(energetic classical music) >> Welcome to Cube Conversations. I'm Stu Miniman. Here with the CEO and co-founder of ThousandEyes Mohit Lad. Thanks so much for joining us here in our Palo Alto studio. >> Thanks too. I'm excited to be here. >> Alright, we always love when we get the founders on. So before we get into the company, take us back. What was the why, what were you seeing in the marketplace, and bring our audience a little bit about your background in the team and what you bring to the table. >> Sounds good. So, my background, personally, is I finished my PhD at TCLA and studied computer science, focused more on the Internet. And one of the reasons we focused-- my co-founder was my colleague as well-- and one of the reasons we focused on studying the Internet was we believed that it was going to dramatically transform our lives, and the quality of our life eventually will be highly dependent on the quality of the Internet. So that's essentially the reason we focused on researching on the Internet, on connectivity and performance. And then as we came out of grad school, and looked at the market, it was clear to us that the ship of the enterprise was dramatically changing because of the adoption of cloud, and SaaS, and infrastructure of service, and that the Internet was going to be a key component of what an enterprise looks like, and it was a black box. So our thesis behind starting the company was to really help companies understand how to manage Internet-centric WAN environments, which is what today's world looks like. >> Okay, for people that don't know ThousandEyes give us how long's the company been in business, the state of the product, how many customers you have, funding, and the like. Give us a snapshot. >> Yeah, so we started in 2010. We had an odd start in many ways because we didn't start with venture funding, so started with a small national SAANS foundation grant. And the result of that was we were very focused on customers from the early days. So for the first two years, very small, about three or four people, and then raised our first round funding in 2012 through Sequoia Capital. As of today, we're about 220 plus employees headquartered in San Francisco. And we split our engineering between San Francisco and London, so these are the two hubs. We also have offices in Austin and New York. And in terms of customers, close to 500 customers at this point of time, a heavy concentration in the mid to high end of the market, so we have more than 50 Fortune 500s, a large concentration of the top financials, and really what excites us is the fact that we're helping decode some really, really complex environments that are becoming more and more complex. >> Yeah, I loved that starting point. You find, in the networking world, there's a lot. It's government, it's scientific, need to understand this. Internet's been a distributor of architecture since the early days, but it's been going through a lot of transformations. Heck, even the TV show Silicon Valley's even talking about a "new Internet." And it's so funny for me to watch that because I'm like, oh wait, I'm talking to the people in here in Silicon Valley that are actually building that with blockchain and decentralization and the like, so its mirroring what's happening in the real world. >> Yeah, and the thing that people sometimes don't realize is the Internet was not built for enterprises. And I tell customers that when you're going to Office 365, when you're going to Amazon, you're relying on the same Internet that your kids are using to watch cat videos. And that's what's carrying your production traffic, and it's really difficult for enterprises to actually make sense of what's slowing things down, where the risk is, what's breaking, and that's where we really help companies understand and take control and thrive in these connected environments. >> It was funny, years ago we used to talk about "the consumerization of IT," and what people use at home will work its way into the enterprise, but you're right. What do businesses need that's different? ThousandEyes has, I believe you call it "Network Intelligence." How is that different than the public standard Internet that you like, and tell us a little bit about what your secret sauce is and what you're bringing to the customers. >> If you think about enterprises from 20 years ago, all the applications would be on the data centers, and it would be a pretty closed environment connected through MPLS connections and so on. So you could deploy the standard APM technologies on the data center to understand what's going on with the applications. And now if you fast forward to today, when you're using something like Office 365 or SalesForce or Workday, or so on, the applications don't sit on your premises anymore, and your network is not just your priority network, but a large portion, in fact, majority of your environment is actually the public Internet. So what is needed for you to thrive in this environment is the ability to actually understand what you depend on and be able to map out not just the user experience of applications that you don't control anymore, but the underlying factors that are impacting that application. And so what we're doing is essentially creating a huge, humongous data set on public performance of the Internet, of different components of the Internet. And we do this with some tremendous data collection but also a lot of smart heuristics that we've built on top, which makes sense of it. And then we marry this data with data we also collect from inside the enterprise. So what we're creating is this environment of a seamless network, and take off this notion of networks today are borderless, right? They really don't have any sort of borders around where the edges and so on. And what we're doing is making sure that customers can look at these hybrid environments as if it's their own private network. >> It's interesting, I think back, when we moved from the client/server era to now, the SaaS environments, like, oh, it'll just magically all work anywhere. I think back to Citrix, has a very heavy networking piece to be able to make those work anywhere. What needs to be fixed, what's kind of under the covers that most people don't understand that in a SaaS environment, solutions like yours are helping to make sure that I can