>> Narrator: From around the globe it's theCUBE! With digital coverage of UiPath Live, the release show. Brought to you by UiPath. >> Hi everybody this is Dave Valenti, welcome back to our RPA Drill Down. Ted Kummert is here he is Executive Vice President for Products and Engineering at UiPath. Ted, thanks for coming on, great to see you. >> Dave, it's great to be here, thanks so much. >> Dave your background is pretty interesting, you started as a Silicon Valley Engineer, they pulled you out, you did a huge stint at Microsoft. You got experience in SAS, you've got VC chops with Madrona. And at Microsoft you saw it all, the NT, the CE Space, Workflow, even MSN you did stuff with MSN, and then the all important data. So I'm interested in what attracted you to UiPath? >> Yeah Dave, I feel super fortunate to have worked in the industry in this span of time, it's been an amazing journey, and I had a great run at Microsoft it was fantastic. You mentioned one experience in the middle there, when I first went to the server business, the enterprise business, I owned our Integration and Workflow products, and I would say that's the first I encountered this idea. Often in the software industry there are ideas that have been around for a long time, and what we're doing is refining how we're delivering them. And we had ideas we talked about in terms of Business Process Management, Business Activity Monitoring, Workflow. The ways to efficiently able somebody to express the business process in a piece of software. Bring systems together, make everybody productive, bring humans into it. These were the ideas we talked about. Now in reality there were some real gaps. Because what happened in the technology was pretty different from what the actual business process was. And so lets fast forward then, I met Madrona Venture Group, Seattle based Venture Capital Firm. We actually made a decision to participate in one of UiPath's fundraising rounds. And that's the first I really came encountered with the company and had to have more than an intellectual understanding of RPA. 'Cause when I first saw it, I said "oh, I think that's desktop automation" I didn't look very close, maybe that's going to run out of runway, whatever. And then I got more acquainted with it and figured out "Oh, there's a much bigger idea here". And the power is that by really considering the process and the implementation from the humans work in, then you have an opportunity really to automate the real work. Not that what we were doing before wasn't significant, this is just that much more powerful. And that's when I got really excited. And then the companies statistics and growth and everything else just speaks for itself, in terms of an opportunity to work, I believe, in one of the most significant platforms going in the enterprise today, and work at one of the fastest growing companies around. It was like almost an automatic decision to decide to come to the company. >> Well you know, you bring up a good point you think about software historically through our industry, a lot of it was 'okay here's this software, now figure out how to map your processes to make it all work' and today the processes, especially you think about this pandemic, the processes are unknown. And so the software really has to be adaptable. So I'm wondering, and essentially we're talking about a fundamental shift in the way we work. And is there really a fundamental shift going on in how we write software and how would you describe that? >> Well there certainly are, and in a way that's the job of what we do when we build platforms for the enterprises, is try and give our customers a new way to get work done, that's more efficient and helps them build more powerful applications. And that's exactly what RPA does, the efficiency, it's not that this is the only way in software to express a lot of this, it just happens to be the quickest. You know in most ways. Especially as you start thinking about initiatives like our StudioX product to what we talk about as enabling citizen developers. It's an expression that allows customers to just do what they could have done otherwise much more quickly and efficient. And the value on that is always high, certainly in an unknown era like this, it's even more valuable, there are specific processes we've been helping automate in the healthcare, in financial services, with things like SBA Loan Processing, that we weren't thinking about six months ago, or they weren't thinking about six months ago. We're all thinking about how we're reinventing the way we work as individuals and corporations because of what's going on with the coronavirus crisis, having a platform like this that gives you agility and mapping the real work to what your computer state and applications all know how to do, is even more valuable in a climate like that. >> What attracted us originally to UiPath, we knew Bobby Patrick CMO, he said "Dave, go download a copy, go build some automations and go try it with some other companies". So that really struck us as wow, this is actually quite simple. Yet at the same time, and so you've of course been automating all these simple tasks, but now you've got real aspiration, you're glomming on to this term of Hyperautomation, you've made some acquisitions, you've got a vision, that really has taken you beyond 'paving the cow path' I sometimes say, of all these existing processes. It's really trying to discover new processes and opportunities for automation, which you would think after 50 or whatever years we've been in this industry, we'd have attacked a lot of it, but wow, seems like we have a long way to go. Again, especially what we're learning through this pandemic. Your thoughts on that? >> Yeah, I'd say Hyperautomation. It's actually a Gartner term, it's not our term. But there is a bigger idea here, built around the core automation