CEO of ONEGCC and Zaman Zaman, founder and CEO of Skiplino. Welcome to theCUBE. Thanks for coming on. >> Thank you for having us. >> Thank you for having us. >> So I got to say, I was watching you guys yesterday in your little, and then Bahrain, you're on your best behavior. You didn't chirp too loud, but I can see the energy in the entrepreneurs. You know there's real entrepreneurs in the room when you can see the energy, right? And all the executives were in there, and you've got the Amazon, so you're on your best behavior banging your fists on the door. You guys are doing some good work, so congratulations. >> Thank you very much. >> So what's the real deal? What's it like here? I mean I know it's tough to get access to capital, but the government's bringing some capital to the table, there's momentum, there's opportunities. What's the straight scoop here? >> So for the past three years, when Start-up Bahrain started, there's been tremendous support from the government because they really want to see this, what they're calling the Fourth Industrial Revolution, they want it to happen. They're pushing for it. They're pushing technology start-ups. And we were really blessed to be, I mean to have started just a few months before that, so we're riding an amazing wave. We've been getting a lot of support from Tamkeen, a lot of legislation support from the government, the EDB obviously have been doing a massive job in trying to support us, getting us business. And I mean since we started til today, we've at least doubled or even tripled the amount of clients we have. And there's a lot of attention now to technology start-ups. And I think as a growing sector, Bahrain, we're really reaping the fruits of it. >> And what is your start-up, ONEGCC? Just take a minute to explain what your start-up's doing, how many people you've got going on, the stage of the opportunity. >> So before I founded or co-founded ONEGCC, I was in an investment firm, and one of our investments was in Saudi. It was called a mega-recruitment company. And what we were trying to do is, we had 500,000 work permits. We had to bring a bunch of people and start outsourcing them to companies, but the Ministry of Labor still wanted us to maintain Saudization within these companies that we're working with. And it was a very tough challenge trying to find the right GCC nationals, the right Saudis. I mean 40% of them hold degrees in Humanitarian Islamic Studies, so how do you place all of these when most of the jobs that are being offered are in construction, retail, and other services? So that's when we started ONEGCC. We said you know what, we'll hire people based on skills rather than their job titles or academic background. And that's really where we started ONEGCC. >> So it solves your own problem? >> Exactly. >> You had a little pain there. >> Well today it's our own problem. >> Yeah, now you have a bigger problem. It's called growth. >> (laughs) Yeah, but tomorrow it's going to become a global problem with AI and smart machines wiping out almost maybe 70%. >> So how many people involved in the start-up? What's the stage, would you call it? >> So today we have 18 employees. We're still early stage, but we're growing as well as we can. >> Great. Tell us about your story here. >> Well, mine was a multi-lingual intelligent queue management system. So we realized there was a gap in the market. >> First, explain what a queue management system is, and remember 'queue' is not an American word. That's an English word, or international word. Queue is 'line' they call it in America. >> Okay, let's say line management. >> But we're talking about physical standing in line at the bank. >> Yes. When you go there, you actually take a token and wait. So we realized it was a problem not only in Bahrain. It was a global problem. What we did was, we went to investigate the issue. How it started was, I went to a bank a day before I traveled, and I had to wait for one hour and forty-five minutes just to clear a check. So I found that not acceptable. So what we did was go study the markets. And we realized that was like three or four players controlling the market for the past thirty years. Some people tried to do it cloud-based, but they didn't get it right because they didn't cater to those segments, which is the large B2B clients that need to scale or have a large number of branches. So when we decided to go and build it on the cloud, we realized that there is no performance management on each agent that is live and was streamed. So when we built the reports, we realized that most of it is bottlenecks that can be solved with AI or machine learning. So we incorporated that into Skiplino. Now Skiplino has around 2,500 companies from around the globe in 196 countries. And it's now in 69 languages. >> That's amazing. How many people in your opportunity, working with you? >> Including founders, we're around 15. >> Fifteen, great. Well congratulations, and one of the things I wanted to kind of get here while we're broadcasting around the continent and around cloud is, I live in Silicon Valley, so everyone's got the entrepreneurial bug going on, but you have successes and failures. That's the way it works. You've got to try something and hit the homeruns once in a while, but you got to get a couple base hits. It's really hard. I mean people don't understand how hard it is, right? If they've never done it, it's hard as hell. So, but having the ecosystem support is key, but Start-up Bahrain is doing some good work with EDB. What is the key requirement and what's the need? Where is it working, are you guys seeing on the ground here? Because the community's there and that's a check. That's hard to do. I mean robust entrepreneur community's good, and there's money. So now you've just got to fill in the blank. What is the cloud going to bring you guys? What are you guys hoping for? What do you want to see? >> Of course with the cloud, the best thing that comes with the cloud is scalability, for us. In effect, we're removing the unpremised queue management systems businesses, but the good thing that's happening in Bahrain, and around the GCC too, is ministries and governments are more receptive for additional transformation, and they know that's the only way to keep up. So actually we're the first cloud-based service the Bahraini government used. >> And you're using Amazon now? >> No, (laughs) we're actually a Microsoft concept partner. >> Oh, okay. >> We're the first. >> Are you using Azure? >> Yes. >> Okay, makes sense. Great partner. >> Because we usually deal with banks and telecoms. Microsoft always has a foot in the door there, but we are thinking of having an AWS structure, too. >> It's okay, use it here. It is what it is, a multi-cloud world we're living in. How about your solution? >> So actually we were in the first cohort of C5 Accelerate, which is a program supported by AWS, so we are on AWS, and obviously for us, as a start-up, setting up in the beginning, we have limited resources, and setting up on the cloud just makes it so much easier. >> Yeah, a no-brainer. Not a decision. >> Exactly. >> You got to go to cloud. If you do a start-up and you're not on the cloud, you're spending too much cash. >> (laughs) Exactly. >> It's just the way it is. It's the dumbest thing you should ever do. Unless there's a prototype and you want it next to you, like a puppy and a dog or whatever pet, kind of thing, a security issue. Other than that, there's no reason. >> And it's faster to set up. It's easier for us to reach a wider audience. When we do reach the wider audience- >> What do you think about the show here? What was your walk-away? Obviously you guys are in the middle of the community. We're here for the first time. I was really impressed and I learned a lot, and I made some observations that I didn't expect to have that were really positive. It was a good experience for me, but you guys live it every day. Amazon's in town. There's good dynamics going on. What's your impression? >> Impression on what? >> This show, Amazon's presence, the community coming together. Everyone came here from the gulf states. >> I think one of the main things that we needed to happen in the system is that mind shift. So corporates to start adopting start-up technologies, and for investors who are used to investing in traditional investments and real estate to start actually investing in start-ups. So I think AWS really helped in that mind shift. I think the work that EDB is doing also is helping that mind shift. Now we're seeing more angel investors who are interested in getting into the tech start-up space and more corporates are willing to adopt our technologies, even though they're fairly new. >> Your thoughts on the show? >> It definitely shined a spotlight on Bahrain. Getting Amazon to open AWS in Bahrain is, first of all, we're getting a lot of talent that's going to come in and be trained to set up. So it's a huge- >> It's like you guys are standing around. The metaphor, I'm imagining, you're standing around, you're working on some things, you're hustling, you're scrapping, you're smart. And then all of a sudden, a big resource generator just pops down and says, hey entrepreneurs, I was built for you. >> Yeah. >> And you're there and now you're present at creation. And when you're present at creation of a movement that has this much growth because let's face it, this is going to be growth, and you guys are going to be the leaders. >> Yeah. >> Hopefully. >> So you got to pay it forward. You have big responsibilities. >> Hopefully. >> And you going to make some money along the way, too. I mean, you know the old expression. >> No pressure, huh? (laughs) >> You know the expression, "Hang around the barber shop, "you'll get a haircut." So this is, "Hang around the cloud, "you're going to create some value." So you've got to capture it. So this is the dynamic that I see as an entrepreneur. I was like, damn, if I lived here, I'd be setting up shop. I'd have five companies going on. I'd be telling all my friends to come on in. >> Because you're in the ground floor right now. >> You're present at creation. We're going to start covering you guys, and do some work with you guys. I'm already convinced. >> It's a big wave, and we're happy to be riding it. >> We're going to collaborate with you guys. I think it's a really unique thing. I mean at this scale, it's unprecedented. I mean this is Amazon. I mean in the U.S. everyone is jockeying for where Amazon's next headquarters is going to be, and literally, people are freaking out, like, come to my state. Because they know, with it come jobs, services. It's like putting up a sports stadium, and all of a sudden there's all these new things around it, right? >> Sure. >> It's going on, >> Exactly. >> So this is going to be a big opportunity. >> It's huge. >> For start-ups. So you guys are going to be reaping the rewards. >> Hopefully. >> You hungry? >> We are. (all laughing) >> You have no idea. >> I'm from California. In America, it's like we call it the wave. Get your surfboard, get out there. A lot of sets coming in. So congratulations. Thanks for sharing. >> Thank you very much. >> Thank you for coming to Bahrain. It's a pleasure having you. >> Looking forward to working more with you guys. >> Definitely a pleasure. >> Thank you, John. >> Okay, we're here in Bahrain. That's a wrap. We're wrapping up with the founders and CEOs. This is the entrepreneurial action here and the signs are all pointing towards growth. Amazon Web Service is going to bring cultural revolution, economic, society, people, all going to be coming here, for the region, not just Bahrain, but all around the region. I'm John Furrier with theCUBE. Thanks for watching.

(upbeat music) >> Live from Toronto, Canada, it's theCUBE, covering Blockchain Futurist Conference 2018. Brought to you by theCUBE. >> Hey, welcome back everyone, here's theCUBE live here in Toronto, Canada in Ontario for Untraceable presents Blockchain Futurist Conference. I'm John Furrier here with Al Burgio, Julie Lyle for the wrap up of the show. Special guests, industry legend Al, serial entrepreneur, Julie, CMO, Barnes and Noble. >> (laughs) >> Great career you've had and you're here new to, first time, we're going to have these big events. At the wrap up we try to get a handle on it and I think the big story here, for me at least, was, during this week, you got a futurist conference, while the price of crypto was plummeting to an all-time low for the year. Yet everyone's upbeat, 'cause they're talking about the future, not about prices. This has been a big part of what we see, build out durable companies, real entrepreneurial activity. Sure, they want to make profit. People scrounging a little bit here and there but most of the time upbeat. >> It's hard to judge things or understand things from afar, John, and people tend to look at prices all day long but that doesn't necessarily give you an indication of what's going on with blockchain technology with some of the organizations out there. The team at Untraceable by far a leader, not just in Canada but internationally with people that are able to try out the entrepreneurs and what have you and it's events like this with just a couple days you get yourself brought up to speed and keep your finger on the pulse. >> Big names. >> Yeah huge names. >> And a futurist event, you got to have some players, some whales on the money side, check, got whose actually inventing the future, entrepreneurial hustle, pitch competitions happening, so all this is blending together. Julie, your perspective, first time seeing a crypto culture community, what's your observation? >> Well I would echo what Al has said about the event itself, it was really well organized and what I was impressed with, surprised actually, but impressed with was the combination of both the technologists as well as the investors and those that are trying to understand how to build these commercial communities and commercial applications out. For a marketer like myself, it's difficult enough to see around corners, but to understand this technology and to have people here who are really trying to target it at solving a specific real-world business problem, it seems like a natural extension of the march on towards bigger and greater, more powerful communities. >> And the technology is interesting, because in previous jobs you've had, you've innovated with data, real-time user data, user experience. Now the shift of token economics potentially could have a huge slingshot advantage to create new opportunities, instrumentation, targeted experiences. Seeing that big time here but the plumbing's not yet in place. It's like the roads aren't paved out. When is blockchain going to be good? >> Yeah, so everyone, there's a clear sentiment: blockchain's the future, the visions are amazing. Ironically, the name of the conference is the Blockchain Futurist Conference and so you have some visions of this that are maybe five to 10 years out, but many of what others are working on, it's the here and now, right? >> Yeah. >> You have opportunities that can demonstrate product market fit today. Others maybe within the next 24 months and they're working hard to do that, fostering their communities of early adopters, businesses perhaps, consumers. In the market in general there's this concern, when's the use going to happen. Quite frankly, we're seeing early stage projects, companies going to market extremely quick. Normally this is the stuff that private companies do. You don't hear the successes and failures; most fail. >> Irrational exuberance certainly happening, going on, but that's ending, you're starting to see that with some of the bubble popping a little bit. It's not so much a mega pop, it's more of a big air coming out of it. But I want to ask both you guys, as senior industry players, because I see couple things happening that are eye level: Token economics is driving a new business model innovation. Blockchain is infrastructure, making things go immutable, having advantages of decentralized infrastructure. And the middle between the two is interoperability. These are the core themes. How do we get all those working together and what would be the benefits of all those working together? Interoperability is a big theme of this event. >> Yeah, it starts with obviously having a forum where you can collaborate with like-minded individuals and you're hearing a lot of these conversations happening and getting a sense of what people are working on as well. It's a new emerging technology. In terms of interoperability, I tend to look at integration as perhaps more important than a focus around interoperability, looking at pre-existing systems in the market and really identifying ways where they can slowly, gradually use aspects of or features of blockchain to really start this shift and this movement and this evolution towards web 3.0. >> Julie, your observations about business model innovation, opportunities that marketers and senior people should be thinking about, mindset-wise? >> Loyalty, obviously, would be a great application, but I think there's far more sophisticated business models around actually, again, the communities, the power of networks, right, and artificial intelligence, blockchain and just what the internet and technology is doing to drive those communities and to empower those consumers. That's where this is headed. It seems to me like a very natural extension. I would also say though, that there's a lot of work to be done in corporate America, private or public businesses. There's a lot of infrastructure to build that interoperability and to make it a seamless experience that will either drive value and adoption or won't, and we've seen that with other technologies fail as well. >> We've seen the same classic adopts, cloud computing, same thing >> Absolutely. >> Amazon, no one's ever going to use it. Oh my God, let's make it consumable and easy. Boom, usage goes up. >> Absolutely. >> Same kind of thing going on here. >> Yeah, user interface is evolving for all things blockchain. >> Alright, guys, thanks so much for coming on. Final predictions, you want to dare make a prediction, Al? >> Before a prediction, one of the things I'd really like to highlight for this event really was having the opportunity to share the stage with someone like Larry King. >> Take a minute to explain what happened. Larry King, the legend-- >> Legend. >> Was here, explain what happened. >> The CNN Larry King. We had fellow legends on the stage and I was humbled to be in their presence. Larry King really was here. He had the opportunity to interview some of the brightest minds in blockchain and in a lot of ways help bring legitimacy to this event, let along the space. Conversations that we'd hear in the hallways of people having conversations with people that they know and sharing with them that they were attending this event and oh, is it blockchain, is it bitcoin, you're going to one of those conferences and then mentioning that one of the headliners was Larry King, is all of a sudden-- >> What was he like, what was your impression of him? Certainly getting up there but-- >> I would say it's exactly the Larry King we know. His questions were phenomenal, really engaging and he knew how to direct those questions. Each question he had for the right fellow attendee on stage. It was awesome. >> Awesome. Well, congratulations, a great job. That's a wrap here, live in Toronto, Canada in Ontario with the Futurist Conference CUBE coverage. Special guests, Al Burgio, Julie here at theCUBE. Thanks for watching, see you next time. (upbeat music)