have the promise of anywhere, any device, any cloud? >> Yeah, so a few different things. It's not just the applications are moving to cloud, SaaS. The users are also starting to be a lot more remote and mobile, and what that creates is an environment where a user may be unhappy with the performance of Office 365, and IT's responsible for solving that issue when the traffic is entirely bypassing the corporate environment. So it's going from a Starbucks coffee shop to Office 365 servers, and that's the environment that you're responsible for even though you don't physically control that. And as you think about that, the way we thought about the solution was not just essentially give people visibility into these complex environments, but also create an ecoystem where all these SaaS companies that you rely on as an enterprise are ThousandEyes customers. And we help them decode the Internet, and to large extent, deal with the Internet when they're delivering an application. But as an enterprise, if you're using one of these top SaaS applications, by using ThousandEyes you can not only understand the performance, but you can speak the same language with them when you are trying to troubleshoot and come into a consistent understanding of what the performance is. >> So, you're working with the SaaS providers, you're working with the enterprise, sounds like you're working with both. If I'm an enterprise CIO, and okay, yes, I'm pushing my people to work remote and everything like that, I can't worry about 10,000 employees and the network that they had. Help explain how that works. >> Right, so the requirements of a solution for today's world is beyond just giving visibility. Even if you rewind to the world from 20 years ago, you would find that when there's an issue, there's a lot of finger-pointing going on between the server team, the app team, the network team, and that finger-pointing has become worse in a multi-tenant environment, especially as you use third parties for your applications. So as an example from a few weeks ago, Amazon had a major outage in the East coast. And not only did it take down applications that were hosted on Amazon, but we had customers that were surprised that their applications were not working, and the reason they were not working was they were making, for example, API calls, where the API provider was hosted in Amazon. So they did not even realize the dependencies that they were bringing into their environment. So we had a situation where if we're using a messaging service, and I can't message the person sitting in front of me, because it's going through the Amazon environment. And so its really important in this ecoystem that we as a technology provider create something that helps you connect with each other, rather than just be a siloed solution and that's a huge part of our value chain is to make sure that we can provide you the technology that helps you see through different environments, but also establish good communications back and forth. >> Mohit, networking as an industry has tended to be one of the slower moving pieces of our market. The WAN has been going through such a transformation. You launched in 2010, from 2010 to now 2018, cloud is a much bigger piece, SDWAN wasn't part of our vocabulary. How are thing different now than when you launched the company and how has that impacted your product and your engagement with customers? >> That's a great question. One of the things that I see a lot is this shift in, at least some of the leading customers that we have, a shift towards the notion of network as a core competency. And what I mean by this is when you had environments which were static, so, you're familiar with Visio. People would use Visio to do their network topology maps. They would not change for five years, or maybe three years, depending on the customers. But if you do a Visio map of your extended environment today, it's invalid one second after it's done because the Internet is constantly changing. And so the notion of this network being a static thing is not valid anymore, and companies that need to thrive have to really treat the network as a core competency--and by network, it's not just a network, it's a skill set around networks. Coming back to the trends, the trends that you're seeing are essentially being driven by the fact that you do need to take control of the network, you do need to actually manage it, much more than you used to manage it in the past, and that will give you an edge when it comes to performance to cloud applications, better connectivities, sometimes in situations like SDVAN, it's around reducing cost through MPLS links. >> You've got kind of opposing forces when you look at that. Networking should be a core competency, but don't we have to have to have more intelligence in the network? Leverage all the analytics: machine learning and AI should manage that, 'cause it's changing so fast I can't wait for a person to do that. How do you balance that, how do your customers look at that, and how's that fit into your product? >> So absolutely right, I think networking should be a core competency but networking is not just about connecting devices and using wires to connect things. It's around really understanding what's happening, even understanding what the network actually looks like, because that's something you don't control. There's a lot of focus that we put on analytics, and one of the notions that we've developed over the many years is this notion of network intelligence. And the idea is pretty straightforward. When you're using an Amazon or an Azure, you're going through the same public environments that other customers are going through, and what we do is we essentially mine our entire data set, really understand what are the aspects of the network that are affecting multiple customers, and bridge that into a single cohesive view that is beneficial for you guys. So for example, if you have connectivity issues from the offices here at the CUBE to an Amazon, you would not only know whether it's just you, but you would have more perspective on, hey, this is a larger segment of the customer base of ThousandEyes is actually going through an issue, and here's where the specific issues are. So one of the benefits that the ThousandEyes ecosystem brings to customers is every customer