platform. So let's talk for a second just what's not about the core platform and then what Hyperautomation really means around that. And I think of that as the bookends of how do I discover and plan, how do I improve my ability to do more automations, and find the real opportunities that I have. And how do I measure and optimize? And that's a lot of what we delivered in 20.4 as a new capability. So let's talk about discover and plan. One aspect of that is the wisdom of the crowd. We have a product we call Automation Hub that is all about that. Enabling people who have ideas, they're the ones doing the work, they have the observation into what efficiencies can be. Enabling them to either with our Ask Capture Utility capture that and document that, or just directly document that. And then, people across the company can then collaborate eventually moving on building the best ideas out of that. So there's capturing the crowd, and then there's a more scientific way of capturing actually what the opportunities are. So we've got two products we introduced. One is process mining, and process mining is about going outside in from the, let's call it the larger processes, more end to end processes in the enterprise. Things like order-to-cash and procure-to-pay, helping you understand by watching the events, and doing the analytics around that, where your bottle necks, where are you opportunities. And then task mining said "let's watch an individual, or group of individuals, what their tasks are, let's watch the log of events there, let's apply some machine learning processing to that, and say here's the repetitive things we've found." And really helping you then scientifically discover what your opportunities are. And these ideas have been along for a long time, process mining is not new. But the connection to an automation platform, we think is a new and powerful idea, and something we plan to invest a lot in going forward. So that's the first bookend. And then the second bookend is really about attaching rich analytics, so how do I measure it, so there's operationally how are my robots doing? And then there's everything down to return on investment. How do I understand how they are performing, verses what I would have spent if I was continuing to do them the old way. >> Yeah that's big 'cause (laughing) the hero reports for the executives to say "hey, this is actually working" but at the same time you've got to take a systems view. You don't want to just optimize one part of the system at the detriment to others. So you talk about process mining, which is kind of discovering the backend systems, ERP and the like, where the task mining it sounds like it's more the collaboration and front end. So that whole system thinking, really applies, doesn't it? >> Yeah. Very much so. Another part of what we talked about then, in the system is, how do we capture the ideas and how do we enable more people to build these automations? And that really gets down to, we talk about it in our company level vision, is a robot for every person. Every person should have a digital assistant. It can help you with things you do less frequently, it can help you with things you do all the time to do your job. And how do we help you create those? We've released a new tool we call StudioX. So for our RPA Developers we have Studio, and StudioX is really trying to enable a citizen developer. It's not unlike the art that we saw in Business Intelligence there was the era where analytics and reporting were the domain of experts, and they produced formalized reports that people could consume. But the people that had the questions would have to work with them and couldn't do the work themselves. And then along comes ClickView and Tableau and Power BI enabling the self services model, and all of a sudden people could do that work themselves, and that enabled powerful things. We think the same arch happens here, and StudioX is really our way of enabling that, citizen developer with the ideas to get some automation work done on their own. >> Got a lot in this announcement, things like document understanding, bring your own AI with AI fabric, how are you able to launch so many products, and have them fit together, you've made some acquisitions. Can you talk about the architecture that enables you to do that? >> Yeah, it's clearly in terms of ambition, and I've been there for 10 weeks, but in terms of ambition you don't have to have been there when they started the release after Forward III in October to know that this is the most ambitious thing that this company has ever done from a release perspective. Just in terms of the surface area we're delivering across now as an organization, is substantive. We talk about 1,000 feature improvements, 100's of discreet features, new products, as well as now our automation cloud has become generally available as well. So we've had muscle building over this past time to become world class at offering SAS, in addition to on-premises. And then we've got this big surface area, and architecture is a key component of how you can do this. How do you deliver efficiently the same software on-premises and in the cloud? Well you do that by having the right architecture and making the right bets. And certainly you look forward, how are companies doing this today? It's really all about Cloud-Native Platform. But it's about an architecture such that we can do that efficiently. So there is a lot about just your technical strategy. And then it's just about a ton of discipline and customer focus. It keeps you focused on the right things. StudioX was a great example of we were led by customers through a lot of what we actually delivered, a couple of the major features in it, certainly the out of box templates, the studio governance features, came out of customer suggestions. I think we had about 100 that we have sitting in the backlog, a