>> Announcer: Live, from Washington, D.C. it's CUBEConversations with John Furrier. >> Hello, everyone, and welcome to special on the ground here with theCUBE in Washington, D.C. I'm John Furrier, the co-host of theCUBE, and co-founder of SiliconANGLE, as we explore the disruption in Washington, D.C. with cloud computing and all the hot stories we have Timothy Kotin who is the founder of SuperFluid Labs. Thanks for joining me today. >> Thanks so much, John. >> So you guys are doing some pretty disruptive stuff, obviously, societal change, and ventures for good. Social change is a big part of the stories we're covering. You're in the middle of it here at PeaceTech Accelerator. We're here at the United States Peace Institute. What's your story? >> Thanks for having me. SuperFluid Labs, my organization, is a data analytics firm working in Africa. What we do is we help small businesses to unlock their potential using the power of data. For some organizations, this means being able to deliver essential services to millions more people, so for some organizations, it means increasing revenues, and for some organizations, it means understanding opportunities for greater efficiency and productivity. >> Y'know, PeaceTech Labs and PeaceTech Accelerator as part of this global movement where people want to apply AI for good, data for good, and in some cases good is just business, right? Economists, economies are thriving with big data and cloud. You guys are are using the cloud to bring new business models to Africa, to start. You're going to land and expand and take over the world. What's the key thing for you? >> Great, thanks. So the key thing for us is really that in the last few years, there's been an explosion in data, globally. 90% of the data in the world was created in just the last two years, and this presents a huge opportunity to unlock impact for businesses, and so some of the clients that we work with, for example, one of our clients is providing off-grid solar systems for households in sub-Saharan Africa, and they innovate, the innovation, the key innovation behind this model is the ability to deliver energy access as a service, where individuals pay on a pay-as-you-go basis. >> It's interesting, you know, helping society is not just donating money, but enabling entrepreneurs to be successful. You're an entrepreneur, you're here at the Accelerator. How do you get off the ground? I mean, what's great about the cloud is you don't need to provision all these servers, you're using the cloud. How are you guys going from a zero-stage start to getting into the market? What technology are you using, what strategy are you deplyong? >> Excellent. I think innovations such as the cloud have really been essential to our business model. A decade ago, it would have been impossible to launch a business similar to ours, so we use several cloud providers. Obviously, Amazon Web Services is one of them and many others, and what these services have allowed us to do is they've allowed us to focus on the innovation that we are delivering, the solutions that we are delivering, and less on infrastructure, provisions, and worrying about power outages, networking and all of that. >> In Africa, what's the conditions there? I mean, obviously, mobile is everywhere, but there's no telephone lines, and you've got mobile RF flying all over the world. >> Mobile is huge in Africa. I'm going to tell you an interesting stat. In the next three years, there are going to be an additional three hundred million smartphones in sub-Saharan Africa. That's more than the population of the U.S. and that's just in the next three years. >> Huge growth market. >> Huge growth market. >> How are businesses adapting, 'cause this is there you're taking your angle, right, using data, and how does that connect to the proliferation of phones, and how do business folks use it? Is that where you want to target in terms of your solution. >> Excellent question. So, the most innovational businesses that we have seen have taken advantage of access to mobile phones to develop innovative business models. So we have banks, for example, in Kenya, that have developed mobile-only lending and savings products, and they've expanded from 40,000 customers in 2012, to over twenty million customers at the end of last year. >> What's the ecosystem like in Africa, and what's the entrepreneurial cross-over when you go outside the borders of Africa? Obviously, you know in other continents, other economies. How does it all working together? Is it Bitcoin, is it blockchain, is it just standard cloud, how is the emerging landscape in tech impacting the emerging growth inside Africa. >> It's really phenomenonal, and what is most exciting, especially for me, given my experience in the U.S. and in the West and also in Africa is that a lot of the patented technologies, whether that is AI or cryptocurrency, or blockchain, is actually being used to good effect, it's actually being used to deliver essential services in Africa, and you'd be shocked. I was telling someone the other day that when you talk about payments, money-transfer innovation, Africa is really the hotbed for this. >> So you see crypto and blockchain hot in Africa right now. >> It is, and it's being applied in many other use cases beyond payment. So, you have some companies are innovating in land title administration, using that for growth tech and many other use cases. >> Great for property, great for store of value. Talk about your journey here at the PeaceTech Accelerator. How is that working, obviously they're helping you guys, with they're providing a lot of services. Tell us about what those guys are doing. >> Great, well the time here, this is actually the third week of our time here, it's really been very interesting. We've been exposed to mentors who have generously given their time to come and share their experience as other previous or experienced entrepreneurs, or executives that run large corporations, and there's mentoring sessions, we're exposed to investors, we're exposed to a cohort of other similarly minded entrepreneurs. >> That's great because you've accelerated. I've got to ask you a question, as the entrepreneur, you're always seeking for, most entrepreneurs are always seeking for that data edge, y'know, trying to understand the market force, there's all that good stuff. What have you learned here at the PeaceTech Accelerator? What was the something that you said, "Wow, that's something that I never would have gotten." >> Very interesting. So one of the things that has really stood out during my time here is really the emphasis on the fact that business, that delivering great business, or delivering business for good can cut across multiple sectors, I mean, for profit businesses like mine, and I think that is very reassuring, to know that there's a growing recognition globally around the impact and the social good that businesses can deliver. >> So you're using mobile as your backbone for your connectivity, how is the Internet of Things, or IOT, and AI going to be part of your plan? You see that consuming most of your IP and lots of property? >> Very much so. So given the stats I gave earlier on around the growth and explosive growth of data, and the explosive growth of mobile access, that is going to be essential to our IP and our patents, and we thing that's what will really give us the edge in this market. >> Great, final question for you, does D.C. get this? I mean, D.C. certainly is trying to be more global, you're actually here in D.C. at Accelerator, what's your assessment of the Washington, D.C. culture here? >> I think D.C. really gets it. I mean I think D.C. is really the hub of a lot of international development, international outreach by the U.S. government and many other international organizations. So, my being here is actually of the fact that D.C. gets it, and I'm originally from Ghana and from Africa, and we have other members of our cohorts who are flying in from all over the world, and that's the true evidence. >> How's the cloud impacting you? The U.S. is helping you to bring that innovation, what kind of edge are you bringing with cloud computing? >> It's providing speed, it's providing cost-effectiveness, and it's also providing scalability, rapid scalability. >> All right, I'm John Furrier on the ground in Washington, D.C. where all the innovation's happening here, in the United States Peace Institute, we're here with PeaceTech Accelerator, I see great stuff happening, entrepreneurship in social sectors are really happening, AI is a big part of that, IOT, cloud, all the trends are helping out a new generation of start-ups. Thanks for watching. (upbeat music)

>> Narrator: Live from Washington, D.C. It's Cube Conversations with John Furrier. (techno music) >> Hello everyone, welcome to our special on the ground presentations, The Cube coverage in Washington, D.C. I'm John Furrier, the co-founder of SiliconANGEL, the host of the Cube. We are getting all the stories on what's happening with the innovation and entrepenuership in our societal nonprofits and/or innovation in government. We hear Peter Prix is the OneRelief app founder, onereliefapp.com, OneRelief is your venture. You're part of the PeaceTech Accelerator. We're here at the United States Peace Institute in D.C. Tell us about your opportunity. >> Great pleasure. Yes, my name is Peter, CEO and founder of OneRelief, the OneRelief app. What we do is let people like you and me make quick donations, micro donations to disaster relief aid. So after emergency has struck, Hurricane Maria, last year in September, approaching the Caribbean Islands. We all knew about it, we all saw those pictures on TV. And we all felt empathy and wanted to help and wanted to gift, but there's no easy way. So what we do with the OneRelief web app is we let people like you and me easily, with the click of a button, make quick donations that supports certified disaster relief agencies on the ground. >> And you guys are a start up here at the PeaceTech Accelerator. >> Exactly, we're a startup here at the PeaceTech Accelerator. >> Great, well I'm really bullish and I think crowdsourcing has opened up the democratization of giving, which has been phenomenal. But there's some scale issues, now there's ten zillion apps, certainly GoFundMe, we know about those things. They're kind of peer-to-peer. You know, friend has to socialize with that but you know, a lot of folks are wondering, hey, if I donate to that Haiti situation, or hurricane, where does the money go? We heard in Puerto Rico, half the stuff didn't even get there. This is a big fear, cognitive dissonance from the giver. Do you guys solve that problem? >> Yes, so absolutely. When it comes to giving at the moment you can choose between giving to the big players, the big charities that we don't trust, as we know. Or you can go on a platform like GoFundMe and there's actually 12,000 fundraisers for Hurricane Maria. And you don't know who to trust either. So what we do in OneRelief is we provide a marketplace, a platform that is certifying charities with confirmed people on the ground. And when you make a donation through the platform you actually get an update. You get a status notification, help has been embarked, help has arrived in a community. You get visuals, you get video of what's happening on the ground. And you get feedback at the end of the disaster of what has actually been achieved with the money you've donated. >> So you close in the loop from the giver, from the journey of the money to the destination, and seeing the impact of it. >> Absolutely. From the second you press the donate button and you donate and you share a fundraiser, you can see how the money is getting to the country, how the money's being used, what it's being used for, and what the progress of that is, providing you information on the impact of your donation and closing the loop and encouraging you the next time another disaster happens to donate again. >> Create some reliability. You're essentially verifying the end points of where the cash goes. >> Peter: Absolutely. >> How's it going? How far along are you guys? Sounds like a great idea, I think it's an awesome idea. Getting a little dashboard, seeing the impact, make people feel good, know their money's going to work. How do you get this off the ground? You're in the Accelerator, what's the status? >> Absolutely, we're about three weeks away from the launch of the platform, it will be launched on March 1st, so we are in the final push of getting the app off the ground. We have partners, we have contracts signed with, for example, Action Against Hunger, where agencies that have country offices that have been working in the countries that are very often struck by crises for many many years. So it's not that their money goes to a small charity that we've never heard of and are not able to get any accountability information, but it's going to certified agencies that have people on the ground. >> And they're excited by this, it sounds like. >> Oh they are more than excited. It's changing the entire industry. It's rather than the rich people signing big checks it's people like you and me small donations that have an impact of changing the world. And what the OneRelief app is really special and good at it's the speed at what this happens. So, a disaster strikes, within hours, the fundraiser's online on social media and people can donate. >> And one of the great things about us covering Gov Cloud, we've observed that bringing a modern stack like cloud you can actually radically transform these industries that have technology going in some cases so antiquated they don't know what's running on. >> Oh no, absolutely. So, the platform itself is running on AWS and we use serverless cloud technology that allows us to really scale the platform, whether a thousand people donate or a million people donate at the same time it's running on a serverless cloud. >> So you're providing critical infrastructure services for donations , big or small? >> Absolutely, and it's 100% scalable, which wasn't able a few years ago. >> How is the accelerator helping you, PeaceTech? >> Yeah, a really interesting question in multiple ways, both through mentoring support that we get through the partners that bring incredible support and help us really in getting the platform off the ground. AWS helps helps us with setting it up on lambda, that's wonderful. We have C5 who gives us some really interesting support in how we can operate this as a nonprofit with a tech startup mechanism. We have partners like the PeaceTech Lab that helps us really operate as a nonprofit. >> We've been covering AI for Social Good Intel among other partners. Really kind of look at this, not just as a philanthropy opportunity, real change. But what's interesting to us us we've reported on SiliconANGLE is the societal entrepreneurship market is booming in D.C. Can you comment about what it's like here? I mean, is that right? Obviously Silicon Valley where we live you get a lot of the tech alpha tech guys out there. But here it's like non-profits. What old ways of doing things are now kind of becoming more entrepreneurial because of cloud? What's your reaction to that? >> No, absolutely, I think Washington, D.C. Is the best place for us to be at. It's a mix of government, non-profits, and foundations that come in. There's a lot of, actually a lot of young startups coming up, impact startups. There's lots of coworking spaces. And we can really feel it. This is the most conducive environment for us as a startup to grow and to thrive getting support from partners that we need. >> Societal entrepreneurship as a category, I mean, I don't even know if that's the name of it, what do you call it, is booming. Can you share any anecdotes, is it booming, is it just emerging? What's your thoughts? >> Societal entrepreneurship. Yes, what the OneRelief platform really does, it allows everyone to give. It is enabling every citizen in the world to make a quick donation an amount that every one of us can afford. >> Final question, what's your core challenges as you get through the accelerator, look to go to market, is it the partnerships, is it the tech? What are your core challenges? >> I think it's really clearly communicating how OneRelief is different and how it is not like all the other platforms out there, how we are the one stop shop in a marketplace that is connecting people who want to do good with receiving charities on the ground. >> How do you compare and contrast to say these other crowdsourcing and crowdfunding platforms? >> Yes, on the one hand there's the big players, the big charities that we don't trust, that we want to give directly to because we don't know what happens with the money. And there's peer-to-peer fundraising that we don't trust either because they're tiny and we don't know who's setting up those fundraisers. We are right in between. We are a platform that is connecting the donor with a certified charity. >> How about emerging technologies like blockchain which has been very popular in supply chain-like things, because you're basically an end-to-end supply chain of money moving to the end point, the relief or whatever. >> Peter: Yeah! >> Good use of blockchain? No? Are you thinking about that? >> Oh no, absolutely. We actually have an innovation lab that is only purely looking at blockchain from different angles. One of them is for us to accept crypto donations and to be the first platform on the market that is accepting micro donations in cryptocurrency. And secondly, we are looking at blockchain technology and running a hyperledger project at the moment to see how we can accelerate the speed at how long it takes to get the donation from when a person makes it into the receiving bank account on the ground in country xyz in the world. >> A whole new infrastructure wave is coming, you're seeing it decentralize applications and hardened end-to-end apps like you guys. >> Yeah, no, absolutely. >> Well, congratulations Peter. Thanks for joining me here. This is the Cube Conversation on the ground here in Washington, D.C. where emerging markets and nonprofits and just ventures for good are now the new entrepreneurship craze in Washington, D.C. It's the center of the action and with cloud and modern software and blockchain and things of that nature you can make it happen. Thanks for watching. (techo music)

>> SiliconANGLE Media presents ... theCUBE! Covering AlibabaCloud's annual conference. Brought to you by Intel. Now, here's John Furrier... >> Hello everyone, I'm John Furrier, the co-founder of SiliconANGLE, Wikibon, and theCUBE. We are here for an exclusive Cube conversations at the Alibaba Cloud conference here in Hangzhou, China. We're here with Dr. Wang, who's the chairman of the Alibaba Group Technology Committee as well as the founder of Alibaba Cloud, here in the new Museum of Inspiration at the event. Thanks for spending the time with me. >> Thank you for coming. >> So before we talk about Alibaba Cloud and all the goodness going on here at the conference, talk about this Museum of Inspiration. It is new, and it has kind of a display theme. You kind of walk through time. What was the motivation and the inspiration for the museum? >> Yeah, I think the keyword for the museum, inspiration, is really the inspiration that started the museum. I would say that there's two, really the artists thinking about that. The first thing is really about when people, people take a lot of things for granted. One of the goals for this museum, it just shows the people they probably see every day. But just let them, just, wow, okay, that's different from what I thought. I think a lot of people take for granted, but it's really a great invention, a great human contribution to the whole society. I think that one thing is really about that people understand why we got here today. So that's the first thing. The other thing is really about science and technology. When people are talking about science and technology, people often will say, whether we can combine science and technology. But I don't think that's the right way to describe the relationship between science and technology. I would say science and technology, really the two sides of the coin. I really want to see, let people to see two sides instead of mixing together and got one thing. So that's two things that's parallel, just like zero and one. They are two things. When they're put together in a computer, amazing things happen. If you mix the zero and the one, like half something, then it's just not that fun. So I really want to make sure it's the museum of science and art instead of the mixture of science and arts. So that's the one thing. The other thing is really about the inspiration of future. Most of the museum is really about the past, to show how we have in the past, and with less on the inspiration to help people to think about the future. This museum is really, when we think about everything over here, we did talk about the past, but we want to make sure people think about the future. That's the whole idea about the museum. >> And the computer industry is fairly young, if you go back to modern computing. But you kind of have a take here about how technology really is embedded in life. Talk more about that impact 'cause that seems to translate to the conference here at Alibaba, that technology isn't just about the speeds and the feeds, it's about the integration into life. >> Yeah, and I think that from this museum we can see actually I trace back the origin of all the technology. When people are talking about the computer technology, I really want to talk about the computing technology. And then we can trace back, see actually the human is the first signal computing device. Our Mother Nature created for us. If you look at the same things differently, you really can see the origin of that. I think in this museum we talk about two really original things. The first is about the nature origin of the Internet. When talking about Internet, people talk about our current technological infrastructure of Internet. When you look at the human history, how is when people walk, you create an Internet for Earth? You can see a lot of things can trace back. Then, with this kind of trace back, you can help us to think about what's going to happen next. The trace of the original idea is actually very important if you're thinking about technology. >> Talk about the story of Alibaba Cloud. That is not, It's new, Amazon has had it for around, early 2000's. But you guys came right after Amazon, 2009. Still young and growing. How does the Alibaba Cloud take the culture of this inspiration? What are some of the design principles of the Alibaba Cloud? >> Actually I would say the Alibaba Cloud is different from the Amazon Cloud. In the sense we have different vision about the future. Unfortunately though, we are put under the same umbrella called cloud computing by media, I will say that. So we are different, in the sense when the Amazon, actually I show great respect to Amazon. When Amazon started cloud computing, they are really talking about the utility. They're talking about how to cut the cost down. So basically, they start with the low cost of IT infrastructure. That's what I understand. When I started Alibaba Cloud, we know that actually cost is important for sure. But we know that actually the computing part is more important than the cost if you're thinking about the big data era. We started with thinking it's the acentric cloud computing. When you look at our first brochure and we put those words over there. That's almost nine years ago. We called it acentric cloud computing. Instead of the IT-centric cloud computing. This actually, it's not just an idea difference. It's actually, eventually, influenced of the underlying technology infrastructure. Our whole underlying technological infrastructure is designed for the data, instead of just for the IT deployment. >> Jack Ma was talking about this industrial revolution, this digital transformation. What strikes me is you guys have that same art and scientist dynamic, art and science coming together, reminds me of the Steve Jobs technology liberal arts thinking that spawns new creativity. Certainly the iPhone is a great example of that as one of the many things. But now the new generation is coming together. You have a big artist focus here at the event. Music festival, not just technology. How is that part of the focus at the event here? What does that mean for new developers? >> I think it's really the crossing behind that. If