that we add creates more value in the data set. >> How will some of the big waves coming like 5G, IoT, all of the Edge pieces, does that tie into the offering that you have? >> Ultimately, the common denominator for all of this is the Internet, right? Some of these technologies are more towards the last mile, but they have to go through the same core, the Internet, and it's really interesting because one of the user events we did in London a couple weeks ago, we had one of our customers, a large manufacturing company, and they were talking about how they were drilling in Texas, but the drilling was controlled through a site in Belgium, and all of this only worked because the connectivity was reliable. So they were using ThousandEyes to actually ensure that the connectivity between their giant 50 ton driller was maintained to their headquarters. So those are the kinds of applications that, we didn't build it for this specific application, but the fact is we find new ways that ThousandEyes is being used, essentially because there's more and more reliance on the Internet to make things work. >> Any other customer use cases that you want to highlight? Any customer case studies you can share? >> Yeah, so we primarily help with very broadly two sorts of use cases. So one aspect is if you are providing an online service that really depends on the Internet, has a global audience, or even a large regional audience, we help those customers really understand the user experience across the Internet and understand what parts of the Internet may be impacting the applications. So think about all the major SaaS companies that use ThousandEyes, all the major retail banks, they have an online asset that they care about, that's one use case. And then the other use case is enterprise companies. So this is everything from oil and gas, to tech enterprises, to financials. They depend more and more on the Internet when they are going into Cloud and SaaS, and for them it's really unnerving when they look at the environment they're getting into and have no visibility into this black box. So that's where we provide them intelligence into this extended environment and help them understand why a user may be having issues to Office 365 or WebEx, or all of the WYS or IP solutions that are also more and more Internet dependent. >> Mohit, how are your customers doing with the rapid pace of change here? You've talked about networking is a skillset. Finding the right skillset and training people up has always been a big challenge, but what are you seeing in the customers you're talking to? How are they doing these days? >> So the customer's very, depending on the maturity and the transition that they're going through, I still find in a lot of regions that the cloud is still new, SaaS is still new, and we're in many ways in a bubble in the value. Things happen pretty quickly here, but as you step outside you realize that some of the companies are ready to scorse and still making their first strides into SaaS and cloud, and one of the things we help these sets of customers with is essentially helping them plan towards that move. So if you have a large deployment, if you're making a large shift in your infrastructure, even, you think about, let's say a situation where I want to get rid of MPLS, I want to rely on direct Internet circuits, that's a big change, and we can help you measure the performance of MPLS performance of Internet and help you make that data-driven decision. Coming back to the notion of how our customer is doing, there are customers that have realized that network skillsets and engineering around that is core, so they invest a lot of efforts into building that core mindset. There are customers that are starting to build that, and there are customers that are looking at partners to bring that expertise in. So these customers will never build a core set of function around networking, but they look at partners, managed service providers that can bring that expertise into the environments. >> Last thing I want to ask you. You're talking about global networks, we haven't talked about security. Governance and compliance is usually some of the biggest challenges that we are having. The macroeconomic challenges of the Internet. We interviewed the president of ICANN a few years ago, and he gave a warning to our audience that said we might not have one Internet in this near future. We already are starting to see a fragmented Internet, and that could be a huge challenge. Security, governance, compliance, big topics here, but maybe bring us home on that as to what you're seeing and how that affects. >> So one of the things the Internet does, it connects people, right? And when it connects people it also makes it easy for the bad guys to reach the good guys, and so things that concern our audiences in terms of security. The way the Internet works, it's very easy for somebody to announce your address space, for example, and this has happened on several occasions, which creates a denial of service, a different denial of service where all the traffic would go to a party, which is announcing your address space, but not you. So there's all these issues where DNS mapping could be changed, the routing could be changed, and our DDoS attack that happens takes a lot of the upstream environment that you have out of the equation. And so as every day passes, there's more and more things that are being discovered in terms of how attacks can be generated, and how organizations can be brought down. So one example I'll give you which is very specific I've seen is in denial-of-service attacks, this is starting to become pretty routine in today's world. It started with the solutions being on-prem solutions that would detect the volume of traffic and try to filter traffic, and then it moved to using cloud-based solutions, because the volume of traffic would be so high, that you could not actually do this on your end. So you use these cloud-based solutions. You would turn them on when you would detect an attack, and then turn them off. And the financials in particular were always under attack, so now they've gone to a model where they're always turning these things on. A DDoS mediation service, which is based in the cloud. And what has happened, this is a really interesting phenomenon that we've seen, is, let's