lot of which we've already done, and really being disciplined and really focused on what customers are telling. So make sure you have the right technical strategy and architecture, really follow your customers, and really stay disciplined and focused on what matters most as you execute on the release. >> What can we learn from previous examples, I think about for instance SQL Server, you obviously have some knowledge in it, it started out pretty simple workloads and then at the time we all said "wow, it's a lot more powerful to come from below that it is, if a Db2, or an Oracle sort of goes down market", Microsoft proved that, obviously built in the robustness necessary, is there a similar metaphor here with regard to things like governance and security, just in terms of where UiPath started and where you see it going? >> Well I think the similarities have more to do with we have an idea of a bigger platform that we're now delivering against. In the database market, that was, we started, SQL Server started out as more of just a transactional database product, and ultimately grew to all of the workloads in the data platform, including transaction for transactional apps, data warehousing and as well as business intelligence. I see the same analogy here of thinking more broadly of the needs, and what the ability of an integrated platform, what it can do to enable great things for customers, I think that's a very consistent thing. And I think another consistent thing is know who you are. SQL Server knew exactly who it had to be when it entered the database market. That it was going to set a new benchmark on simplicity, TCO, and that was going to be the way it differentiated. In this case, we're out ahead of the market, we have a vision that's broader than a lot of the market is today. I think we see a lot of people coming in to this space, but we see them building to where we were, and we're out ahead. So we are operating from a leadership position, and I'm not going to tell you one's easier that the other, and both you have to execute with great urgency. But we're really executing out ahead, so we've got to keep thinking about, and there's no one's tail lights to follow, we have to be the ones really blazing the trail on what all of this means. >> I want to ask you about this incorporation of existing systems. Some markets they take off, it's kind of a one shot deal, and the market just embeds. I think you guys have bigger aspirations than that, I look at it like a service now, misunderstood early on, built the platform and now really is fundamental part of a lot of enterprises. I also look at things like EDW, which again, you have some experience in. In my view it failed to live up to a lot of it's promises even though it delivered a lot of value. You look at some of the big data initiatives, you know EDW still plugs in, it's the system of record, okay that's fine. How do you see RPA evolving? Are we going to incorporate, do we have to embrace existing business process systems? Or is this largely a do-over in your opinion? >> Well I think it's certainly about a new way of building automation, and it's starting to incorporate and include the other ways, for instance in the current release we added support for long running workflow, it was about human workflow based scenarios, now the human is collaborating with the robot, and we built those capabilities. So I do see us combining some of the old and new way. I think one of the most significant things here, is also that impact that AI and ML based technologies and skills can have on the power of the automations that we deliver. We've certainly got a surface area that, I think about our AI and ML strategy in two parts, that we are building first class first party skills, that we're including in the platform, and then we're building a platform for third parties and customers to bring their what their data science teams have delivered, so those can also be a part of our ecosystem, and part of automations. And so things like document understanding, how do I easily extract data from more structured, semi-structured and completely unstructured documents, accurately? And include those in my automations. Computer vision which gives us an ability to automate at a UI level across other types of systems than say a Windows and a browser base application. And task mining is built on a very robust, multi layer ML system, and the innovation opportunity that I think just consider there, you know continue there. You think it's a macro level if there's aspects of machine learning that are about captured human knowledge, well what exactly is an automation that captured where you're capturing a lot of human knowledge. The impact of ML and AI are going to be significant going out into the future. >> Yeah, I want to ask you about them, and I think a lot of people are just afraid of AI, as a separate thing and they have to figure out how to operationalize it. And I think companies like UiPath are really in a position to embed UI into applications AI into applications everywhere, so that maybe those folks that haven't climbed on the digital bandwagon, who are now with this pandemic are realizing "wow, we better accelerate this" they can actually tap machine intelligence through your products and others as well. Your thoughts on that sort of narrative? >> Yeah, I agree with that point of view, it's AI and ML is still maturing discipline across the industry. And you have to build new muscle, and you build new muscle and data science, and it forces you to think about data and how you manage your data in a different way. And that's a journey we've been on as a company to not only build our first party skills, but also to build the platform. It's what's given us the knowledge that to help us figure out, well what do we need to include here so our customers can bring their skills, actually