you're thinking about technology and now e-commerce, what's really the one thing behind that that's really changed the way of peoples' lives? Computing in that sense, computing is not just technology. It's really something that changes the way of life of every people. I think the e-commerce change the way of life of every people. In that sense, they are the same. If you look at the peoples' lives, they won't just live on technology. They won't just live on the arts. They need a life, love means everything. By nature, we have to make sure as consumers, they need something more than just one thing. I think we are very lucky we understand that. If you're thinking about the young people, I will give you a few numbers about this conference about young people. In China, we have a very specific word talking about the young people a couple of years ago. We call the 'badiho'. It basically means the generation born of the '80s. When people talk about 'jodiho', that basically means people born after '90s. And then people talking about the 'leniho' it's basically people born after 2000. I think that most of the visitors for this conference are 'leniho', 'jodiho', and 'badiho'. These are all young, all young people. >> The digital culture. >> It's a digital culture. I would rather use my own word in the book I would say instead of digital. For me, digital generation is already an old generation I would say. I would like to call this the online generation. They do everything online. Even the last generation do a lot of things digital because digital is everywhere. But I want to emphasize it's an online generation. They do everything online. >> Dr. Wang, talk about data. You mentioned that's the key ingredient, the fuel for innovation. That's impacting the city brain project you guys are doing. Talk about the city brain and the role of data and how that's impacting the societal users out there certainly here in China, the traffic is crowded. This is just an example of what else is out there. >> Okay. City brain actually it's, again it means different things based on the perspective. One thing that's probably important is the data. This is first time actually I think instead of using the big data, it's better to using what I call the data results. It's a better word than big data. I think the one fundamental thinking for the city brain is we find a human army. Humans finally realize actually that data results is the most precious resource for the city, instead of land and water supply. Because we already know that the land is limited. The water supply is limited. This is very important. It doesn't view data as a non-essential thing. It's just a part of your IT system. We finally realize that data is part of the city instead of part of your city IT system. I think it's a leap frog thinking, at least for me. When it got to that, and you realize that today all the existing IT systems cannot actually really embrace the data. IT system is just to support the people doing the work they used to do. And then you realize we need an infrastructure to really make the value from the data. Just like we have water supply for the city, then you can use the reservoir. Otherwise, the reservoir is useless for the city. I think city brain is just like a water supply system for the data. The city eventually can consume that. We start thinking it's a new infrastructure for the city just like water supply system, just like power grid, just like any way system. That's how we're thinking about it. This is the first thing. The reason we got to the traffic system is this is the problem every city has around the world. From my yesterday's presentation, I just joked about we build two roads for the city, which is too many. I was thinking a lot of people realize it. That's why Boston had the project. They want to get all the roads under the surface. Under surface. But it's still a road. It's still expensive. You know how much money they spend just to move all the roads. >> The big dig, I remember, that was the-- >> Yes, that's a big dig. I don't think that's, that's good for the transportation system, but I don't think that's the number one way for the growth of the city. I think probably most of the city don't have the money to do that. What the data city brain wants to do whether we can take the resource of data and we can optimize every aspect of the city so we can use less resource to support city growth. When we start with the traffic, it's just to make sure, you know that when we use the data to optimize the traffic lights, the idea behind that actually we use the data to optimize the time. How to just read the time. It's not just lights. And then if you're thinking, when we show the eventually, if you have enough data, then we can have less roads in the city but still got the same. >> So the Internet of Things is the hottest trend. 0bviously machine learning and artificial intelligence are part of that, and the cloud powers this new edge of the network, and the data has to flow. So the question that a lot of technologists who are architecting these solutions ask is how do you make the data go at a very low latency? That takes compute power. That takes a lot of technology. How does Alibaba Cloud think about the architecture? Obviously you have a strategic partner like Intel, Obviously with a lot of compute power. You got to think differently around making the data move. If it's like water, it needs to flow. So real time is really important, but self-driving cars, real time is down to the millisecond, nanosecond. How do you think about that as a technologist? >> I think the, if you go back to the Internet of things, I think it's still the Internet. I would say eventually, if you're thinking about the word cloud computing and people use edge computing and people talking about Internet of things. For me, it's just the computing of the Internet. Cloud computing is the computing of the Internet and edge computing is computing on the Internet. Even the IoT is the computing of the Internet. If you're talking about the data, I think eventually it's really about the data on the Internet. It's not data on the sensor. It's not data on the cloud. Basically it's data on the Internet. I would expect eventually the Internet infrastructure will be improved significantly. It's not an improved cloud. It's not improved edge computing. Or it's improvement of the IoT. But it's really, >> Together. >> it's together. >> So Intel, I was covering them, Mobile World Congress earlier in the year. And obviously five G. You need the mobile overlay, that's super important. You also have the end-to-end inside the cloud. Obviously Intel is a strategic partner. Can you talk about the relationship you have with Intel? And also your philosophy, technically speaking, with the ecosystem? Because it's not just Intel, it's everybody. There's a lot of people here at this event. American companies as well as international companies who are now going to be part of your ecosystem. >> Actually the, we certainly have a very good relationship with Intel. I think we share in some sense the same vision. I think that the number one thing is really about people learning about how important the computing is. For me, the Intel is not that, a chip selling company. Intel is really the provider of computing power. That's what I understand. And we can expect eventually the whole ecosystem is really about who is going to provide the computing power. Who is going to provide the infrastructure to make the data? Instead of just equipment supply, eventually the need for computing, and the need for data, will be the challenge for every company, including Alibaba Cloud. We are not, we are not immune from these challenges. We will feel the same challenge. What we want to do is really make sure that with all these partners, provide enough computing for the next 10 or 20 years. We want to make sure that there's enough data flow for the next 10 years. In that sense, it's not the traditional ecosystem as like you do this and you do that. It's basically how we can work together to really make sure we have the challenge for the data and computing in the next 10 years. >> Yesterday we covered the news that you guys announced 15, building and R&D over the next three years, which is a lot of money. Also it has a very international and global view. Academics with younger folks. Alibaba Cloud is going to be a part of that, I'm assuming. I'd love to get your thoughts on how you see that intersecting. But the question for you is the cloud world today is moving at very, very fast speed. We're seeing Amazon, for instance, has been the best in terms of new announcements every year. Not one or two, like a ton of announcements, a lot. How are you guys going to continue to keep the pace? To move faster because the city brain is a great project, but it's going to have more evolution. It's going to move fast. How are you guys keeping up with the pace? >> I think the only way, that's not just for the next 10 years. Actually when I started Alibaba Cloud, we take the same philosophy. Actually the user moves very fast than us. If you look at the users in China they move very fast probably than anywhere else around the world. If you use the city brain project, I would say city brain project is basically tell the people, we need the computing power more than any other task. You really can see that. People want you. If you can't satisfy their demand, then somebody else is going to do that. It's not something we want to move fast but >> You have to move fast. >> You have to move fast. That's why the China is special. I want to say China is not just a place for the market. China is the place that pushes you to move faster. That's more important than market size. >> You mentioned data technology and information technology kind of transferring to a new world. Software is also a big part of it. Software you have to compute, obviously with Intel and the relationships you have. But software is growing exponentially. Certainly in open source, we see Cloud Native Foundation here. They'll probably have Linux foundation. Open source is going to grow exponentially. Most of the code will be shipping. But you have more data growing exponentially. Software is eating the world, but data is eating software. That means data is greater than software. If you look at it that way, that's super important. As the new architects, you and I were just talking about how we've in the industry for a while. You certainly have an amazing career from Microsoft now at Alibaba. A new generation of architects and developers are going to create new innovations around this dynamic of data. What's your advice and how do you view that if you are 21 years old again right now and you were going to jump into studies and academic and or field. It's a whole new world. >> I think there's probably two suggestions. Not necessarily for the young generation, but I would say it's just a suggestion for the young generation to push that habit. The first thing you mentioned about the data eats software. Well, I would put it in a different perspective. I would say for the last generation, the last two or three generations, I would say the computer era, we are really talking about the computer software. That's pretty much in everything. For this generation, I would say we are talking about computing plus the data. That box is not important, but the computing power is more important. For the computing era, the box is important. >> There's no box. It's the world, it's the cloud. >> That's one thing. The implication for this, I want the young generation to push is, then we need the new infrastructure. Thinking about the build as a great vision, got to have the computer in every home. That's infrastructure. Today when you are in the computing process data era, the infrastructure is not there. I think the vision for the Alibaba Cloud is make sure that we have this infrastructure for the next 10 or 20 years so the young generation can take advantage of that and to do that innovation and inventions, just like computing in every home. >> That's very important. I think that also speaks to businesses, how enterprises, I remember my first start up, I had to buy all this equipment and put it into the telephone closet. Now, start ups and small businesses don't need IT departments. This has been a big growth area certainly for Alibaba Cloud. But now all businesses might have a small closet, not a big data center. This is going to change the nature of business. So work and play are coming together. This speaks to the Museum of Inspiration theme here where you can have work and play kind of integrate but yet still be separate in that analog digital world. What's your vision on this new dimension of everything doesn't have to be just digital? You can have an analog life and mix it with digital. >> Actually I was always sad. It's not, the world never has just one side. It always has two sides. The difference is which side is important at a particular time. Just like when people talk about digital and analog, the analog will exist forever. It's hard for you to kill. The question is whether you can find the most beauty from the digital at the same time you can most beautiful part of the analog. I would say that the people, just like when talking about software, people still loved the hardware. And people still loved the touch. The digital has to make sure it looks good. Will it work versus it looks good? I would say we want to make sure people live in a world with two sides, instead of just giving them one side of the world. >> You mentioned people still love hardware. I always say, a car drives but there's still an engine, and people like to understand the engine. There's a maker culture in the United States that's been growing over the past two decades. And now even more accelerated is the maker culture because of the edge and how technology has become part of the fabric of life. How do you see that maker culture being enabled by more cloud services? Because anyone can make a skateboard or motorcycle or a computer or a device now. Powering that with the cloud is an opportunity. How do you view that? >> I would say that eventually, if we have the broad definition of a cloud, I would say eventually, everything the maker makes will be part of the cloud. When talking about clouds, we're really talking about Internet, so every hardware, every piece of hardware will be part of Internet. I would say, if you look at the evolution of the Internet, Internet, it's just a backbone at the very beginning. Actually the first revolution the Internet made is really to make sure that every piece of software is a part of Internet. That's how we got the world wide web. I would say when talking about the maker culture, I would say eventually that every piece of hardware will be part of Internet. So Internet won't be complete without the hardware. In that sense, the cloud is a really essential part of that. >> There's some really interesting things happening here in China that I'm excited about. One of them is the nature of the user base and how close you guys are to that. In the US a similar scale but it's kind of spread over a bunch of other cloud providers. But the interesting phenomenon as data grows exponentially, as software grows exponentially in open source, things are becoming more decentralized. Without talking about the whole initial coin offerings, I know China has banned it and Russia's going to ban it. Other countries are putting a clamp down on crypto currency. Putting that aside, there's still blockchain as a potential disruptive enabler. You're seeing decentralization becoming a new architecture dynamic because you have to support the growth of these devices at the edge. Distributive computing has been around for a while, but now a decentralized architecture dynamic exists. How do you steer that technology direction? >> You have to separate from the the distributive architecture versus its physical location. I would say I like the blockchain idea very much. I think eventually it would be part of the Internet. It's not just something that sits on top of the Internet. It would be very fundamental, just like TCP and IP. This is low level, so this would be part of the Internet instead of standing on top of the Internet. Eventually, in that sense, Internet would be very distributed. By thinking that it's nothing, there's no decentralization exists. You still need, even though physically, it's in one place. >> It's almost decentralized, not 100 percent. >> Yeah, yeah. Obviously this would be different. Without Internet, without new software, that basically, just like PC. PC is really in a single box, and we use all software in a box. We distribute architecture. We could have decentralized, but everything actually is distributed. You still cannot trace that. You put like a meeting. A service in a data center. It's actually distributed over this one meeting service. In that sense, it's completely distributed. >> That server list too is a big trend where if you talk about the edge of the network, you got to move compute to the data sometimes. Or have compute on the edge. So this is going to be continued growth, you see that as well right? >> Yes, but I still think, if you use Silicon as a measure for this computing power, I would say if you can see there's more silicon on the edge, but I would say when we put one silicon on the edge, you probably have to put 100 silicons on the cloud. It's still kind of-- >> It's a relationship. >> It's a relationship, just like our body is very important but the brain consumes the most oxygen. >> It's important what's in the cloud then. You got to have the computing, have those ratios. It depends on the architecture. >> Yes, yes. >> Final question for you is as the folks in Silicon Valley, where we're based, and Palo Alto want to know is Alibaba, what it means to them? If you have a chance to say a few things about what Alibaba Cloud is to America, what would you like to say? >> I would say that actually they would just put the cloud computing aside. Just look at what it really means behind that. I think the cloud, we do have an understanding of what the cloud computing really means. At the very beginning actually, I wouldn't call the company a cloud computing company. I would call it a general computing company. It's really a fraction of what's thinking in China. Again, my comment is not just to view China as the market to sell your product. To view China as the place to inspire having a new product. >> And it's a global world now, the world is flat. >> Yes, just like United States, it's not, it's a place inspired. All the people around the world together to have a new idea. I think the people in China just love new things. They love to try new things. It really can shoot your size of your innovation. >> And it's a global collaboration, it's interesting. That phenomenon is going to continue. You've done amazing work here. Congratulations on the Museum of Inspiration and the projects you're working on. Personal question for you. What are you excited about now? We kind of joke about how old we are now, but the young people certainly have a great future ahead of them. But you have a lot of experience and you're steering Alibaba's technology committee across the group as well as being the founder of the cloud. What are you excited about right now, technically speaking? What's the big, or just impact? What's the big wave that you like? >> I think it's very exciting in a couple of things, three things I would say. The first is really about just look at technology itself. Just like when I described my book, it's really, really exciting in your life if you can see the Internet plus the computing and plus data, cause they're together. Just like you have this engine, you have the airplane, a couple of things, they're together wherever. This is a very, very exciting era. This is not just about a technology era. It's an era that all things happen at the same time, so that's very exciting. That's one thing. The second thing as you read about the city around over here, I think the the Alibaba the Hanzo, it's just a very special for Alibaba, but I think it's special for the other company as well. So this place is very special. Just to give you an idea where you are, this area has the most networked river in the past. If you look at the map, it's like Internet. I would say, all the people over here, just their mindset. It's just on an Internet mindset. Even goes back 100, 200 years ago because the river is the only way for them to travel, for the communications-- >> That's the data back then. >> That's exactly my point, see. If you look at the map, so this is very exciting. The other thing about that the Alibaba, for me, the Alibaba you know Alibaba, we have a very broad opinions. You can feel that. From a technology point of view, that basically means it's the place you can touch every aspect of technology. You have a very slight, very-- >> You have a great surface area aperture to look at impact of life. >> So you think about these three things together. It's hard to say the, you better get excited. >> It's a great time to be in technology, isn't it? Entertainment, e-commerce, web services. >> For me, when I work on the city brain project, it's just the beginning of machine learning. A lot of people, they are fighting for like, when people talk about speech recognition, they are fighting for the last one meter for the speech recognition. But if you're talking about city brain, it's the world. The most big AI project. And it's just the beginning. We just start with the one percent. >> It must be a lot of fun. You got a lot of data to work with. You have real life integration. It's super exciting. When are we going to see you in Silicon Valley? >> I appear regularly to Silicon Valley two or three times every year. We'll probably see sometime early next year. >> Thank you very much for the time, appreciate it. >> Thank you for coming to the conference and coming to the museum. >> Thank you very much for your inspiration. >> Thank you. >> Thank you.