say, a particular bank, let's say Bank of America is under attack. The same provider that's protecting Bank of America is also protecting Wells Fargo and JP Morgan, and that infrastructure under stress could mean that Wells Fargo could actually have availability issues even though they are not under attack. So one of the things we see in the Internet is this notion of collateral damage, where you may not be the actual victim or target of an attack, but because of shared infrastructure, you're collateral damage. These are the scenarios which place more and more of an importance on gathering this intelligence on what's going on in the Internet. >> Mohit Lad, really appreciate you coming to help share with our audience everything that's happening in the WAN, network intelligence, multi-cloud, global environment world. Look forward to catching up with you more in the future. This has been a CUBE Conversation, I'm Stu Miniman, thanks for watching the CUBE. (energetic classical music)

>> Hi, I'm Peter Burris, welcome to this Cube Conversation, where we bring some of the best ideas in the industry to the Wikibon, SiliconANGLE communities as a way of catalyzing further conversation about some of the changes, and some of the opportunities that are presented by tech in a world that's digitally transforming. We're being joined today by Bobby Patrick, who's the CMO of a company called UiPath. UiPath is one of the leaders in a technology known as robotic process automation. And we're going to talk about the problems, the solutions, and the directions forward with this, what we regard as a very, very important technology on the rise. Bobby, welcome to the Cube. >> Hi Peter, great to be here. >> So Bobby, let's start with who are you? Tell us a little bit about yourself. >> Sure, Bobby Patrick, CMO, UiPath. I was CMO of the cloud business HPE prior, a Cube alumni, I guess we call them, right? And had a history of startups, in SQL space, and open source, and different transformational companies. But I was really intrigued by the idea of software robots over the last six months, and joined UiPath, and it's just been an amazing adventure to see this kind of amazing technology really deliver outcomes for companies faster than I've ever seen happen in tech in my history. >> Well let's talk about that, so, every technology that's going to be successful has to target a problem, a group of people who are trying to solve the problem, and a set of returns. So let's talk about, what is the problem that UiPath and related technologies are actually trying to address? >> Let me start at the macro level first of all. Robotic process automation is instructive trend for digital transformation. For the last three, five, seven years, vendors and companies have said, "I want to go digital." Digital, digital, digital. Right? And going digital's really difficult. Back office processes and front office processes are complex, there's a lot of human interaction involvement in it, and in the past, the way to tackle that would be IT would engage in a significant integration project, an IT project, would purchase equipment, technology, and try to rebuild and redefine the process. Robotic process automation tackles that problem of digital transformation in a very different way. It says forget the idea of going and redoing all of the systems in the data. Let's just take it from the human perspective. Let's see how does a human engage in the process today? And let's completely mimic that human interaction. Let's do that in a way that has complete accuracy, actually higher compliance, and do that in a way that's very simple. And so our technology, which has been built over a number of years, has now perfected the ability to actually replicate and emulate a human user, interacting with multiple systems, something they do every day, in the enter process, move data around, analyze data, look at the data for context, and then execute that process continuously. And that has resulted in an industry that is booming. Forrester said last year it was a $250 million industry, it'll be a $3 billion industry in three years. And UiPath is the fastest growing company in what's called RPA. >> So let me break that down a little bit. So a couple of general principles. The computing industry has always been focused on how we can substitute technology, specifically in the form of programs, for labor. And when we do that, we're able to reduce errors, we're able to speed up the activities, we have derivative opportunities to integrate things we never did before. So let me see if I got this right. What you just described is, instead of trying to substitute for that labor, by creating a net new program that has a whole bunch of static elements, we're actually going to turn these tools and apply them to the question of, how do people do things, let's substitute for the things that people do, start there. Have I got that right? >> Yeah, I mean imagine a contact center in a customer service operation for an airline. They receive an email from a customer that's complaining, about a bad flight, that contact center specialist has to look at a variety of systems to determine your status, what did we give you recently, in two days they will respond. Maybe the person's name is Michelle, and they'll respond in two days, and give you something. Well now, Michelle the software robot can do that exact same thing in a matter of minutes, with complete accuracy, and you can apply machine learning to it, and AI to it, to determine, 95% of the time, if I provide this in this situation, I'll have a happy flier, a happy member. That's what we're talking about here, which is software robots that essentially are perfecting these complex business processes both in the back office and in the front office. Often where lots of documentation's involved, lots of different systems are involved, and a human has to interact between all of those over and over. >> So, RPA, effectively, robotic process automation, effectively provides a means to mimic the work of a person. Because that's where most process engineering is done. Mimic the work of a person, codify it in a way that actually leads to a better business outcome. So that's what it is. Now take us through how does this work? Who are the people involved in the process, what does the technology do