to our platform, and I do think this is a place where we're going to see the real impact of AI and ML in a broader way. Based on the kind of apps it is and the kind of skills we can bring to bear. >> Okay last question, you're ten weeks in, when you're 50, 100, 200 weeks in, what should we be watching, what do you want to have accomplished? >> Well we're listening, we're obviously listening closely to our customers, right now we're still having a great week, 'cause there's nothing like shipping new software. So right now we're actually thinking deeply about where we're headed next. We see there's lots of opportunities and robot for every person, and that initiative, and so we're launched a bunch of important new capabilities there, and we're going to keep working with the market to understand how we can, how we can add additional capability there. We've just got the GA of our automation cloud, I think you should expect more and more services in our automation cloud going forward. I think this area we talked about, in terms of AI and ML and those technologies, I think you should expect more investment and innovation there from us and the community, helping our customers, and I think you will also see us then, as we talked about this convergence of the ways we bring together systems through integrate and build business process, I think we'll see a convergence into the platform of more of those methods. I look ahead to the next releases, and want to see us making some very significant releases that are advancing all of those things, and continuing our leadership in what we talk about now as the Hyperautomation platform. >> Well Ted, lot of innovation opportunities and of course everybody's hopping on the automation bandwagon. Everybody's going to want a piece of your RPA hide, and you're in the lead, we're really excited for you, we're excited to have you on theCUBE, so thanks very much for all your time and your insight. Really appreciate it. >> Yeah, thanks Dave, great to spend this time with you. >> All right thank you for watching everybody, this is Dave Velanti for theCUBE, and our RPA Drill Down Series, keep it right there we'll be right back, right after this short break. (calming instrumental music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering UiPath Forward Americas 2019, brought to you by UiPath. >> Hi everybody welcome back to Las Vegas, we're at the Bellagio at UiPath Forward III, day two of theCUBE covers. theCUBE is a leader in live tech coverage. We go out to the events. We extract the signal from the noise. Erik Alexis here is the Vice President of Global Intelligent Process Automation at GE. Eric thanks for coming on. >> Yeah absolutely excited to be here. >> So, you guys have a COE, you're obviously heavily involved in essentially running the COE, is that right? >> Yeah that's my role at GE. I lead our Global Center of Excellence for intelligent process automation. Our journey started with UiPath a while back in 2016. So, it's been an incredible journey so far. >> And I want to get into that. So, before I do, I was struck by the Forrester analyst, Craig LeClair this morning made a statement. I don't know if you're in there, but he said, "Yeah COE, setting up a COE, "maybe that's asking too much." But I talk to a lot of people that have a center of excellence. Maybe it's definitional but what does your COE look like in terms of just it's role, size? >> Yeah it's a great question, so I think in terms of the role that we play more broadly, I mean we provide a lot of the technical expertise, the hands-on development and the operational support for our business units. And so we've really kind of developed that expertise over time, and we use our business units to really drive and identify the opportunities that come in through the COE. So, in terms of the size of the COE, we've got in total number of heads, we've got about 50 primarily technical resources there, that are supporting development as well as ongoing operation. >> Awesome, okay so let's talk about your journey. When did it start? What was the motivation behind it? How did you make the business case, and we'll get into it. >> Yeah so our journey started back in 2016, GE, we used to have a shared services organization that we had a very forward-thinking CEO at the time who wanted to really disrupt the way that we worked. And so RPA was something that was just coming out and kind of getting noticed by a lot of these shared services organizations. And so throughout the year we assessed a couple of technologies obviously landing on UiPath for a number of reasons. I would say in terms of our journey 2017 was kind of our year to prove the technology. We wanted to see if this stuff could really work long term and operate at scale. Given that I'm still here obviously, we proved that was correct and then 2018 was kind of the year of scaling and operationalizing kind of a sustainable model to support our business units across the board from an RPA standpoint. So, really building out a proper structure, building out the governance that goes along with building robots and building a kind of a resource team to continue to support the bots that we were at scale at that point, so maintaining those bots is critically important. And then 2019 has really been the year and I think the theme of this conference in general, a bot for every person I think that's the direction we're moving in 2019. We've kind of perfected the concept of the back office robot and the development of those, and running those at scale. And now we're moving towards a whole new market share when it comes to attended automation and citizen development. >> So, in '16 it was kind of kicking the tires it was almost like R&D. And then '17 was really essentially a proof-of-concept right so still a small team, a two piece kind of team kind of thing right? And then when you