>> Hi everyone, I'm Sam Kahane and you're watching theCUBE, on the ground, extremely excited for our segment here. Wasabi just launched last week on Wednesday. We have their co-founder and CEO with us here today on theCUBE. David, thank you for coming on today. >> Hey, nice to be here Sam. Thank you. >> So, unbelievably exciting. Can you tell the world about Wasabi? >> So if you know what Amazon S3 cloud storage is, you pretty much know what Wasabi is, except we're one-fifth the price and six-times as fast. (laughing) >> Incredible. So, you know, co-founder and CEO of Carbonite decided to start Wasabi. Tell us, why Wasabi? >> Why the name Wasabi? >> Well, the name as well. >> Cause it's hot. (laughing) My co-founder Jeff Flowers, who's one of the great technical geniuses I've ever met in my life, came to me about three years ago, with this paper design for a new storage architecture, and said, "I think we could do something that's going to be far faster and far more efficient in storage than what the cloud providers Google, Amazon and Microsoft are doing," and I said okay, "Well you should go check it out." So he left Carbonite, and we spent about a year doing design work, and eventually we ended up with this design that was so compelling to me that I decided it was time to jump on board, and join Jeff again, and this is this is the sixth company that we founded together since 1980. So we kind of know how to complete each other's sentences. It's been a winning combination, there's been quite a lot of successes there. >> So, I'd love to hear about the vision of Wasabi. >> My vision of Wasabi and cloud storage in general is that cloud storage ought to be like electricity or bandwidth, it should just be a commodity. Right now you have all these silly tiers, you have Coldline and Nearline and Standard and Glacier, and these artificial tiers that Amazon, Google and Microsoft have made to try to protect their high price spread. Wasabi is faster than the fastest of them and it's cheaper than the cheapest of them, so why do you need all these silly things in the middle? It's just like electricity, you go to plug your computer or your blender into the wall, you don't have three different plugs, one for great electricity, one for so-so electricity and one for crumby but cheap electricity, you know, you just have one. So one size fits almost all needs, and I think that's the way cloud storage is going to be as well. When we get to that, it'll be best man wins, right? The guy with the best performance and the lowest cost is going to win, and we feel we can compete in that environment. >> So a buzzword I've been hearing is 'immutable buckets', can you tell me about that? >> Yeah, so that's the one functional difference between Amazon S3 and Wasabi, otherwise Wasabi is completely 100% plug compatible with Amazon. You can unplug Amazon, plug in Wasabi and all your applications should work, and the other way around too. That's part of being a commodity, right? Your suppliers should be interchangeable. But, immutable buckets is something which really came from our Carbonite heritage. We know from Carbonite that most data loss is not due to failing disk drives and things like that today, it's stupid mistakes, you know people accidentally overwrite or delete a file? It's bugs in application software cause data to get overwritten or deleted. Then you get things like Wannacry, which come in, grabs all the data on your computer and encrypts it. So immutability means if you store data in an immutable bucket, it cannot be altered, and it cannot be deleted. It can't be deleted by you, it can't be deleted by us, and it certainly can't be deleted by a hacker or somebody breaking in from the outside. So, about 10 or 20 years ago, people invented something called the WORM tape, write-once-read-many, that was really one of the first forms of immutable digital storage. Once you put your data on there, that was it, when the tape is full, you take it off, put it in the drawer, and it's safe. That's not a very good system by today's standards, but we've built immutability into Wasabi, so that when you create a bucket in Wasabi, and for those people who don't know about object storage technology, a bucket is like a folder, and an object is like a file, when you create a bucket in Wasabi, you can flip a switch and you can say, "I want to make this bucket immutable for 10 years," let's say, and any time you go in and try to erase or alter any of the data that's been written, you just get an error message, which is what the wannabe virus would have gotten had it tried to encrypt that data. So the only downside of immutability is once you put something in there, you can't go in and clean it up. You're going to be stuck paying to store that data for a long time, but at our price of 0.39 cents per gigabyte per month, I don't think anybody would bother ever trying to clean it up anyway. You know, it's like when's a good time to go empty that U-Haul storage locker? Eh, I'll write another cheque for $40 and think about it next time. (laughing) >> So your tag-on is a hot storage? >> Hot storage, yeah. >> So you launched one week ago, on Wednesday. Tell us about that first week, how crazy was it? >> Well the only thing we did was some PR, so there were a number of articles that appeared about us, and we were expecting maybe 15, 20 companies would come sign up in the first week, do a free trial. But by 48 hours in, we were over 150, and by one more day we were at over 200. And we kind of had to shut down new sign-ups because it was just more than we could handle. We were just worried that we would get overwhelmed. Now we're trying to catch up, we just put more storage online in the last 24 hours, and now we're working through the stack of people. I don't know how many more have come in since then, but it's been a lot, so we're working through that now to give people their passcodes so that they can get on the system, hopefully by this time next week we'll be caught up. >> Well congratulations. >> Thanks, thanks! >> Any last words that you want to leave the people with about Wasabi? >> Well anytime you drop the price of anything by 80%, unexpected things are going to happen. When bandwidth suddenly got cheap, you got Netflix and movies over the internet and that kind of stuff, which people hadn't even dreamed about. I'll be really interested to see what people do with really cheap, fast storage. When you think about all these storage intensive apps like Pinterest, Instagram and things that involve videos and so forth, storage has got to be your biggest cost. And most of these apps are free, so the only revenue you're going to get is going to be advertising. I'll bet there are a lot of business models that just won't work at Amazon's prices, but drop those prices by 80%, and now suddenly you say, "Wow, this could be profitable." I'm not going to invent those apps, but I'm sure that some of the people who are signing up for Wasabi today are thinking about things that didn't work in the old regime, but with commodity cloud storage at these low prices, it starts to make sense. So we'll see, I think it's going to change the world. >> I hope so, and it's going to be exciting to watch. >> Yeah, it'll be fun. >> We'll need to catch up again soon and check back in on the growth. But David, thank you for coming on theCUBE tonight! >> You're welcome Sam, thank you. >> And CUBENation, thank you for watching. (Outro music)

>> Narrator: Live from San Jose, California in the heart of silicon valley, it's theCUBE! Covering QuickBooks Connect 2016. Sponsored by Intuit QuickBooks. Now here are your hosts Jeff Frick and John Walls. >> Welcome back to San Jose, California. We continue here on theCUBE our coverage of QuickBooks Connect 2016. Of course theCube is the flagship broadcast here on SiliconANGLE TV where we extract the signal from the noise and I tell you what, with our next guest, we have a lot of signal to bring you. Scott Cook, the founder and the chairman of the executive committee at Intuit. Scott, thank you for being with us. We really appreciate the time and have been looking forward to this for quite some time once we knew you were going to be on theCube. It's good to have you. >> Good to be here. >> Let's talk about just first off, look at where you are now, right? 30-some odd years. It's been quite a ride I would assume for you. >> Yeah, it started, you know Tom and I got together and then there were two of us and then we eventually had seven of us in a basement. Well they called it the garden level. But the only part of the garden you could see would be the roots and the gophers. (laughter) And then we hit bad times and the things ... We just couldn't get money. We couldn't get sales so we shrunk down to four people. Couldn't pay salaries. It was pretty ugly. And from that, to look at 5,000 people here today. 8,000 employees in the company. When I started the biggest PC software company was 160 employees, and they were huge! Oh these giants! (laughter) >> How do I manage all this? >> Yeah, yeah. >> Well a quote that we've heard a couple of times today. We heard on the keynote stage. About the corporate philosophy of we fall in love with your problems, not our solutions. And is that the driving force you think? I mean, why you've made it through 33 years? >> I think yeah. Yeah, I actually think that's pretty important not just to the success of Intuit and QuickBooks and Mint and TurboTax, but to business in general. My theory is what great entrepreneurs do is they find the intersection of two circles. So think of a Venn diagram and the intersection. One circle is what are people's biggest, most important unsolved problems? Not the problems that are already solved by someone else. Find the ones that aren't solved yet. And then look for the ones that we can solve. Cause you can't solve everything. But look where we can apply the best technologies in the world. What's in that intersection? And focus there. >> And in some of the research to get ready for this. You've talked about really focusing on the important stuff. You gave a great example in that Khan Academy talk about there's really only 1 1/2 things that you should really be focusing on to really move the ship forward. And that was a very great insight. >> Yeah, you know all of of us have the desire to do too many things. You get groups. You've got 10 people in a room, they each have their ideas and it's tempting to shoot at too many targets. And those 10 targets are not of equal importance. You got to go through and kind of rigorously and be disciplined and say what's the 1 1/2 most important? And stay relentlessly focused on that. >> And then how is your role changed? As time has passed and you're no longer the CEO. Now you're chairman head of the executive board. How have you kind of learned to still keep your hands on it but in kind of a little bit more of a distant role? >> Well, first of all, thank goodness for leaders like Brad Smith, Sasan Goodarzi who heads up our small business group, that's really the host of this show. Thank goodness for great leaders like that. So my role's changed a ton. I work really on two areas now which is strategy and coaching our entrepreneurs. So strategy over to Brad and our other leaders. I'm trying to help our leaders see the future and make the big strategic calls. What's really most important? How do we know? And then work with our entrepreneurs. We're a collection of entrepreneurs basically. We've got a couple hundred entrepreneurial projects going on inside the company at any one time. And each one of those is like a little startup. I mean, they've got a customer in mind. They've got a problem they're trying to solve to improve people's lives so fundamentally. And there are challenges. So helping grow our entrepreneurs and then grow the culture around them to allow great entrepreneurs to invent things to change the world and do that from within Intuit with a huge reach to be able to get the inventions out in the hands of millions. And change the lives of tens of millions of people. >> So, over the course of the run of the company, they haven't all been home runs. >> Scott: Oh yeah. >> Right. So how have you learned from those swings and misses? And applied them to the small businesses that you're serving? Who are swinging and missing on a regular basis and you're trying to narrow that margin, right? Trying to make them more successful. >> Scott: Yeah. >> So what did you learn you think maybe through your attempts about that culture of trying basically. >> I think maybe the most important thing really dovetails with what you just said. Early on, when the company was, before we even had our first product out, we'd build a version of it and then we would bring in test audiences of it and have them test it to see if they could figure it out without us saying anything. And they couldn't. So then we'd redesign it and then we'd test again. And then we'd redesign it and test again. Over time kind of lost some of that dedication to running experiments. And it became whose opinion? And you'd build, and it was the loudest opinion in the room. Or the boss' opinion. And that produced a number of failures. Things that just didn't work. Customers didn't buy it. Or they bought it and it didn't it didn't produce the desired effect when they bought it. So the thing I've learned about life and companies is to set up a culture where you make decisions based on fast cheap experiments. That very thing you were talking about. If you got an idea, figure out, okay, what's a leap of faith assumption, let's go try it. And don't debate it. Try it. And then we learned from trying. Oh, a bunch of those don't work. And then we learned from the things. Why didn't it work? And that teaches us something we didn't know before. That maybe the fulcrum, the pivot, to a new idea. And some of those do work or most of it worked. But other pieces didn't. And we learned by doing. Not by debating in a conference room. So to set up your company so that people throughout the company can take their idea and run the experiment. That produces great entrepreneurs and great learning. A continuous stream of learning. I guess the learning begins when you first get real people trying your idea for real. >> Let me follow up. Cause the other thing you talk about is that often comes from the youngest and the newest employees. Which is completely antithesis to a kind of hierarchical structure. Where these are the people that you should be listening and giving them the opportunity within this comfortable framework to do these experiments. >> Absolutely. Sometimes the very freshest ideas come from the people farthest from the boss. Newest in the company. Closest to the customer. But typically in a hierarchy, whose got the least clout? Whose ideas are the least listened to? It'd be the new person, the young person. >> Jeff: Right. >> And so part of the genius of running a company of decision by experiment is that everyone's ideas can be run as an experiment. The boss' idea. The CEO's idea. And the person that's new. We should be testing each of those. Except in a crisis where you got to make snap decisions. And hopefully those aren't very often. You should run the company so that each good idea can be tested, regardless of where it comes from. And then the great thing is, then you get the best ideas from all your folks and they learn from doing. If their idea doesn't work, now they learn from that. Ooh, okay. I thought it was going to do X, it did Y. Why? What didn't I know? That's where learning comes from. Learning doesn't tend to come from the successes, learning comes from the things that didn't work. >> So, I think we've all seen good executives. How they operate. They hire good people, right? That's ... You have a vision and then you hire people who surround that and amplify that vision. So when you're looking for people or when you've been looking for people to work with you. What's that common thread? Or what are the traits that you've looked for the most to think that's a good fit? Or this is the person that I want on my team. In order to carry on this vision to where it's expanded to where it is today. >> Let me break that into two buckets. There are a set of things which are unique to particular career paths. So certain things from engineers might be different than certain things from a salesperson or a marketer or a finance person. So let's set that aside. Let's cover the commonalities. I think there's a few things. When you think about the people you've most loved working with or for. There are people who are great creative problem solvers. Instead of seeing a problem or barrier and giving up or being unglued by it. Can figure out okay, how're we going to solve that problem? And then there's people who are there to serve. Where it's not all about them. I've got a thing that I tell our folks that others won't care how much you know until they first know how much you care. So if one of our speakers today said it. If your first job is to serve yourself you're not going to go very far. Because who wants to work with someone who's self serving? Who wants to buy from a company that's only looking after its own front P&L? Job one is you got to serve who you're serving. The customer or the person of the company who you serve. So we look for people who are really motivated by the outside to try to do right by the customer. I think you look for people who are achievement oriented. Who get stuff done. Who make things happen. Do you want to work with somebody who always needs to be dragged along? No. You want to work with somebody who's pulling you along. Who's getting a lot done. So you go, wow, that person gets a lot done. So I think those are pretty core. Solve the creative problems. Have the passion and energy to serve, do what's right for the customer. And then get a lot done. >> And then you've talked about the curse of success. And avoiding the curse of success. And you guys have done that, obviously. So what are the kind of the lessons to say fresh? This started as a checkbook register and now the future of payments and mobile and the options are just tremendous. Bitcoin, who knows where that's going. So, as the future keeps evolving, how do you stay fresh? How do you keep the team fresh? How do you not rest on your laurels even though you have 5,000 fans walking around San Jose convention center today? >> This is a real challenge for companies. Because success turns organizations. It makes them dumb and slow. It's tempting, the thing I would avoid is it's tempting to look at your achievements. To look through the rear view mirror. And look at boy, how much we've achieved. But that only makes you self satisfied. In fact, with an organization you need to do the opposite. Look to where we want to be. Look to where we should be. And we're here. And then say, well shoot we are not very far. So for example, and I define these in customer terms. For example, we started our first product helped somebody manage a checkbook and pay bills. If you look at it really, the problem of paying bills has gotten worse. It used to be all bills came in the mail. So you had a little physical reminder. Some come in the mail, some you get by e-mail with invoices from some people. Some you go online and find a website. You pay some at a bank website. Maybe you go to the biller, you pay some. You write checks for some. It's much harder now. We have not actually got to the point. When our nirvana is you never worry about a bill. And you're never late. And you're never overdraft. The overdraft rate in the country is around 30% of households have a late payment during the year from which they get fees. And the overdraft rates, the overdraft charges can be $30, $35. We have not solved that yet. We got to look and say with all that we've done, that's what we should have done. So we've got a team working on that right now. Because we got re-focused on it. So we'll be coming out in December with stuff in there. Look at tax. Tax many people would say is one of our best businesses. And it is. Look at all we've achieved. But, look at the reality. People are still spending a lot of time on tax. Who wants to be spending time typing stuff into tax software? Does anybody? (laughter) No. There's not an accountant, there's not a consumer. We haven't solved that yet guys. There are still a hundred million people in the country typing stuff in to systems to do taxes every February, March and April. That's where we want to be. Is ultimately there is no typing in. All that information you have that goes in your tax return goes in automatically. And if you're an accountant, it all goes in for your clients automatically. So that you can focus on the high level stuff and not the drudgery. So, viewed from the lens of really what life should be. What's our aspiration? Our ideal? Keep people focused on that. And it sure has helped motivate us. I mean, we should be finding a lot of money for small businesses. And we're launching, announcing today ways that we help small businesses find more money. We should be eliminating the drudgery of running a small business. Nobody wants to do the book work. Instead, they want to do what they love to do in business. It could be working with clients. It could be the craft of doing the business. It could be selling new business. Every business person has something they love to do. And it's not doing the books. And that yet, people still have to do it. We want to have it on your phone so you don't have to do the books. It's done automatically. And you got a question, boop boop, there's the answer. >> So you mentioned the phone. Is that the next big growth opportunity? Mobile this is top priority with so many different sectors right now. >> Yeah, yeah. It's the growth today. In fact, every new feature and new benefit that Sasan Goodarzi showed today in his keynote address. Every one of 'em, he showed it on a mobile phone. Every one. It's the fastest growing. TurboTax the great consumer business. It's the fastest growing platform by far. So yeah, if you can take stuff off a desktop and put it so automatically that you can just get on your phone, say, okay, yep, do it. >> Right, right. >> Yeah, so that's where we're aiming a lot of our innovation. And these are amazing platforms. A simple example, the fastest growing form of employment in the United States and in fact, in the world is self employed. Where you think of an Uber driver or someone like that. People who work as consultants, contractors, they work for themselves. They've got to keep track of all their business expenses. Or they lose that money on their tax returns. Money out of their pocket. They got to keep track of every individual business expense which of course, they co-mingle with their personal checking, personal credit card. And they got to keep track of every mile they drive for business. And keep it separate