for them, how long does it take? Give us a little bit about it. >> So one of the beauties to RPA is that this doesn't require deep engineering talent to be able to build a software robot, and execute it. In fact, some of the breakthroughs in the technology that's been created at UiPath are a studio designer, which looks much like Visio, where you can drag and drop a workflow. Subject matter experts are becoming the next coders, really. Where they can actually design the workflow. There's actually a recorder function that can actually record the user-- >> That's where it starts. It starts with the recorder looking at how people are doing things and picking up that, and turning that in semantics that are meaningful to-- >> Yeah, defining a workflow. Which has exceptions, and handling. I should mention, when you're creating, or you're automating a process, there are really two kinds of robots you're designing. One is one called an attended robot, where along that workflow that robot's going to stop and ask a human a question. It's about a third of the market right now. So the process executes and a human might have to fill in some gaps alone the way. An unattended robot can run in the cloud, or on a VM in an on-premises data center, and execute that process behind the scenes, over and over and over.. So you kind of, you're building one of two. And UiPath supports both attended and unattended robots. But yes, you're designing the workflow, that workflow may interact with a variety of systems, you might receive an email and read the email, the robot reads the email. You might actually log into salesforce.com to find out if they're a customer. You might actually upload the email as a artifact, you might then download some information, put it into a PDF, and send it on. That's an example of a workflow that you're automating end to end. >> So we've got that workflow designed, what are we doing next with it? And who's doing it? >> So this is one of the beauties, too. One of the challenges in IT is projects take a long time. But in RPA-- >> Peter: And they fail. >> And they fail. What's interesting in RPA, what we've proven now, is you can pretty much begin to digitize a process in a matter of weeks. The outcomes are almost immediate. And payback periods are often six months or less. An RPA project almost self-funds itself, which is one reason why I think this is taking off so fast as well. >> So if we want to get a payback period in six months, it means that the whole notion of how fast does it take to get a group up and running on this, becomes crucial. So what is RPA typically, who's it typically targeting? Is it a professional software developer, someone with no technology expertise, business analysts, where-- >> Business analysts, definitely. You're talking line of business. You're talking finance operation. There's a lot of innovation in finance operations. How do I improve my ability to handle invoice reconciliation, and manage purchase orders, and all that paperwork and movement of data. >> So these are people that are familiar with workflows, they're familiar with process design, et cetera, but may not be familiar with coding >> These are subject matter experts. They're not familiar with coding, but they know the process really well. They know what to do when there's an exception, they know what to do in a sequence of events, and so that's why we often say subject matter experts are the next big coders, because they can actually go and learn, in fact UiPath, we have a program called an academy. Academy is on our site, we launched it last April. 35,000 people have been certified already. These are typically business analysts who go get trained, online, self-led, get a diploma, a foundational or an advanced diploma, and are RPA developers, in fact. Now you can go deep. There's C#, you can develop and you can go deep behind it. So I'm not saying there's not some ability to go really deep in certain development. But for the most part, you're a finance operation, you're an HR operation. I'll give you an example of one that just popped up yesterday. A company called West Monroe, they're a consulting firm in Chicago, they announced that they built Rosie the Robot. And Rosie the Robot, with UiPath, is a robot that onboards all their new employees. And they're doing a lot of M and A. They're growing really fast. And onboarding all the employees was a task that required a lot of people to do a very system data intensive process. Now Rosie does all that for them. Very simple example, you can then kind of zoom out and realize that really every process, most processes, have some kind of human interaction repetitiveness to them which a robot can either assist a knowledge worker, or can actually execute that entire process flawlessly. >> Now, we're not talking about technology that's really esoteric, that requires an enormous net new experience in learning from an operations staff. We're talking about technologies that can be targeted specifically to a problem, and end up generating artifacts that are familiar to what's currently in place. Have I got that right? >> Yeah, and I think what's important, so enterprise RPA really addresses two sides. One, the business side, that's trying to digitize a process and automate, maybe for cost savings, but more important than trying to apply AI. And get smarter, right? And so that's the business side. It also addresses the IT side, which is, okay, I've got to secure these robots, how do they scale, how do I manage and govern them, imagine having thousands and thousands of robots. I'll give you another example. NASA. The first robots that NASA launched, the first one, they named George Washington. And George did a-- >> Good name. >> Bunch of work for the finance group, and they got really comfortable with George. They'd walk in in the morning and say, "What has George done for me last night?" Which is awesome. But George was onboarded just like a human worker. Meaning he has to log in to different systems, just like a human worker, and by the way, his password expires every 90 days. So how do they solve that? They created the boss robot. And the boss robot's name? Constitution. Constitution changes George's password every 90 days. That's what's happening here, is you're building out your digital workforce. So IT worries, then, about