talked about scale, helped us understand what's involved in scale, I know it's also another big theme of this conference. What are the challenges of scaling and how did you resolve those? >> Yeah that's a very good question. I think it's a question that has been very common throughout this entire conference. I would say when I think about scaling what I've noticed over the past few years is that, the actual bot development is about 25% of the work that you need to do, right? When it comes to scale there is everything outside of the actual development is the important part. So, how are you funneling opportunities into a pipeline, how are you streamlining the entire process reengineering of fitting an RPA into an existing process, what's governance you have in place to make sure that the code of that development is clean and can be maintained long term? And then more importantly I think that people overlook, people think of scale as being able to develop a lot of bots. I think more importantly what scale is is being able to efficiently maintain a large portfolio of bots, and that's what I've realized this year. We've got now about 300 automations in production and your reputation as an organization is really on how well you maintain those bots, because if your bots are consistently failing, and you're not fixing them quick enough for your functional users to leverage them, then you lose a lot of credibility. So, I think that's been a big learning for us as we reach scale. >> That's interesting I mean I think about scripts, how fragile scripts are and you got a lot of 'em, and they almost always break. And so what is the discipline that allows you to have that quality of bot that is maintainable? Is it a coding discipline? Is it a governance? Is there other automation involved in maintaining those bots? >> No there is and I think the team that's under me, my technical team has done a phenomenal job of setting this up, but we've got some very rigorous standards that we've put in place around. We do have reusable components for example that need to be used on every single robot that goes into production, so that when I look at for example a bots login, that bots login is going to be the same across all my bots. So, every developer who's going to be maintaining that bot knows what it is and how to fix it. I think the standardized logging as well to make sure that we've got robust logging for every single robot is incredibly important because again that's going to be critical when somebody goes to try and fix the bot. >> So you are like an app store, you're enforcing rules like Apple for developers. >> Exactly. >> Okay so let me ask you a question. See now several years in if you had a mulligan, what would you do differently? >> Yeah I think that's another very good question. I think when you first start with this technology, it's unbelievably exciting, because it's something that you can immediately see the difference and the impact it can make, and so you want to try and apply it everywhere to everything, to solve every problem. And I think that's kind of where we got a little ahead of ourselves. We weren't as thoughtful as we should have been when we started taking in the use cases that we were bringing in and while I sit here and tell you that we've got 300 automations in production, I've also decommissioned about 90 automations as well. Because you kind of live and you learn as you go through that process on. This doesn't make sense for RPA. It's not driving the value anymore. It's not driving the right value for the company. >> And is that because the process needs to be reworked before it's automated or there are other factors? >> Yeah I think there's a couple of factors there. I think number one, some bots are intentionally just for short-term use. We look across the portfolio, some bots you design for to operate for two weeks for a massive for example document transition or something like that. So, that's a common reason for decommissioning. I would say secondly you just picked the wrong process. It's not big enough. You think this is perfect for RPA, but it's saving somebody maybe five or 10 minutes a week, which in reality do you really want to put all the effort and to continue to maintain something like that on a back office level? So, I think the size of the processes and the complexity you've got to be thoughtful about as well. >> Thinking about a bot for every worker, what does that actually look like? Is that like you get a laptop and you get a bot? How does that actually manifest itself? >> Yeah I think as I've talked to some of the teams and Daniel as well about this, it's really around I mean imagine opening it up just like any other application on your computer and Excel, you've got that sitting on your desktop and you use that for a number of different things. I think that's kind of how I envision it and everyone when they come into GE, they'll get their laptop and it's part of their kind of package of software that they get. One of them will be UiPath and I think again if GE where I see that as the future. We've got to be thoughtful about how that's rolled out because you want to make sure it's done the right way and you want to make sure that that succeeds and what comes along with that is a lot of education. There's a lot of people that need to be educated on the technology in order to roll that out effectively. >> It's part of the onboarding part, just part of the HR onboarding, and so you open up your laptop and based on your role you'll have a library of bots that are applicable for your job. Is that kind of what you envision? >> Again I think that's kind of the future state and so HR will have a common library that they can pull from and Finance will have a common library that they can pull from. And I think the announcement this weekend of or this week of our StudioX is going to make