with contemporaneous records that the IRS requires with the starting odometer reading, the ending odometer reading, and the destination and what it was for. Well you can imagine that's such a pain in the butt. So many independent business people, freelancers fail. Or they do some but not others. And that's money right out of their pocket. Thousands of dollars they don't get. They should get that they deserve. So we've devised and a team really creative work, QuickBooks Self Employed. It sits on your phone in your pocket. It reads what's coming from your bank and your credit cards and anytime you're stopped at a stop light or you've got two minutes before a meeting starts. You can go through and say oh, that was a business expense, business, business. That was personal, personal. It's that fast. And then you get complete records for your taxes. Oh then mileage. There's lots of software out there that'll track your mileage but it does by pinging the GPS. GPS takes battery. You ping the GPS all day long, what happens? Zhoom. >> Goodbye phone. >> Bye bye phone. So it's worthless. Our guys we launched that. Quickly found out that people stopped using it because it drained their battery just like everyone else. So, three clever engineers. Together with a couple others came up with a really clever idea which we've patented now. And it tracks your location without pinging your GPS all day long. So it doesn't drain your battery. So now you had complete records. It can detect when you're driving and where you started, where you finished. How many miles. Keeps perfect record, just as the IRS requires. And then you just have to tell it which are business, which are personal. And then it learns. Which one are business trips. So that over time, it knows when you're driving on business and you don't have to do anything. You get complete tax records. We've got businesses using it who get on average $7,000 of tax deductions. $7,000 of tax deductions. Because of the way it tracks. >> And you're taking advantage of the platform. You're taking advantage of the accelerometer. >> Yes. >> More importantly I think. The thing about mobile that most people don't maybe consciously think of is the way we interact with it as you said is little bits of time here, there, and everywhere. >> Scott: Yes. >> It's not the sit down thing. But I think what I think is most exciting about this show is it's a lot of talk about technology. But at the end of the day, it's really more about business. And small business. And small medium size business. And getting business done. >> Scott: Yes. >> And letting people do those dreams like the gal that was on the keynote. >> Scott: Yes. >> Letting her build her company and her franchise. And not have to worry about am I getting all the right deductions. >> That's right. I think the technology is the enabler. But it's all to enable what? What are we trying to deliver? And you saw it, in the kind of lead of slides. We're trying to fuel the success of small business. This is all about success. The technology's an enabler but that's not the center, the star of the show. The star of the show are small businesses and how they succeed. And how the suite of things that hundreds of developers and hundreds of software entrepreneurs who all build for the QuickBooks ecosystem. The new methods, and new ways to drive small business success. And at the end of the day, we don't measure ourselves with software. We measure ourselves with how much more money did we make small businesses? How much time did we save them so they could do what they love? How did we help them grow their business? Running a small business is a, and I know from starting Intuit, it absorbs who you are. You identify with that business. It is your representation to the world. To your spouse, to your in-laws. And if that business is successful, it's something about you that's irreplaceably positive. If that business is struggling, it strikes to the core. I mean, you feel bad. You look bad. So helping businesses succeed. And move them from mediocrity to success is such a home run for the psychology of this growing part of our economy. For each individual, it's your report card on yourself. And we can help make those report cards much better. That's our mission. That's how we're going to change the world so, so dramatically. People can't imagine going back. >> I'd say that you've already changed it dramatically. And it is exciting to hear about the next steps but this whole blend of strategy and execution and culture you're being commended for. It's just a great example of all those factors coming together and make great things happen for a lot of people around the globe so congratulations for that and thank you for being with us Scott. We appreciate the time here on theCube. >> Jeff, John thank you very much. This was a pleasure. >> Jeff: Thank you. >> You bet. Back with more from San Jose in just a bit. You're watching theCube here on SiliconANGLE TV. (techno music)

(gentle music playing) >> For centuries, we've been captivated by the concept of machines doing the job of humans. And over the past decade or so, we've really focused on AI and the possibility of intelligent machines that can perform cognitive tasks. Now in the past few years, with the popularity of machine learning models ranging from recent ChatGPT to Bert, we're starting to see how AI is changing the way we interact with the world. How is AI transforming the way we do business? And what does the future hold for us there. At theCube, we've covered Oracle's AI and ML strategy for years, which has really been used to drive automation into Oracle's autonomous database. We've talked a lot about MySQL HeatWave in database machine learning, and AI pushed into Oracle's business apps. Oracle, it tends to lead in AI, but not competing as a direct AI player per se, but rather embedding AI and machine learning into its portfolio to enhance its existing products, and bring new services and offerings to the market. Now, last October at Cloud World in Las Vegas, Oracle partnered with Nvidia, which is the go-to AI silicon provider for vendors. And they announced an investment, a pretty significant investment to deploy tens of thousands more Nvidia GPUs to OCI, the Oracle Cloud Infrastructure and build out Oracle's infrastructure for enterprise scale AI. Now, Oracle CEO, Safra Catz said something to the effect of this alliance is going to help customers across industries from healthcare, manufacturing, telecoms, and financial services to overcome the multitude of challenges they face. Presumably she was talking about just driving more automation and more productivity. Now, to learn more about Oracle's plans for AI, we'd like to welcome in Elad Ziklik, who's the vice president of AI services at Oracle. Elad, great to see you. Welcome to the show. >> Thank you. Thanks for having me. >> You're very welcome. So first let's talk about Oracle's path to AI. I mean, it's the hottest topic going for years you've been incorporating machine learning into your products and services, you know, could you tell us what you've been working on, how you got here? >> So great question. So as you mentioned, I think most of the original four-way into AI was on embedding AI and using AI to make our applications, and databases better. So inside mySQL HeatWave, inside our autonomous database in power, we've been driving AI, all of course are SaaS apps. So Fusion, our large enterprise business suite for HR applications and CRM and ELP, and whatnot has built in AI inside it. Most recently, NetSuite, our small medium business SaaS suite started using AI for things like automated invoice processing and whatnot. And most recently, over the last, I would say two years, we've started exposing and bringing these capabilities into the broader OCI Oracle Cloud infrastructure. So the developers, and ISVs and customers can start using our AI capabilities to make their apps better and their experiences and business workflow better, and not just consume these as embedded inside Oracle. And this recent partnership that you mentioned with Nvidia is another step in bringing the best AI infrastructure capabilities into this platform so you can actually build any type of machine learning workflow or AI model that you want on Oracle Cloud. >> So when I look at the market, I see companies out there like DataRobot or C3 AI, there's maybe a half dozen that sort of pop up on my radar anyway. And my premise has always been that most customers, they don't want to become AI experts, they want to buy applications and have AI embedded or they want AI to manage their infrastructure. So my question to you is, how does Oracle help its OCI customers support their business with AI? >> So it's a great question. So I think what most customers want is business AI. They want AI that works for the business. They want AI that works for the enterprise. I call it the last mile of AI. And they want this thing to work. The majority of them don't want to hire a large and expensive data science teams to go and build everything from scratch. They just want the business problem solved by applying AI to it. My best analogy is Lego. So if you think of Lego, Lego has these millions Lego blocks that you can use to build anything that you want. But the majority of people like me or like my kids, they want the Lego death style kit or the Lego Eiffel Tower thing. They want a thing that just works, and it's very easy to use. And still Lego blocks, you still need to build some things together, which just works for the scenario that you're looking for. So that's our focus. Our focus is making it easy for customers to apply AI where they need to, in the right business context. So whether it's embedding it inside the business applications, like adding forecasting capabilities to your supply chain management or financial planning software, whether it's adding chat bots into the line of business applications, integrating these things into your analytics dashboard, even all the way to, we have a new platform piece we call ML applications that allows you to take a machine learning model, and scale it for the thousands of tenants that you would be. 'Cause this is a big problem for most of the ML use cases. It's very easy to build something for a proof of concept or a pilot or a demo. But then if you need to take this and then deploy it across your thousands of customers or your thousands of regions or facilities, then it becomes messy. So this is where we spend our time making it easy to take these things into production in the context of your business application or your business use case that you're interested in right now. >> So you mentioned chat bots, and I want to talk about ChatGPT, but my question here is different, we'll talk about that in a minute. So when you think about these chat bots, the ones that are conversational, my experience anyway is they're just meh, they're not that great. But the ones that actually work pretty well, they have a conditioned response. Now they're limited, but they say, which of the following is your problem? And then if that's one of the following is your problem, you can maybe solve your problem. But this is clearly a trend and it helps the line of business. How does Oracle think about these use cases for your customers? >> Yeah, so I think the key here is exactly what you said. It's about task completion. The general purpose bots are interesting, but as you said, like are still limited. They're getting much better, I'm sure we'll talk about ChatGPT. But I think what most enterprises want is around task completion. I want to automate my expense report processing. So today inside Oracle we have a chat bot where I submit my expenses the bot ask a couple of question, I answer them, and then I'm done. Like I don't need to go to our fancy application, and manually submit an expense report. I do this via Slack. And the key is around managing the right expectations of what this thing is capable of doing. Like, I have a story from I think five, six years ago when technology was much inferior than it is today. Well, one of the telco providers I was working with wanted to roll a chat bot that does realtime translation. So it was for a support center for of the call centers. And what they wanted do is, Hey, we have English speaking employees, whatever, 24/7, if somebody's calling, and the native tongue is different like Hebrew in my case, or Chinese or whatnot, then we'll give them a chat bot that they will interact with and will translate this on the fly and everything would work. And when they rolled it out, the feedback from customers was horrendous. Customers said, the technology sucks. It's not good. I hate it, I hate your company, I hate your support. And what they've done is they've changed the narrative. Instead of, you go to a support center, and you assume you're going to talk to a human, and instead you get a crappy chat bot, they're like, Hey, if you want to talk to a Hebrew speaking person, there's a four hour wait, please leave your phone and we'll call you back. Or you can try a new amazing Hebrew speaking AI powered bot and it may help your use case. Do you want to try it out? And some people said, yeah, let's try it out. Plus one to try it out. And the feedback, even though it was the exact same technology was amazing. People were like, oh my God, this is so innovative, this is great. Even though it was the exact same experience that they hated a few weeks earlier on. So I think the key lesson that I picked from this experience is it's all about setting the right expectations, and working around the right use case. If you are replacing a human, the level is different than if you are just helping or augmenting something that otherwise would take a lot of time. And I think this is the focus that we are doing, picking up the tasks that people want to accomplish or that enterprise want to accomplish for the customers, for the employees. And using chat bots to make those specific ones better rather than, hey, this is going to replace all humans everywhere, and just be better than that. >> Yeah, I mean, to the point you mentioned expense reports. I'm in a Twitter thread and one guy says, my favorite part of business travel is filling out expense reports. It's an hour of excitement to figure out which receipts won't scan. We can all relate to that. It's just the worst. When you think about companies that are building custom AI driven apps, what can they do on OCI? What are the best options for them? Do they need to hire an army of machine intelligence experts and AI specialists? Help us understand your point of view there. >> So over the last, I would say the two or three years we've developed a full suite of machine learning and AI services for, I would say probably much every use case that you would expect right now from applying natural language processing to understanding customer support tickets or social media, or whatnot to computer vision platforms or computer vision services that can understand and detect objects, and count objects on shelves or detect cracks in the pipe or defecting parts, all the way to speech services. It can actually transcribe human speech. And most recently we've launched a new document AI service. That can actually look at unstructured documents like receipts or invoices or government IDs or even proprietary documents, loan application, student application forms, patient ingestion and whatnot and completely automate them using AI. So if you want to do one of the things that are, I would say common bread and butter for any industry, whether it's financial services or healthcare or manufacturing, we have a suite of services that any developer can go, and use easily customized with their own data. You don't need to be an expert in deep learning or large language models. You could just use our automobile capabilities, and build your own version of the models. Just go ahead and use them. And if you do have proprietary complex scenarios that you need customer from scratch, we actually have the most cost effective platform for that. So we have the OCI data science as well as built-in machine learning platform inside the databases inside the Oracle database, and mySQL HeatWave that allow data scientists, python welding people that actually like to build and tweak and control and improve, have everything that they need to go and build the machine learning models from scratch, deploy them, monitor and manage them at scale in production environment. And most of it is brand new. So we did not have these technologies four or five years ago and we've started building them and they're now at enterprise scale over the last couple of years. >> So what are some of the state-of-the-art tools, that AI specialists and data scientists need if they're going to go out and develop these new models? >> So I think it's on three layers. I think there's an infrastructure layer where the Nvidia's of the world come into play. For some of these things, you want massively efficient, massively scaled infrastructure place. So we are the most cost effective and performant large scale GPU training environment today. We're going to be first to onboard the new Nvidia H100s. These are the new super powerful GPU's for large language model training. So we have that covered for you in case you need this 'cause you want to build these ginormous things. You need a data science platform, a platform where you can open a Python notebook, and just use all these fancy open source frameworks and create the models that you want, and then click on a button and deploy it. And it infinitely scales wherever you need it. And in many cases you just need the, what I call the applied AI services. You need the Lego sets, the Lego death style, Lego Eiffel Tower. So we have a suite of these sets for typical scenarios, whether it's cognitive services of like, again, understanding images, or documents all the way to solving particular business problems. So an anomaly detection service, demand focusing service that will be the equivalent of these Lego sets. So if this is the business problem that you're looking to solve, we have services out there where we can bring your data, call an API, train a model, get the model and use it in your production environment. So wherever you want to play, all the way into embedding this thing, inside this applications, obviously, wherever you want to play, we have the tools for you to go and engage from infrastructure to SaaS at the top, and everything in the middle. >> So when you think about the data pipeline, and the data life cycle, and the specialized roles that came out of kind of the (indistinct) era if you will. I want to focus on two developers and data scientists. So the developers, they hate dealing with infrastructure and they got to deal with infrastructure. Now they're being asked to secure the infrastructure, they just want to write code. And a data scientist, they're spending all their time trying to figure out, okay, what's the data quality? And they're wrangling data and they don't spend enough time doing what they want to do. So there's been a lack of collaboration. Have you seen that change, are these approaches allowing collaboration between data scientists and developers on a single platform? Can you talk about that a little bit? >> Yeah, that is a great question. One of the biggest set of scars that I have on my back from for building these platforms in other companies is exactly that. Every persona had a set of tools, and these tools didn't talk to each other and the handoff was painful. And most of the machine learning things evaporate or die on the floor because of this problem. It's very rarely that they are unsuccessful because the algorithm wasn't good enough. In most cases it's somebody builds something, and then you can't take it to production, you can't integrate it into your business application. You can't take the data out, train, create an endpoint and integrate it back like it's too painful. So the way we are approaching this is focused on this problem exactly. We have a single set of tools that if you publish a model as a data scientist and developers, and even business analysts that are seeing a inside of business application could be able to consume it. We have a single model store, a single feature store, a single management experience across the various personas that need to play in this. And we spend a lot of time building, and borrowing a word that cellular folks used, and I really liked it, building inside highways to make it easier to bring these insights into where you need them inside applications, both inside our applications, inside our SaaS applications, but also inside custom third party and even first party applications. And this is where a lot of our focus goes to just because we have dealt with so much pain doing this inside our own SaaS that we now have built the tools, and we're making them available for others to make this process of building a machine learning outcome driven insight in your app easier. And it's not just the model development, and it's not just the deployment, it's the entire journey of taking the data, building the model, training it, deploying it, looking at the real data that comes from the app, and creating this feedback loop in a more efficient way. And that's our focus area. Exactly this problem. >> Well thank you for that. So, last week we had our super cloud two event, and I had Juan Loza on and he spent a lot of time talking about how open Oracle is in its philosophy, and I got a lot of feedback. They were like, Oracle open, I don't really think, but the truth is if you think about database Oracle database, it never met a hardware platform that it didn't like. So in that sense it's open. So, but my point is, a big part of of machine learning and AI is driven by open source tools, frameworks, what's your open source strategy? What do you support from an open source standpoint? >> So I'm a strong believer that you don't actually know, nobody knows where the next slip fog or the next industry shifting innovation in AI is going to come from. If you look six months ago, nobody foreseen Dali, the magical text to image generation and the exploding brought into just art and design type of experiences. If you look six weeks ago, I don't think anybody's seen ChatGPT, and what it can do for a whole bunch of industries. So to me, assuming that a customer or partner or developer would want to lock themselves into only the tools that a specific vendor can produce is ridiculous. 