how do I manage and secure, and scale, so we think about scalability, and big scale is a big challenge, but opportunity that we're focused on, tens of thousands of robots that companies will have. We often say it'll ultimately be one robot per every employee. >> So we have not, or I think you've mentioned the word, or the phrase, "AI" just once. So this is utilizing similar kinds of concept. The attended versus unattended, for example. How you go about training. But I got to believe that there's going to be a roadmap for integrating a whole bunch of these new technologies, that are capable of providing even more degrees of freedom, more functionality, how is RPA and some of these new technologies going to intersect over the course of the next few years? >> This is a really, really important question. So RPA, and enterprise RPA and UiPath, we believe it's a platform. So once you digitize that process, you can then do things with it. We've opened APIs, it's very extensible, you can integrate with a conversation API of Watson, integrate with a chat bot and have the robots do the back end work. At Exxon, they're doing IOT, and deploying sensors left and right, but all the systems in the back end are legacy systems and Excel spreadsheets. So the robots actually are the back end, supporting the deployment of IOT on the front end. So you have this amazing combination. But what people really want to do, then, is they want to look at that process and say, "How do I make it smarter? "How do I improve the productivity over time?" It's great to get that initial bump of perhaps cost savings, when you think about the robot doing, what eight FTEs did, the one robot does. So that's one thing. But the bigger thing is being able to apply data science to the process, looking for ways to mine the process, to think about how can I do the execution better? And that's when we apply machine learning to a process. Where we can actually look, instead of having a rule, in the process that executes, you actually have the experience. Where you say, oh 90% of the time it happens this way. So I'll fill the field in, instead of going and tracking down an empty field. So you can really get smarter, and really improve productivity. Peter, this is all about productivity. GE's a great example of one, that spoke at a conference of ours recently. And the first nine months, they had $25 million of productivity from the robots. The next nine months, $150 million. But this is not about cost-cutting or employees. This is about, actually, hiring. This is about getting smarter in every process. This is about eliminating errors completely. >> Well, productivity is not just a function of the denominator, which is cost. It's also a function of the work that you can perform. And so what you're saying is that utilizing these technologies, while it may displace certain laborious tasks, nonetheless, it's automating and improving the quality of a whole bunch of others, which allows people to go off and do net new things that perhaps are better in service to customers, for example. >> Yeah, one of the fast savings we're seeing from our customers is that they're actually able to use robots to fill the gap of being able to hire new employees. So that, in Japan, here's a great, Japan's almost a unique market. Japan RPA, and UiPath is used on some of the world's largest RPA projects, like SMBC Bank, or Dentsu, the advertising agency, company, there, they're using robots to address two things. One, the decaying population, so robots are filling the gap. And also, two, suicide. There are very high suicide rate because they work these amazing hours every week. Well they're actually using robots to reduce the number of hours, as the robots complement the work of the workforce in Japan. So we're really seeing, interestingly enough, is that robots are actually filling the gaps, and beginning to do work of a workforce that maybe you wish you could hire but you can't hire. So I think that trend is what we're going to see more of in 2018. >> Excellent. So, Bobby, thank you very much for coming on the Cube, here in our Palo Alto studios, and talking to us about RPA, robotic process automation. We heard a little bit about what is it, how does it work, what's the impacts of using it, and obviously, UiPath and yourself as a increasing or emerging force within an important new marketplace for enterprises and users who are trying to increase their productivity. >> Thank you, Peter. >> Once again, this is Peter Burris, in a Cube Conversation with thought leader Bobby Patrick at UiPath. Bobby, again, thanks for coming. >> Bobby: Thank you.

>> Announcer: Live from San Francisco, it's The Cube covering Informatica World 2017, brought to you by Informatica. >> Hey, welcome back, everyone. Live here in San Francisco for Informatica World 2017. This is The Cube's exclusive coverage. I'm John Furrier with SiliconANGLE and The Cube. My co-host, Peter Burris with Wikibon Research. Our next guest, Justin Donlon, the Business Applications Manager, Carbonite; a customer of Informatica, welcome to The Cube. >> Thanks, it's great to be here. >> So you've done a lot of interesting things. We were just talking before you came on camera. >> Yeah. >> Really hard. Moving to the cloud was really easy. >> Right, it helped us big time. >> So tell us about some of the interesting things you've got going on. >> Okay, well, this is a great use-case which we've been speaking about here at Informatica World. We sell through a number of distributors and through probably 8000, 9000 partners, but two of our distributors. We didn't have an e-comm way of interacting with him so we built up this manual, semi-manual process. We actually called it the manual, automated, auto-process. (laughing) That's what we called it. So we built up this process and we just thought we can't keep going like this. We had received a purchase order in email, send it over to sales ops then open it, validate it , does this make sense? They agree, sign it off, pass it onto finance. Finance would open it, say, "yep, makes sense," key it into our great playing system, (mumbles), pass it on to provisioning. This is for a SaaS product that we sell. It's just not scalable at all. >> John: A lot of touch points through there-- >> Too many touch points and a delay for something that should