'Cause nobody knows, if anybody claims that they know where the innovation is going to come from in a year or two, let alone in five or 10, they're just wrong or lying. So our strategy for Oracle is to, I call this the Netflix of AI. So if you think about Netflix, they produced a bunch of high quality shows on their own. A few years ago it was House of Cards. Last month my wife and I binge watched Ginny and Georgie, but they also curated a lot of shows that they found around the world and bought them to their customers. So it started with things like Seinfeld or Friends and most recently it was Squid games and those are famous Israeli TV series called Founder that Netflix bought in, and they bought it as is and they gave it the Netflix value. So you have captioning and you have the ability to speed the movie and you have it inside your app, and you can download it and watch it offline and everything, but nobody Netflix was involved in the production of these first seasons. Now if these things hunt and they're great, then the third season or the fourth season will get the full Netflix production value, high value budget, high value location shooting or whatever. But you as a customer, you don't care whether the producer and director, and screenplay writing is a Netflix employee or is somebody else's employee. It is fulfilled by Netflix. I believe that we will become, or we are looking to become the Netflix of AI. We are building a bunch of AI in a bunch of places where we think it's important and we have some competitive advantage like healthcare with Acellular partnership or whatnot. But I want to bring the best AI software and hardware to OCI and do a fulfillment by Oracle on that. So you'll get the Oracle security and identity and single bill and everything you'd expect from a company like Oracle. But we don't have to be building the data science, and the models for everything. So this means both open source recently announced a partnership with Anaconda, the leading provider of Python distribution in the data science ecosystem where we are are doing a joint strategic partnership of bringing all the goodness into Oracle customers as well as in the process of doing the same with Nvidia, and all those software libraries, not just the Hubble, both for other stuff like Triton, but also for healthcare specific stuff as well as other ISVs, other AI leading ISVs that we are in the process of partnering with to get their stuff into OCI and into Oracle so that you can truly consume the best AI hardware, and the best AI software in the world on Oracle. 'Cause that is what I believe our customers would want the ability to choose from any open source engine, and honestly from any ISV type of solution that is AI powered and they want to use it in their experiences. >> So you mentioned ChatGPT, I want to talk about some of the innovations that are coming. As an AI expert, you see ChatGPT on the one hand, I'm sure you weren't surprised. On the other hand, maybe the reaction in the market, and the hype is somewhat surprising. You know, they say that we tend to under or over-hype things in the early stages and under hype them long term, you kind of use the internet as example. What's your take on that premise? >> So. I think that this type of technology is going to be an inflection point in how software is being developed. I truly believe this. I think this is an internet style moment, and the way software interfaces, software applications are being developed will dramatically change over the next year two or three because of this type of technologies. I think there will be industries that will be shifted. I think education is a good example. I saw this thing opened on my son's laptop. So I think education is going to be transformed. Design industry like images or whatever, it's already been transformed. But I think that for mass adoption, like beyond the hype, beyond the peak of inflected expectations, if I'm using Gartner terminology, I think certain things need to go and happen. One is this thing needs to become more reliable. So right now it is a complete black box that sometimes produce magic, and sometimes produce just nonsense. And it needs to have better explainability and better lineage to, how did you get to this answer? 'Cause I think enterprises are going to really care about the things that they surface with the customers or use internally. So I think that is one thing that's going to come out. And the other thing that's going to come out is I think it's going to come industry specific large language models or industry specific ChatGPTs. Something like how OpenAI did co-pilot for writing code. I think we will start seeing this type of apps solving for specific business problems, understanding contracts, understanding healthcare, writing doctor's notes on behalf of doctors so they don't have to spend time manually recording and analyzing conversations. And I think that would become the sweet spot of this thing. There will be companies, whether it's OpenAI or Microsoft or Google or hopefully Oracle that will use this type of technology to solve for specific very high value business needs. And I think this will change how interfaces happen. So going back to your expense report, the world of, I'm going to go into an app, and I'm going to click on seven buttons in order to get some job done like this world is gone. Like I'm going to say, hey, please do this and that. And I expect an answer to come out. I've seen a recent demo about, marketing in sales. So a customer sends an email that is interested in something and then a ChatGPT powered thing just produces the answer. I think this is how the world is going to evolve. Like yes, there's a ton of hype, yes, it looks like magic and right now it is magic, but it's not yet productive for most enterprise scenarios. But in the next 6, 12, 24 months, this will start getting more dependable, and it's going to change how these industries are being managed. Like I think it's an internet level revolution. That's my take. >> It's very interesting. And it's going to change the way in which we have. Instead of accessing the data center through APIs, we're going to access it through natural language processing and that opens up technology to a huge audience. Last question, is a two part question. And the first part is what you guys are working on from the futures, but the second part of the question is, we got data scientists and developers in our audience. They love the new shiny toy. So give us a little glimpse of what you're working on in the future, and what would you say to them to persuade them to check out Oracle's AI services? >> Yep. So I think there's two main things that we're doing, one is around healthcare. With a new recent acquisition, we are spending a significant effort around revolutionizing healthcare with AI. Of course many scenarios from patient care using computer vision and cameras through automating, and making better insurance claims to research and pharma. We are making the best models from leading organizations, and internal available for hospitals and researchers, and insurance providers everywhere. And we truly are looking to become the leader in AI for healthcare. So I think that's a huge focus area. And the second part is, again, going back to the enterprise AI angle. Like we want to, if you have a business problem that you want to apply here to solve, we want to be your platform. Like you could use others if you want to build everything complicated and whatnot. We have a platform for that as well. But like, if you want to apply AI to solve a business problem, we want to be your platform. We want to be the, again, the Netflix of AI kind of a thing where we are the place for the greatest AI innovations accessible to any developer, any business analyst, any user, any data scientist on Oracle Cloud. And we're making a significant effort on these two fronts as well as developing a lot of the missing pieces, and building blocks that we see are needed in this space to make truly like a great experience for developers and data scientists. And what would I recommend? Get started, try it out. We actually have a shameless sales plug here. We have a free deal for all of our AI services. So it typically cost you nothing. I would highly recommend to just go, and try these things out. Go play with it. If you are a python welding developer, and you want to try a little bit of auto mail, go down that path. If you're not even there and you're just like, hey, I have these customer feedback things and I want to try out, if I can understand them and apply AI and visualize, and do some cool stuff, we have services for that. My recommendation is, and I think ChatGPT got us 'cause I see people that have nothing to do with AI, and can't even spell AI going and trying it out. I think this is the time. Go play with these things, go play with these technologies and find what AI can do to you or for you. And I think Oracle is a great place to start playing with these things. >> Elad, thank you. Appreciate you sharing your vision of making Oracle the Netflix of AI. Love that and really appreciate your time. >> Awesome. Thank you. Thank you for having me. >> Okay. Thanks for watching this Cube conversation. This is Dave Vellante. We'll see you next time. (gentle music playing)

>> From the SiliconANGLE Media office in Boston, Massachusetts, it's theCUBE. Now, here's your host, Dave Vellante. >> Hello everyone, and welcome to this week's episode of theCUBE insights, powered by ETR. In this breaking analysis, I'm going to provide a little detail on the recent announcement that Insight Partners was acquiring Veeam for five billion dollars. There was a lot of information on the announcement in press releases and in news articles, so what I really want to focus on is what it means for the industry generally, and for the data protection community specifically. So, very briefly this was a five billion dollar exit for Veeam on top of a five hundred million dollar investment lead by the same Insight Partners last year. I think it had earlier investments, kind of a rent, with an option to buy. New management is being promoted from within, which I think is significant, to replace the two founders. Andrei Baronov and Ratmir Timashev are going to step down after the transition and give up their board seats. Veeam is a fascinating company. It started in the 2006, 2007 time frame, after the two founders, who met in college, formed and sold Aleta software to Quest. Then they started a company called AMUST Software, from which they created Veeam. You never hear about AMUST, but I believe it's the engineering and development arm of Veeam. Now the new CEO of Veeam, Bill Largent told theCUBE that AMUST is now a wholly owned subsidiary of Veeam and it won't effect any of the engineering assets that exist in Prague and in Russia. So this I the thing about Veeam, it's a very closely held company controlled by it's two founders, with a domicile in Switzerland. My understanding is Baronov is, well he's the technical guru, and he's a resident of that country in Switzerland, and the HQ there is very lean, the sizable engineering teams, as they say, is in Russia and Prague. Timashev resides in the US, and he's a marketing genius, who helped create this company, and it's always punched above it's weight class with, epic parties, and great products. Now interestingly, Veeam's rise, it coincided with the ascendancy of VMware. Veeam became the standard backup software for small to medium size companies within VMware shops. Their products are renowned for being simple, and working as advertised, and their customer support is outstanding by all accounts. But the US business lagged, despite the fact that most of VMware's business is in the Americas. You'd think you think if they super glued themself to VMware their Americas business would be higher. So a few years ago they decided to really go hard after the enterprise and they brought in Peter Mckay, from VMware, and he began to build up a US presence. But the enterprise business, it requires a lot of things that were kind of antithetical to Veeam. So think about long sales cycles, expensive sales people, belly to belly selling, with the expectations of, road maps, and clarity around enterprise feature sets. Now McKay was named CEO with Baronov, who continued to run engineering. So it was a bit of a culture clash. You got the sales oriented leader wanting the engineering team to turn on a dime and help close large deals, and satiate partners like HPE and Sysco, and you've got this genius co-leader, slash engineer, with an incredible track record of delivering features that the customer loves. So it really didn't work out and then Veeam scaled back on it's ambitions some what. At it's annual user conference in Miami last year, Ratmir came on theCUBE, and he talked about how Veeam's act one was all about dominance in virtualized environment. Let's listen to what he said about act two and then we'll come back and talk about it >> That was act one, we dominated it, we grew from zero to one billion within 10, 12 years. We added three hundred fifty thousand customers over that time frame, and now it's act two. What is act two? Act two is the, again, the new major industry transformation to a hybrid cloud. What are the similarities? Again, Veeam is in a great position because we're at the right time at the right place with a brilliant product. >> Now what we know is that act two is about a few things, one, as Ratmir said, hybrid cloud, multi cloud management, etcetera. But it's also about an awesome exit for it's two founders. Wow five billion dollars, five x revenue multiple, handing over the reigns is really the third thing this is about and creating more traditional governance structure for Veeam. Now they're moving from a governance structure that was closely held and opaque to one that is still going to be closely held, but ideally somewhat less opaque. Which brings me to inside partners. In the money world, you basically have a spectrum of investors. On the one side you've got banks, who are the most conservative. On the other side you've got VCs, now they're the most aggressive, of course. Now somewhere in the middle, you have private equity firms. Now they traditionally invest in companies, and they squeeze them for EBITDA, and they suck money out. But inside is more of a hybrid. They invest in a number of companies as VCs, they take a portion of the ownership. And to me they're more of a rule of forty PE, meaning it's not just about EBITDA, it's about growth plus EBITDA. So a rule of thirty or a rule of forty PE company, they can dial down EBITDA and go for growth, or dial up EBIT and moderate growth. So it's a great model. So I would expect Insight to bring structure and leadership to Veeam, with the goal of taking the company public at some point, because they like to sell to companies for all cash, I don't see a logical buyer at these kind of price points for this company in this market. It's growing market but it's still not a giant market. All right let's shift gears a little bit and get into some of the ETR data. Here's a narrative they put out recently that, to me, sums it up well. ETR said Veeam is one of the few vendors growing share among customers vs previous surveys in the storage sector. And that said, spending intentions are decelerating and continue to look poor in the largest sectors and Veeam trails Rubrik and Cohesity, although on a larger user base. So you can see by this statement that Veeam is of course doing well, but there are some cracks in the enterprise armor that I want to talk about and drill into a little bit. Now this now this Arline customer quote also, to me, sums up one of the reasons for Veeam's success. What this person said is if I want to do a Veeam back up to the cloud, it's basically point and click, very easy to use. Now I've talked to dozens, if not hundreds of Veeam customers, and they all say the same thing, it just works, that's kind of their motto. So this is the big reason why Veeam has steadily gained gained share over time. Now take a look at this chart, which shows the progression over time of Veeam's progress in terms of what ETR calls market share. Now remember, market share is a measure of pervasiveness in the ETR data set. And you can see, in the data, that Veeam has had a steady rise since ETR started tracking them at critical mass back in 2014. And you can see the steady decline in the survey for Veritas and Commvault and what appears to be, rapid momentum building for Rubrik and Cohesity, two companies that I said in my 2020 predictions breaking analysis that would continue to do well this year. Now notice I had to black out the January 2020 survey, which is ending shortly, so stay tuned for those results. But let's drill into Veeam's performance a little bit more. What this chart shows is a candlestick of net score and market share across all the respondents in the ETR survey for Veeam. Remember net score is a measure of spending momentum that subtracts customers that are spending less, the red, from those spending more, the greens. And it's represented over time by this blue line that you see. You can see that this blue line, it bounces around but it holds steady in the past couple of years pretty generally, and really in that thirty to forty percent range which you see on the left hand axis. Now that yellow line, is market share or pervasiveness, it also continues to climb steadily as I showed you in the previous chart. Now again this is amongst all respondents. Let's now take a look at this chart which isolates Veeam's performance in the largest companies, that enterprise push. Notice the pictures is somewhat choppier. Market share is okay, although unlike the previous chart, it's not steady. This is stunning. Peter McKay left in October 2018, and that's when Veeam really pulled back on it's big enterprise push, and you can see, there's a noticeable and steady drop there based on ETR data. So what's happening here is we are entering a new chapter for Veeam, act two so to speak. With new leadership and new governance. Danny Allen is taking over CTO, he previously ran strategy, Bill Largent is going to be CEO, the HQ is moving into the US. So in my opinon, Veeam's issues in the US have been more execution related than anything else. Veeam is a leader. So partnerships with Nutanix, Sysco, HPE, NetApp, should continue to improve and be somewhat productive, actually largely productive. Let's talk a little bit about Veeam's architecture, and a point of discussion that you often hear in the community. Veeam's a Window's based architecture. Now is that a blessing or is that a curse? Well the pros are that the Veeam team came out of a Windows world, and they know the platform very well. They are amazingly good at adding function, without screwing up performance somewhere else. You saw this a couple years back when they were making a big push on the enterprise and they increased the file sizes, and the number of objects that they could support. Another example is when Veeam added cloud back up, it was a really good product, version one. Unlink many products, when they first tried to port to the cloud, that wasn't the case. Recovery from the cloud is very tricky. Things are out of sync, you got a metadata challenge, and generally Veeam was able to achieve consistent levels of performance with it's cloud product. Now flip side of this, is that if you look at most, if not all, modern architectures today, are based on Linux. And once you start getting into mulit cloud, and cross cloud management, you're going to bump into and be interfacing with lots of Linux based systems. So Veeam is going to have migrate code, and maintaining consistent performance is going to be tougher. But as David Fourier, my colleague points out, there are many many ways to skin a cat, and Veeam's engineering team has really, based on it's track record, has proven that it can solve tough problems, and really deliver a great product consistently. I think the bigger issue and challenge for Veeam again, is execution in the US, and of course the enterprise. Customers in EBC's executive briefing centers, they want to see road maps, and enterprise features, and specials. And so we'll see, if that's something that Veeam has an appetite for. If they do, and I'm one of the incumbents, I'd be worried that Veeam could do a land and expand. Where Veeam isn't as strong in large enterprises, big companies they buy from Veeam. Maybe it's a smaller division, or remote location, but it's not like they don't do business in large accounts, they do. So in a way, they've already landed and they have an opportunity to expand, so that's something to pay attention to. If I'm an enterprise customer, I would be pressing Veeam on it's roadmap, and having them clarify their vision around hybrid and multi cloud management. Will Veeam be more transparent and willing to do specials for the enterprise, and their big partners, who expect them, when they say jump, they expect Veeam to say how high. How will Veeam's culture change, is the other thing I want to focus on. As the two founders step down, are they going to be able to main their engineering ethos, and customer loyalty, and can they figure out the enterprise. I'm a big fan of founder lead companies, when founders leave cultures often change. When founders stay, they're intensely committed, even beyond great CEOs who aren't founders. Look at Michael Dell. He went to the mat to keep his company against the great icon, now look at Dell technologies, after the EMC acquisition, it was completely transformed. Look at Oracle, look at the lengths that Larry Ellison goes to win. Compare that to a great CEO Joe Tucci, when he was at EMC, but you know when he was done, he was done, it was over. It wasn't his baby. So my point is how will this effect Veeam's culture and prospects in the long term. For me the bottom line is the big opportunity's in the US. And that's about execution. And I expect with the move to US HQ, new management, I expect they're going to see consistent market share gains, that's going to continue. The enterprise however, that's going to take longer, it's going to require more patience and more money. And with Veeam transitioning from essentially the two founder's lifestyle business into a company that's really built for an exit, they're going to have more money to invest, greater transparency, I hope, and a path to really build on their past successes. So this Dave Vellante signing out from the latest episode of theCUBE insights, powered by ETR. Thanks for watching everybody and we'll see you next time. (upbeat music)