be instant. So we spoke to these distributors and said, "What do you have, what can we do?" We didn't have any options for API integration, so they said, "Well, we've got EDI," so we said, "Okay, first question, what does that stand for?" (laughing) 'Cause we were a cutting-edge company, you know and everything that we do is kind of, >> So 1980s. >> Yeah, I know. Kind of bleeding into it. so we kind of did our homework a little bit and found out what EDI is electronic-- >> John: Where do we sign up for it? >> Yeah, Electronic Data Interchange and then we said, "How are we going to do this?" We kind of looked around a little bit, spoke to our partners at Informatica and I said, "You know, we've got a EDI-capability in the cloud." So we said, "Great, let's do a POC," so we did that POC, banged it together pretty quickly, which is the beauty of a SaaS offering, or the beauty of the cloud, and as we were building this up, we were working with our counterparts at these distributors. These guys who lived and breathed EDI for all their partners and at some point, I just thought you know, we're building this thing up, I don't have anything to compare it to. How do we know if we're even building the right thing? We're just going on what we think seems to be making sense so I phoned him up one day and I said, "Listen, would you mind just taking an hour "and let me walk through what we're building here? "Let me just show you what we're building. "See if it makes any sense." And so he said, "Sure, I'll be happy to do that." He knows EDI back to front and as you mentioned just now it's a very complex, very in-depth, old-school kind of system, old-school, we're processing transactions. I showed him what we'd built out and (mumbles) leveraged Informatica, Salesforce as a front-end. There's a really, really kind of bolted on solution, but we managed to put it together in a few months. I showed him each part and at some point, or at many points, I was waiting for him to interrupt and say, "Well, hang on a second, why are you doing that?" But he didn't, he was silent through everything. So I thought, "Okay, what have we done here?" And so I turned it over to him and I said, "What do you think, is this okay? "Are we doing the right thing?" And he paused for a second and then he said, "Yeah," he says, "this is actually quite an elegant solution "that you've built out in a few months. "This is what has taken us 10 years to mature into." >> John: He was mad! >> I think he was a little mad and for me, it was just a big sigh of relief as I thought, "Okay, we're actually are on track," and we've actually been able to do something really quickly and elegantly through a SaaS product, through these cloud offerings. >> That's a great use case of Informatica. You've taken something that's hard and cloud made it easy for you to do and you had no baggage. In this case, it was a green field for you. What other end-to-end examples are you guys working on because data is now going end-to-end and sometimes it's multi-vendor, of course, but cloud's going to help you. You got there, anything you got else going on? Into any IOT, big data stuff you happening? >> IOT, well, more especially, big data is becoming more and more important to us. As we've kind of grown through our consumer business, Carbonite started out as a consumer product, and as well over one and a half million consumer subscribers and is moved into the very small business, then into this kind of SMB space and a little bit into the enterprise space, and as we've been doing that, we need to understand what we're doing, especially at very small business through the enterprise space. We've acquired these companies. One of the key things we need to do as we acquire companies is identify opportunities for cross-sell and for up-sell, and in order for to do that, we've got to get that data into one repository where we can figure it out pretty quickly. So that's a huge initiative at Carbonite at the moment is building out our data vault and our data legs and getting some accurate and good data governance as we fee this data into these data vaults with our analytics team. >> Peter: That's on the operational side? >> Yeah, that's on the operational side. >> So what Carbonite does is as a service to your customers, which is, I'm not going to say it's standard, but it's some really value-complex, complex things that you do. Has the engineering that you've done there informed the process by which you're starting to re-engineer in your digital footprint on the operations side? >> I know that there are conversations that kind of happened between engineering on the product side and the analytic side, but I think we'd love to see more of that discussion happening. Often what happens in any company, I think, is that you get the silos as we know, but the more that we can facilitate these discussions, I think the better it will be for us. >> Peter: So as you look at the Informatica Tool Care, the presence of, where are you starting, where do you anticipate you're going to use more of some of these tools, whether it's Power Center or MDM, et cetera, as you try to do this, as you try to replicate the experience you just had with EDI and the cloud transaction manager? >> That's a really good question. We've used application integration, so real-time application integration, which is a tool called ICRT. We've used Informatica Cloud Services, which is kind of batch-transferring of information to and fro. We've just, with EDI, implemented B-to-B gateway, which is for that connectivity with partners. And I think one of the key things for us moving forward is going to be data governance. As we have these different sources and different companies coming in, we've got to make sure that we govern and steward and ship it, and can I say sheriff, the data into its rightful homes accurately. We're trying to do that at the moment and we're doing it through spreadsheets and SharePoint and Lucidcharts and diagrams and Visio. One of the tools which I saw, which is an Informatica acquisition, Informatica Axon is a data governance tool. It doesn't store any data, but it just helps you manage and control your data. I think that's going to be crucial for any company which is working at amalgamating systems and data from various sources. >> John: What's the biggest challenge with data integration? One of the things, this is, companies have different views of the problem and opportunity. What's the biggest challenges that people have? >> You know, this is going to sound silly, but one of the biggest challenges that we have right now is just defining our data, defining what this term means. Even just this week, we've got one term, Sale Type, and still we're trying to figure out exactly what that means. That's one field that we want to be able to present to the business and we're still saying, "Hang on a second, what about this scenario?" I think that's the biggest deal is just to have a uniform definition of your different metrics and KPIs and attributes across the business. >> If you do that, you're going to first, you got to find the sources, you got to understand the degree to which synonyms are or are not synonyms, and then you got to go through the social engineering of getting people to agree so it is clear, for example. Do you see that as a facilitator for this process? >> I think it will be, I definitely think that will be, especially with the self-discovery or the intelligence structure discovery. I think that's going to be an exciting thing to see. >> I really like that intelligence structure discovery. That is just, that's not available in today's market. >> Yeah, that's right, but I think we've stepped away from that, I really do think so. >> You guys are. >> Yeah. And as an industry I think we are, with Informatica, partnering with Informatica. >> With Informatica, how are you guys working through (mumbles), you guys as a customer? What specifically are you guys doing with them? Sounds like that EDI thing is an enabler. What else are you working with them on? Share some specific-- >> Yeah, that's right. It's still, at this stage, it's kind of the, it's all cloud. We don't have any on-prem Informatica, so it's all the cloud stuff, and we use it extensively for our cloud systems, our cloud business applications: Markelo, Salesforce, Zuora, NetSuite. Those are the four big ones that we're using and those are the same (mumbles), I guess. So we're using Informatica to bridge the gap between these different systems a lot and so that's our kind of bread and butter with Informatica at the moment. >> John: How about developers onsite for data and dealing with data? How do you guys organize staff and skillsets? Is it mostly engineering? Is there data analysts, data science, how do you guys? >> Yeah, good question. We've got engineering, which kind of sits on the product. Then we've got IT business applications, which is where I fit in, and that's a combination of kind of business analysts as well as developers who build out this, a lot of the systems, and then we have an analytics team. The VP of analytics with Advanced Analytics, analytics platform, Data Lake, Data Vault, and so with those are the three big groups that we look at where Informatica splits across the different groups. >> Now you guys are pretty solid with Informatica, happy with them? >> Yes, very much so. >> Yeah, we've got a great partnership with them. Every time we've bought, it's not because it's been a hard sell. (mumble), We've said, "Okay, we need that," "and this is what we need." >> John: So not a hard sell. How long you been a customer, just curious? >> Almost three years. >> John: So you're not legacy Informatica. You're not locked in? >> No, I'm not, I've never even seen the on-prems. I've never even seen Power Santa, I hope to never see it. I'm not interested. >> You're cloud-native? >> Cloud, cloud first. That's right. >> How 'about you guys, multiple clouds? What kind of clouds (mumbles) do you guys have? >> With Informatica? >> No, for you guys. >> For us-- >> Salesforce, Markelo. >> Those are the things, all those business applications. Salesforce, Markelo, a little bit of hybrid stuff. We've got our own on-premz-- Do you have your own data center? >> We do have, as Carbonite? >> Yeah. >> Absolutely (talking over each other) Our customers data. >> Would you put that in the cloud, customer data? >> Yeah, that is, in fact, moving to the cloud. >> John: Alright, you are. >> Yeah. >> But under your control. It's your, effectively it's your cloud. So as you think about working with Markelo, Salesforce, Zoira, remmember the last one you mentioned, Oh, NetSuite >> Netsuite. >> As you look at those four, everybody, everybody is, all these SaaS companies are making, have a realization that if I can get the data, then I get the customer. Are they starting to make it more or less easy for you to perform these integrations across how they handle things? Where do you think their willingness to expose their APIs, get more information about the metadat, et cetera, is going so you can do a more effective job of bringing it together and creating derivative value out of these very rich, cloud-based applications? >> I think that's an excellent question. And for me as somebody who is not a developer, but as for me as somebody who's very very interested in moving and lending and transferring and transforming data, I have to rely on a tool like in Informatica because I don't want to go digging in the bowels of NetSuite to try and pull data out. I don't even want to have to write an API core. I honestly don't want to do that and I don't really want my team to be doing that. I want to be able to point Informatica at a system and say what have we got, so for me that's crucial. So I think that's where the partnership between a Salesforce and Informatica, I'm relying on that and I think that those sources, like the NetSuite and the Salesforce, I think they're going to continue to hopefully have this really good open partnership with these middleware or these integration tools. We have to have that. If we don't have that, we're stuck. The same people are going to start breaking into Salesforce and breaking into NetSuite to get the data 'cause we're going to get it one way or the other. >> Justin, great success story. I'd love to hear the cloud, need it being, you know, taking advantage of Informatica, really highlights that they've got the modern approach. Appreciate you coming out. Justin Donlon, Carbonite Applications Manager. This is The Cube with coverage of Informatica World 2017. More live coverage here after the short break. Stay with us. (innovative tones)