(intense orchestral music) >> Hello everyone, welcome to this special CUBEConversation, I'm John Furrier, co-host of theCUBE, co-founder of SiliconANGLE Media. I'm here with Erica Brescia, who's the co-founder and Chief Operating Officer at Bitnami, it's the app store for the cloud, they do automated packaging, an application provider. Great to see you, CUBE alumni, great to have you in the studio, thanks for coming in. >> Great to be here, thanks for having me. >> So, so much going on, you've been to theCUBE multiple times, we see each other at conferences and, you made some time, thanks for comin' down, appreciate it. >> Yeah. >> So Bitnami's doing some great things, so give us the update, what's goin' on with the company? >> Sure. So we just launched our new offering called Stacksmith, which is our first enterprise offering that basically takes all the tooling that we've built to deliver the application catalog that we have onto all the major cloud vendors, and allows enterprise IT departments to package up their own applications, both for cloud and cloud-native platforms, as well as for whatever they're running in the enterprise today. So, it kind of meets them where they are, helps them automate the application packaging and maintenance in place today, and then sets them up to successfully move to the cloud and Kubernetes and containers over time. >> So it's kind of reverse of this journey to the cloud, you go to where the user, the customers are, help them put it together. >> And make the journey, really. So what we find is a lot of the more traditional orchestration and packaging tools just aren't well suited to cloud and containers in particular. And so enterprises are looking for new tools to help them solve current problems, which is: we need to support all these different platforms, we might have some things running internally in VMware, we're running some things on Amazon, maybe using cloud formation, and now they're trying to get to Kubernetes, and they're trying to figure out how they can do that without having a separate pipeline for everything, and that's the problem that Bitnami solves. >> Yeah, and that's been a bit, we've identified a product at Amazon, then, I want Azure, I want Google Cloud, I got to hire a different development team, different stacks. So there's kind of this problem with multi-cloud. How are you guys talkin' to customers about it? 'Cause this seems to be the hybrid cloud main problem today. It's like, okay I see the cloud, I understand I'm going to be doing a lot of stuff in the cloud, or cloud's going to be on-prem, and it's going to be in the cloud. How do I get ready for the cloud? That seems to be a number one question. >> Yeah, and I think what people are struggling with is, you know, there're a lot of companies out there, particularly in the cloud-native space, that just say: if you just rebuild everything, then your life will be so much better, right? But that's not really realistic for most companies. They need to be able to take what they have, and be able to package it in such a way that they get a lot of the benefits of the cloud and containers without completely re-architecting everything. Because, it might be practical for, say a new start up, or a company like Netflix or Spotify to do that, but lets face it, most companies are not that, most companies have too many demands on their IT and Ops teams already, hiring talent is hard even for the startups working at the forefront of Kubernetes, so, you really need tools that are approachable and solve current problems, but again, I think the key is, set you up for success in the future, and I think we help people kind of bridge the gap between what they're doing today and what they're doing in the future without trying to push them in one direction, which might not make sense for them. >> Yeah, in Netflix, and the Googles of the world, are potential future scenarios of what they might look like, but they got to take care of the current move from IT to cloud, get ready for it. >> Yeah, maybe, and you know, for a lot of these internal applications it doesn't make sense to completely re-architect and rewrite them, like the ROI isn't there, and there are companies out there that have thousands of Java or .NET applications that they just need to be able to move perhaps out of their data center, in many cases it's being shut down, and, onto cloud platforms and so we try to find that nice balance between helping you get the advantage of the automation of cloud without having to invest in re-architecting apps that just aren't worth re-architecting. >> Got to ask you Erica, we've had a couple conversations, I forget what you were founded, at Bitnami, you've had a great journey, a lot of things have changed. When did you guys found 2010, or 2011? >> So we started Bitnami in 2013. The company before Bitnami was Bitrock, and we went through YCombinator in 2013, and that's when we really started growing out the company. First around the app catalog that we deliver both via Bitnami.com as well as all the major cloud platforms, and that's allowed us to bootstrap the business up to this point. And then obviously we took all of the learnings and the technology from delivering 140 applications across 14 different platforms, native and cloud, and productize that in Stacksmith, so our enterprise users, you know, we have over a million deployments a month, but people have only been consuming the things that we build now they can use our tooling, that we've been building out over the years, to automate the packaging of their own applications. >> And it's, just to kind of put some color commentary around that time, it wasn't the most calm waters of the cloud world, massive growth, a lot of things have happened, so containers come to the scene with Docker and that becomes standardized, now you've got Kubernetes, you got service meshes right around the corner, kind of now it sets a perfect opportunity for you guys to bring customers to this app store concept, for you guys. >> Yeah, and we see this great, we call it kind of the great unbundling, right? Where apps used to be distributed with the operating system and they kind of were this one cohesive piece, and now, with Kubernetes and cloud APIs, the applications are very separate, and so there's kind of this new operating system coming together, which is the operating system of containers and Kubernetes and cloud, and it allows you to combine these different pieces in ways that you never could before. Before, you know, you would just go to your OS repo to pull in the app that you wanted. >> And you see the trends, I mean, Google has the SRE concept sight, reliability, engineer, the operators on the VMware side, dealing with VMs kind of all converging together. So I got to ask you, how does that impact your customers with your new Stacksmith offering, what's the impact to the customers? Is it ease of use, is it ease of deployment, what's the main value at? >> So, I think the most important thing is, as you said, there're all these new technologies coming out and there's also cloud formation on AWS, and there's ARM on Azure, and each cloud vendor is coming out with their own tooling and then, like you said, there's operators for Kubernetes. The advantage that you get with Bitnami is you don't have to understand the intricacies of how to package for all of those different platforms because we do that for you. We abstract away having to understand how to build a cloud formation template versus a helm chart helps that Kubernetes, you know, package manager essentially and we've been very involved in helping define and further that project. We're actually the top provider of the official helm charts. So we see a lot of promise there but, what's interesting about Bitnami is at the end of the day we're platform agnostic. And once you start using Bitnami and Stacksmith, you can very easily add support for other platforms. So we have a customer who started out on AWS, for example, they wanted to give a try to running some things on Azure, and they essentially just had to flip a switch, and then they get an ARM template, instead of-- >> What was your alternative to that? If they didn't do that, what would they have to do? >> They would have had to do it either manually, or find system specific tools for each platform, to do it. So, there's no other like singular tool chain that lets you build natively for all the different platforms and that's the key, we don't try to abstract away ARM or any of these other orchestration technologies by giving you some kind of layer on top of them. We just make it really easy to build for those technologies and also, to maintain those applications and templates over time, so this isn't point-in-time thing, we track all of the updates in everything that goes into that image or a set of images, and allow you to automatically rebuild and redeploy across any of those platforms you need to support. >> You guys have been very successful in the cloud, but also have scar tissue like everybody else that's been through the cloud wars. And now, as it starts to hit kind of an inflection point, how has cloud changed now, what are we seeing now in cloud versus, say 2014, 2015 timeframe? >> Oh boy. So, I think the most interesting thing is how quickly Azure in particular has evolved. If I had to pick one thing that has been incredibly impressive and important in the changing cloud landscape, it's, you know, you go back to 2014, it was pretty much all AWS all the time, right? And, Amazon isn't quite the Goliath it used to be anymore, I mean there's-- >> Well it's still pretty damn big. >> They're still huge. Yeah, absolutely, but I'll tell you what, the others are gaining a lot of ground, and they have really interesting and different advantages, right? Google will send all of their amazingly smart engineers in to help you architect applications, or move them over, I've heard a lot of workloads moving off of AWS onto Google because Google is giving them so much love and support and trying to attract those workloads over. But Azure's advantage is their ecosystem, right? They really understand partnering in a way that Amazons retail DNA just, it doesn't lend itself to that, and so, I think Microsoft's approach to building out a really great ecosystem around Azure, coupled with their huge field sales team, which Amazon has just been building, they've never had an enterprise sales team, is making things really interesting and creating, for us, a great dynamic in the market because we like to see a number of cloud vendors flourish. >> You're an arms dealer. >> Yeah exactly! (Erica laughs) >> Whatever you want, any cloud. >> I don't know if our CMO would want me to put it that way, but. (laughing) >> Dave Alante's favorite term, by the way. >> Sure. >> It's good to be an arms dealer, or be Switzerland, as they, to be more politically correct. >> Yeah, we go with Switzerland. >> Azure's interesting, I was just having conversation with Dave about this, because, you know, you've got, consumerization of IT, and digital transformation, have been the biggest buzz words in IT for the past decade. First it was consumerization of IT, now it's digital transformation. If you think about it Amazon and Google are really the consumer companies, Azure is an enterprise company with an ecosystem, so it's going to be very interesting to see if consumerization is the winning formula or is it digital transformation on the enterprise side? So you got to be, watching that pretty closely. Your thoughts? >> So, I would say on the consumerization of IT side, I mean that is absolutely happening, and, there, we could talk for hours probably on why that trend is here and why it's not going away, just, expectations in general have changed with the advent of iPhone and app stores and convenience across every aspect of our lives, so, I think even Microsoft gets that, and I don't think that the consumer DNA of those companies actually gives them a real edge in this case. What is interesting is, every company is starting to really focus on their app stores and their marketplace strategies, and trying to provide a frictionless buying experience. And there're a bunch of announcements coming, both on the AWS side, and the Azure side in particular, around things that they're doing to ease the enterprise buying process. >> Well we identified the three things, SAS business is table stakes, IOT is coming, connected devices, and then you've got the mobile. Those three things are on 20 year runs. Talking about Bitnami's update, you mentioned Stacksmith, you have some new stuff there, you guys are hiring, what's the ramp up, marketing, cash flow, top line revenues? Go ahead, share it. >> I'm not giving you all that. (both laughing) But, yeah it's a really exciting time for us, obviously bringing this enterprise product to market. We're gearing up to scale quite significantly, so, Bitnami's is kind of unusual in the Valley in that we're bootstrapped, and we're very heavily engineering driven. >> So no outside funding? >> A million dollars in total, which pretty much doesn't even count in Silicon Valley, and that was really just they had a number of individual folks involved in the company, when we went through YC. >> So no venturing? >> No, no institutional funding So, we are just getting ready to build out the whole go to market team around the Stacksmith product, which is very new in the market, just launched in the last couple months. >> So is it generally available? >> Oh yes! Generally available, customers, lots of great things to talk about, but, we don't have the full sales team in place. >> And what's the benefits of Stacksmith? What's the bottom line value proposition? >> It's really helping you to automate the packaging and maintenance of your applications, whether internal or external, you know, third-party commercial apps that you're using internally, and deploying them on any of the platforms that you need to support. >> App store for the cloud, I love that. So let's talk about what you're workin' on, one of the things I'm really impressed, first of all I'm really impressed with what you've done with Bitnami, I love it, love the bootstrap stories, we were bootstrapped as well in the run of SiliconANGLE. So it's great, in Silicon Valley, I think that's like the top tier player, if you can bootstrap it to economic visibility around scale, that's a success so congratulations. But you also have something exciting going on with venture investing. X factor, >> X factor, yep. >> This is super impressive. You raised a small little fund, X factor, investing in women entrepreneurs. Take a minute to explain what X factor is, do you have some news coming, another fund coming? >> Sure, yeah it's been very exciting, so, in the free free time that I really don't have, but this is such a good cause it's worth it. We put together a three million dollar fund, to invest a hundred thousand dollars in 30 different companies, with at least one female founder. And this actually was spun out of fly bridge, we have our token guys, we call 'em Chip Hazard, who's a career venture investor, who's doing a lot of interesting things. But, he basically led the charge with a woman named Anna Palmer, to put together a group of female founders, that's what really differentiates us, I think, from the rest of the market, who are operating their own companies, to invest in these very early stage female founded companies And, I think that gives us a really unique advantage in the market of venture, in that first we have an incredible pipeline and deal flow because, you know, we know these folks who are starting the companies. And we also have a unique perspective on the challenges of getting a new venture off the ground, and I think we can really be an ally to the entrepreneurs that we're funding, and helping them get that first bit of funding in the door, we typically help them with their series A rounds and beyond and they really see us as a peer and someone they can relate to and come to for advice, and so, I think it's a pretty unique value prop that we have as a VC fund. >> Operating experience brings a lot to the table, so, you want to get those first three steps goin', get that venture off the ground, trust. >> Yeah, and we have a very diverse range of experiences that we can bring to bare too, I mean some of us have deep infrastructure experience, some folks are on the consumer side, we've got a few East Coast people, a few West Coast people, a few people scattered in other areas. And we all have different areas of expertise, right? I'm pretty strong on the business development side, and I'm business model, SAS, enterprise software. Some of the other women are much more familiar with like distribution deals, or hardware deals, or other consumer businesses as well, so I think we have a really unique range of experiences and expertise that we can bring to bare in supporting our founders. >> And mentoring too, it's being there for, you know, don't give up! >> Yeah! And we've had founders go through things, and they'll call us at, one of our founders I was just on the phone with, and she was looking at changing her role within the company to take on more responsibility, and we had a great conversation around that, and that resulted in her becoming the COO, which was fantastic. Another founder was going through a difficult time where she and her co-founder were splitting up, and I was able to talk her through that. And we have a lot of those stories where, I think, you know, we have really been seen as an ally who can help founders get through those times, because we've been there, and we can empathize. And, it's an interesting dynamic because everybody knows that we're not going to invest in the next round, so there's never any posturing to make sure that they're still selling us on investing in the company. It's all about, once we're in, we're in, and we'll do anything we can do to help you scale successfully over time. >> And the key is get to that next round, or get a clear line of sight on visibility in the union economics or, scale. >> Exactly. >> Alright, so how much is going into the next funding? Can you talk about the amount, or? >> Yeah, so we're not raising yet, we're just about to start raising, we're going to be expanding the number of investment partners on the team, which is fantastic, and I'm really excited to bring some amazing new women on board, so, you know, for the women out there who are maybe interested in starting to learn a little more about venture and have raised funding and build their own companies, please send us an email: hello@xfactorventures the fund should be about 10 million dollars, is the current target. >> How is it structured? Are they structured as limited partners, general partners? How is it, so if someone comes on board, as you expand the partnership what does it look like? >> Sure, so, we all do invest our own money, but the fund has LPs just like any other fund, so there's a number of great folks who have backed up X factor. We do bring in some of our own folks along the way, you know, I had people that I know, who have invested in the fund and I'm sure that will be the case in the next one, but it's not like the fund is only funded by the investment partners, we have LPs like any other fund. >> But you guys are taking profits out of it, through the caring, right? So typical venture capital? >> It's typical venture capital, you know, it's a fairly small fund to start as we work through things, but we expect it to grow quite significantly over time. I'll tell you, without giving away too much, that we have quite grand ambitions for the long term. >> Alright, well let's keep in touch on the deal flow, congratulations on Bitnami, and, we'll see you at the cloud shows, Amazon, Microsoft Ignite, Google Next. >> Everywhere, yep, I'll be there. >> Erica, thanks for coming on and spending some time here on theCUBE. CUBEConversations here in Palo Alto, I'm John Furrier, you're watching CUBEConversations, thanks for watching. (intense orchestral music)

>> From Times Square in the heart of New York City, it's theCUBE, covering Imagine 2018. Brought to you by Automation Anywhere. >> Hey welcome back everybody. Jeff Frick here with theCUBE. We're in downtown Manhattan, actually midtown Manhattan, at Automation Anywhere Imagine 2018, 1100 people talkin' about bots, talkin' about Robotics Process Automation, or RPA. And we're excited to have the guy that counts the money at the end of the day; it's important part of any business. He's a co-founder, Ankur Kothari, Chief Revenue Officer and Co-Founder, Automation Anywhere. Ankur, great to see you. >> Great to be here, Jeff, thanks for having me. >> So, first off, as a co-founder, I think you're the third or fourth co-founder we've had on today. A little bit of reflection since you guys started this like 14 years ago. >> Yeah. Here we are, there's 1100 people, the room is packed. They had the overflow, they're actually all over us out here with the overflow for the keynote. Take a minute and kinda tell us how you feel about how this thing has evolved over time. >> It feels like a great party to be part of. Always, you're always happy. >> Right. >> One of the traits that you'll find a lot of co-founders is that they are always happy, never satisfied. They're always looking for the next big one. >> Right. >> But it's amazing to be part of Imagine because we learn so much from our customers and our partner as well. It's not just that we bring them together and we're talking. We're learning every time. It's becoming a big ecosystem. >> Right. >> And, an idea as big as a bot or a future of work is too big an idea for one company to continue. You want as many people to come. >> Right. >> So, our idea of Imagine was a little bit like Field of Dreams, you build and they'll come and they'll collaborate and it'll become bigger and bigger. >> And look all around us. I mean, we're surrounded by people and really, the ecosystem. >> And the bots as well, there are bots on the walls and everything else. >> Bots on the walls, partners everywhere. So let's dive into it a little bit. I mean, one of the ways that you guys participate in the ecosystem, and the ecosystem participates, is the Bot Store. >> Yes. >> So it's just like any other kind of an app store. >> Exactly. >> You've got people contributing. I assume you guys have contributed stuff. But we saw earlier in the keynote by Accenture, and EY, and Deloitte. And all types of companies are contributing bots into this ecosystem for lots of different functions or applications. So really, an interesting thing. How's that workin' out? Where'd you come up with the idea? And why's that so important? >> At Automation Anywhere we like to ask ourselves hard questions, as the leaders in this space. And we asked ourselves this question, "What can we now do to further accelerate our journey of all our customers to become a digital enterprise?" The answer came that we are to share in the new bot economy. Now once that answer was clear, every economy requires a marketplace. >> Right. >> And that's where the Bot Store came. It's a marketplace where producers meet the consumers, and you connect them. All we do is, we curate and make sure that the right things go up. But other than that, it's just like any other marketplace. And we thought that if we'll build the right marketplace where the producers meet consumers, we have thousands of customers and large companies looking at it. It will allow perfect place where all the right ideas get converted into product. >> Right. >> We have tons of partners who have domain expertise, functional expertise, vertical expertise; they can prioritize their expertise, they can convert it into IP. >> Right. >> They can do it for free, they can monetize it. So there's lots to gain for producers of all these bots. And if I am a consumer, now suddenly my time clock to make further shrinks, because instead of creating these bots all from scratch, I can download them from this Bot Store and snap them together like a Lego block. >> Right. >> So that's how the whole idea came. We launched it just two months ago and we have hundreds-- >> You just launched it two months ago? >> Yeah! And we have hundreds of bots in it. More than 80-100 partners have participated. We are getting at least 20-30 more submissions coming every day, and we have few hundred submissions coming every week. So, just like any free marketplace, it has an exponential nature. And that's the thing we are counting on. >> That's amazing, that you've got that much traction in such a short period of time. >> Thousands of downloads on a daily basis. Thousands of users just in two month's time. >> You know, we go to a ton of shows. We do over a hundred shows a year. And once shows get to a certain size, it starts to change a little bit. But when they're small like this, it's a very intimate affair on a couple floors here at the Sheraton, everyone is still really involved. They're really sharing. >> Yes. >> There's so much sharing of information. Not so much, you know ... Because they're not really competitors. Within their own companies, they're all part of this same team that are trying to implement this new thing. >> Exactly. >> And you really feel it. >> Exactly. >> So, the store's cool, but the bot economy. When you talk about the bot economy, we talk about API economy a lot. >> Yes. >> How do you see the bot economy? What are the factors that drive the bot economy, and how's it gonna evolve over time? >> We look at it as a few elements. The current version, we think that bot economy, like any economy, has a marketplace, which is our Bot Store. We have a program which we call Bot Games, because any good economy, any new economy, one of the trait is that the good idea can come from anyone. >> Right. >> It can come from anyplace. Like, any customers, any partner, anyone can bring. A good economy, what it does is it brings that idea from anyone, and it gives these vehicles for good ideas to take flight. If the idea is good, it becomes viral, and it has vehicles where those ideas can go to market. What we did was, we created a program called Bot Games. Yesterday on May 29th, we had the 1st Inaugural Bot Games. We invited developers, people who are part of these programs and their companies. And we gamified and created different games. And we thought that if we bring all these champions and pioneers and like-minded people in the same room, give them certain same problem, and then gamify it, put a clock on it, a lot of great ideas will come out of it. >> Right. >> And that came. And some of those ideas will make it to the marketplace, like a Bot Store, like an Imagine. >> Right. >> So that's where all the ideas connect to the customers. And the people who bring those ideas, they also come up. So that's the other aspect. So the Bot Games is where the ideas, you can crowdsource from places. Bot Store is where they go to the market. In between there is a gap. And we are trying to remove that gap by creating a stimulus package for this new bot economy. Like any economy time and again requires a stimulus pack, and we have created one. What we have done is that if you want to learn Automation Anywhere, right? If you want to understand, because that gap is you're to understand Automation Anywhere. We have created Automation Anywhere University a year ago. And now anyone can take courses for free to learn how to create bots. Whether they are customers or partners. And then, if you purchase these bots through one of our certified partners, the first three bots in year one are free. So we are removing the friction in between. If you have not started on this journey, your learning is free, you get ideas from different places, we can get these prebuilt bots, and the first three bots, if you purchase it through our partners, they are free. So we are removing that friction. And then, we are supporting that whole economy with the industry's largest customer success program. >> Right. So I'm curious if you know, maybe you don't know, of the bots in the bots store, how many are free and how many are paid, as a percentage? >> Interestingly, I don't have that stat because we don't actually worry about that. We let all our partners and people who are contributing to this Bot Store decide that. >> Right. >> Some bots they may decide to monetize, some they may not. It's listed on the Bot Store. Offhand, I would say-- >> Take a guess. Is it 50/50? A third? Two-thirds? >> The nature of it looks like 50/50. >> That's a good guess. Full caveat, it's a guess. We didn't do the analysis. >> Exactly. But here is the unique aspect. Yesterday we had a Bot Game, and the winner had an amazing idea that none of us had ever think of. He created this bot that automates the COE of all these programs. Now, we are talking. He is thinking of putting that on Bot Store. That's the power of bringing multiple people together. >> Right. >> That's the power of free economy, where the exponential nature of it is what we are counting on. And we are getting on a daily basis these new bot ideas, these new bots that are making it to the Bot Store. Just like your App Store. I go to App Store to get ideas what I can do on my phone. >> Right, right. >> Just like that, now we are finding our customers are going to Bot Store to figure out what else can they automate. >> Right, right. >> And that's been another amazing part of it. >> You know, it's so consistent. All these shows we go to, right? How do you unlock innovation? There's some really simple ways. One is, give more people the power, give more people the tools, and give more people the data. >> Exactly. >> And you'll get stuff out of it that the small subset of people that used to have access to those three things, they never found. They just didn't think of it that way, right? >> Exactly. And then we firmly believe that any technology, anything, once you democratize it, you give it in hands of everyone-- >> Right, right. >> You can't have a thriving economy unless everyone forms their own point of view. Unless everyone creates their own perspective. And that's our vision of this bot economy. We are bringing everyone and giving them these vehicles to try it out. Look, the technology has reached a stage where it's cheaper to try it out than talk about it. >> Yes. >> And we are doing that so that everyone forms their own unique point of view, and then they express that point of view and we connect those points of view to these thousands of customers worldwide. >> Right. >> Good ideas take flight, and all we have to do is create vehicles for those good ideas to take flight. >> Alright. So, Ankur, I gave you the last word before we wrap up here. If we come back next year, a year from now, inspired 2019, what are we gonna be talking about? What's on your roadmap? What're some of the priorities that you guys are workin' on over the next 12 months? >> We are talking about ... The next 12 months, we are looking at how to further accelerate this journey. Because what people are in this, the real problem people are trying to achieve is how to become a digital enterprise. Not just to automate, but how do you create a digital enterprise? You cannot become a digital enterprise unless your operations are digital. You cannot make your operations digital unless your processes are digital. And you cannot do that unless your workforce is digital. So we are trying to create technologies, vehicles, platforms, so that everyone can scale their program. Where pretty much everyone should have a digital colleague. Everyone should be able to create a bot. Everyone should be able to work with a bot. Every process, every department, every system should have a digital workforce working in it and that can allow you to create a digital enterprise that can scale up and scale down with the demand and supply. >> Alright-- >> That's what we are trying to start. >> Well, we look forward to gettin' the update next year. >> Exactly. >> Alright, Ankur, thanks for taking a few minutes out of your busy day with us. >> Thanks for having me here, and I appreciate and enjoy the conversation. >> Alright, he's Ankur, I'm Jeff. We're at Automation Anywhere Imagine 2018. Thanks for watching theCUBE. See you next time.

>> Live from Midtown Manhattan, it's the CUBE. Covering Big Data New York City 2017. Brought to you by SiliconANGLE Media and its ecosystem sponsors. >> Fifth year of coverage of our own event Big Data NYC where we cover all the action in New York City. For this week in big data, in conjunction with Strata Data which was originally Hadoop World in 2010. We've been covering it for eight years. It became Strata Conference, Strata Hadoop, now called Strata Data. Will probably called Strata AI tomorrow. Who knows, but certainly the trends are going in that direction. I'm John Furrier, your co-host. Our next guest here in New York City is Sergei Rabotai, who is the Head of Business Development at InData Labs from Belarus. In town, doing some biz dev in the big data ecosystem. Welcome to theCUBE. >> Yeah. Good morning. >> Great to have you. So, obviously Belarus is becoming known as the Silicon Valley of Eastern Europe. A lot of great talent. We're seeing that really explode. A lot of great stuff going on globally, even though there's a lot of stuff, you know GDPR and all these other things happening. It's clearly a global economy with tech. Silicon Valley still is magical. I live there in Palo Alto but you're starting to see peering points within these ecosystems of entrepreneurship and now big companies are taking advantage of it as well. What do you guys do? I mean you're in the middle of that. What is InData Labs do in context of all this? >> Well, InData Labs is a full stack data science company. Which means that we provide professional services for data strategy, big data engineering and the data science. So, yeah, like you just said, we are based - my team is based in Minsk, Belarus. We are about 40 people strong at the moment. And in our recent years we have been very successful starting this business and we have been getting customers from all over the world, including United States, Great Britain, and European Union. The company was launched about four years ago and very important thing, that it was launched by two tech leaders who come from very data-driven industries. Our CEO, Ilya Kirillov, has been running several EdTech companies for many years. Our second founder, Marat Karpeko, has been holding C-Level positions in one of the most successful gaming companies in the world. >> John: So they know data. They're data guys. >> Yeah they're data guys. They know data from different aspects and that brings synergy to our business. >> You guys bring that expertise now into professional services for us. Give me an example of some of the things someone might want to call you up on, because the thing we're hearing here in New York City this week is look, we need more data sciences and they got to be more productive. They're spending way too much time wrangling and doing stuff that they shouldn't be doing. In the old days, sysadmins were built to let people be productive and they ran the infrastructure. That's not what data scientists should be doing. They're the users. There's a level of setting things up and then there's a level of provisioning, it's actually data assets, but then the data scientists just want to do their job. How do you help companies do that? >> Well I would probably, if I take all of our activities, I would split them into two big parts. First of all, we are helping big companies, who already have a lot of data. We help them in managing this data more effectively. We help them with predictive analytics. We help them with, helping them build the churn prediction and user segmentation solutions. We have been recently involved into several natural language processing projects. In one of our successful key studies we helped one of the largest gaming companies to automate their customer feedback processing. So, like, a couple years ago they were working manually with their customer feedback and we built them a tool that allows them to instantly get the sentiment of what the user says. It's kind of like a voice of a customer, which means they can be more effective in developing new things for their games. So, we-- >> So what would someone engage? I'm just trying to peg a order of magnitude of the levels of engagements you do. Startups come in? Is it big companies? What kind of size scoped work do you do? >> So I would say at the moment we work with startups, but it's a bit of a different approach than we have with big or well-established companies. When startups typically approach us with asking to help them implement some brand new technologies like neural networks or deep learning. So they want to be effective from the start. They want to use the cutting edge technology to be more attractive, to provide a better value on the market and just to be effective and to be a successful business from the start. The other part, the well-established companies, who already have the data but they understand that so far their data might not be used that effectively as it should have been used. Therefore, they approach us with a request to help them to get more insights out of the data. Let's say, implement some machine learning that can help them. >> How about larger companies? What kind of projects do you work for them? >> It could be a typical project like churn prediction, that is very actual for the companies who have got a lot of customer data. Then it could be companies from such industries like betting industry, where churn is a very big issue. And, the same probably applies to companies who do trading. >> So is scale one of the things you differentiate around? It sounds like your founders have an EdTech background obviously must be a larger, large data set. Is your profile of engagements large scale? Is it ... I'm just trying to get a handle of if someone's watching who, what is the kind of engagements people should be calling you for? Give us an example of that. >> Like, let's say there is a company who has got a lot of customer data, has got some products and they have a problem of churn, or they have a problem of segmenting their customers so they can later address the specific segments of the customers with the right offers at the right time and through the right marketing channel. Then it could be customers or requests where natural text processing is required where we have to automate some understanding of the written or spoken text. Then I should say that we have been getting recently some requests where computer vision skills are required. I think the first stage of AI being really intelligent was the speech recognition and I think nowadays we manage to reach to the level of what we earlier saw in fantastic movies or sci-fi movies. Computer vision is going to be the next leap in all that AI buzz we're having at the moment. >> So you solve, the problem that you solve for customers is data problems. If they're swimming in a lot of data, you can help them. >> Sergei: Yep. >> If they actually want to make that data do things that are cutting edge, you guys can help them. >> Sergei: Yeah. That's-- >> Alright, so here's a question for you. I mean, Belarus has obviously got good things going on. I've heard the press that you guys have been getting, the whole area, and you guys in particular. So I'm a buyer, one of the questions I might ask is "Hey Sergei, how do I know that you'll keep that talent because the churn is always a big problem. I've dealt with outsourcing before and in the US it's hard to keep talent but I've heard there's a churn." How do you guys keep the talent in the country? How do you keep talent on the projects? Is there certain economic rules over there? What's happening in Belarus? Give us the economical. >> Yeah, so, basically what you're saying. The churn problem has always been known for companies who have their development teams in Asian regions. That's a known problem because I have a lot of meetings with clients in the UK and the US, potential prospects, I would say. So they say it is a problem for them. With Belarus, I don't think we have that because from what I know, we have an average churn of under 10 percent. That's the figures across the industry. In smaller companies, the churn is even less and there are specific reasons for that. First of all, that due to Belarusian mentality, we always try to keep to a job that we're having. Yeah? So we do not-- >> John: That's a cultural thing. >> That's just the cultural thing. We do not ... >> You honor, you honor a code, if you will. >> Yeah. >> Okay. >> So, that's one of the things. Another thing is that Belarusian IT industry is very small. We have, I would say, no more than 40 thousand people being involved in different IT companies. The community is very small, so if somebody is hopping jobs from one job to another, it is going to be known and this person is not likely to have like, a good career. >> So job hoppers is kind of like a code of community, honor. Silicon Valley works that way too, by the way. >> Yeah. >> You get identified, that's who you are. >> Yeah. And so nowadays-- >> Economic tax breaks going on over there? What's the government to get involved? >> One of the key things is, the special tax and legal regulations that Belarus has got at the moment. I can definitely say that there is no country in the world that has got the same tax preferences, and the same support from the government. If a Belarusian company, IT company, becomes a part of Belarusian High Tech Park it means the company becomes automatically exempt from BET tax, corporate income tax. The employees of that company having the reliefs on their income, personal income tax rate, and there are a lot more reliefs that make the talent stay in the country. Having this relief for the IT business allows the companies to provide better working conditions for the employees and stop the people from migrating to other parts of the world. That's what we have. >> Sort of created an environment where there's not a lot of migration out of the area. The tech community kind of does it's own policing of behavior for innovation. >> Yeah but I think before those initiatives were adopted there was a certain percentage of people migrating but I think that nowadays even if it happens, yes, you're right, it's not that substantial. >> Great. Tell us ... Great overview of the company and congratulations, it's a good opportunity for folks watching to explore new areas of talent, especially ones that have the work ethic and knowledge you guys have over there. New York here, there's codes here too. Get the job done. Be on time. What's your experience like in New York here? What's your goal this week? What's some of the meetings you're having? Share with the folks kind of your game plan for Big Data NYC. >> Well, yeah, I've really enjoyed my stay here. It, so far, has been a very enjoyable experience. From the business perspective, I had over 10 meetings with the prospective customers. And we are likely to have follow-ups coming in the next couple of weeks. I can definitely say there is a great demand for professional services. You can see that if you go to whichever center you can see there's a lot of jobs being posted on the job boards. It means that there is lack of knowledge here in the US, yeah? One more important thing that I wanted to share with you from my personal observations that USA, UK and maybe Nordic countries, they have very, very strong background for creating the business ideas but Eastern Europe or Eastern European countries and Belarus in particular, they are very strong in actually implementing those ideas. >> Building them. >> Yes, building them. I think we have lots of synergies and we can ... we can ... >> John: Great. >> We can work together. I also got some meetings with our existing customers here in the US and so far we had good experiences. I can see that New York is moving fast. I travel a lot. I've been to over 40 countries in the previous five years and I just ... New York is different. >> It's fun. >> Different. Even different from many other cities in the US. >> Lot of banks are here. Lot of business in New York. New York is a great town. Love New York City. It's one of my favorites. Love coming here as I grew up right across the river in New Jersey. >> Yeah. But, great town, obviously California, Palo Alto, >> Yeah. >> Is a little more softer in terms of weather, but they have a culture there too. Sounds a lot like what's going on in Belarus, so congratulations. If we get some business for you, should we give them theCUBE discount, tell them John sent you and you get 10 percent off? Alright? >> Alright, yes. Sounds great. We can make it a good deal. (laughter) >> Tell them John sent you, you get 10% off. No I'm only kidding because it's services. Congratulations. Final question. What's the number one thing that people are buying for service from you guys? Number one thing. What's the most requested service you provide? >> The most requested services ... First of all, many customers they understand that they have got a lot of data. They want to do something with their data. But before you actually do some implementation you have to do a lot of discovery or preparatory work. I would say, no matter how we end up with a customer, this stage is basically ... The idea of that stage is to identify the ways data science can be implemented and can provide benefits to the business. That's the most important. I think that, like, 95 percent of the customers they approach us with this thing in the first place. And based on the results of that preparatory stage we can then advise the customers. What can they do? Or how they can actually benefit from the existing data? Or what other things they should collect in order to make their business more effective. >> Sergei, thanks for coming on. Belarus has got a lot of builders there. Check 'em out. >> Thanks a lot. >> Builders are critical in this new world. Lots of them with clout, a lot of great opportunities. A lot of builders in Belarus. This is theCUBE, bringing you all the action from New York City. More after this short break. We'll be right back. (theme music) (no audio) >> Hi, I'm John Furrier, the co-founder of SiliconANGLE Media and co-host of theCUBE. I've been in the tech ...