life significantly easier. So, if you need to kind of edit any of those components or make any custom steps, you can do that with StudioX, but I think having a pre-built set of bots by function would be extremely important. >> And StudioX is the citizen developer right? So, okay now how do you then enforce the edicts of the COE if Dave Vallente's writing automations. >> It's honestly a question that we haven't answered yet and I think that's the piece that we're trying to solve for now, to roll it out more broadly. And I think part of it's going to be training right? Educating the broader group, part of it is giving them access to front office robots and so you do have the code back at the orchestrator so that you can see kind of what's going on and make sure if there are massive changes that need to be made, you can make some of that centrally, so I think figuring out how to centrally maintain and store some of that code is going to be important. >> And the idea of moving beyond this what they call this morning the snowflake into the snowball. So, reusable components is something that I've heard a lot about. That's not trivial yeah right because mapping the right component for the right job is always going to be some kind of unique, not always, but there could be some unique element to put in words. So, what are your thoughts on kind of future? I mean we touched on some of them. It sounds like even though you started early, 2016, it sounds like you still got a long way to go. What's the roadmap look like for you guys? >> Well it's really never-ending because you know you see how quickly the industry is changing and how quickly these automation platforms. I think we're at the point now where these are no longer RPA platforms. They're automation platforms with all of the different features and you look at the broader ecosystem of the technologies being pulled into play. I think it's moving from robotics process automation into intelligent process automation. And that's really our goal and leveraging the ecosystem that the UiPath is built is I think what we want to do more of going forward. >> And the primary measurement of value to you, I'm inferring is time saved from doing non-differentiated tasks, is that really a key metric or are there others that you're looking at, bottom line dollars that you're saving or what? >> I think the way that we measure productivity is really in three major buckets. One is the hours saved so that employees can do other things and I would say that is far and away, the largest bucket that we have. But I think additionally you've got to think about direct cost out. I mean if my finance team comes to me and says, we're thinking about hiring a person to do this why not an RPA? Why can't we use an RPA to do that instead? So, it's not like anyone's losing their job over. It's just figuring out a better way to supplement your existing workforce. Then I would say the third way really is thinking about the compliance element of things. So, and that's often overlooked. You may not save anyone time. You may not save anyone hours or dollars, but what you can do is expand for example in your audit function, expand your testing or sampling of a certain criteria, instead of sampling maybe the top 20 risky units, you can now sample a 100% of a population, which fundamentally changes how you can get comfortable with your financial statements and other elements of the compliance. >> Talking earlier just I asked is sampling dead because of RPA right? >> It really feels like that you know. >> Dave: Eric it's super knowledgeable. I really appreciate you coming on. >> Absolutely. >> Dave: Congratulations on all your success really. >> Thank you very much Dave. I appreciate it. >> You're welcome. All right keep it right there everybody, we will be back with our next guest right after this short break. We're live from UiPath Forward III from Las Vegas. You're watching theCUBE. (upbeat music)

>> Narrator: Live from Las Vegas, it's theCUBE, covering UiPath Forward Americas 2019. Brought to you by UiPath. >> Welcome back everyone to theCUBE's live coverage of UiPath Forward. I'm your host Rebecca Knight, co-hosting alongside of Dave Vellante. We're joined by Param Kahlon, he is the Chief Product Officer at UiPath, thank you so much for coming on theCUBE. >> Thank you so much for having me here. >> So-- >> Big week! >> Yes. >> You've been busy! >> I have been busy. >> (Rebecca laughs) >> Thank you David. >> So this morning, you were up on the main stage, and you were sort of giving the audience a state of play of business today. And you were lamenting, saying, "Wasn't technology supposed to make our lives easier? "Wasn't it supposed to free us from the mundane, "and supposed to make us more efficient?" And yet, hasn't quite ended up that way. You had the quote, the famous quote, "We see computers everywhere "except in the productivity statistics," from Robert Solow, the Nobel winner. Can you refine that a little bit? And particularly within the context of the RPA market. >> Yeah, isn't it exciting? I mean, we really have so much technology that we live in today, yet we're busier, we're doing more mundane work than we've ever done before. We're more stressed than ever before. That just seems sort of paradoxical to me that, you know, all this stuff that was supposed to give us more time to do the things that we wanted to do, yet we keep doing the repetitive, robot type work that, you know, we thought technology will free us from. And I think that's fascinating that, you know, that's happening. And I think there's a few theories on why we think that's happening. I think it's happening because business has gotten a lot more complex. You know, companies are having to change business models on the fly. Digital transformation is effecting standard companies, regulated industries, in ways that they did not imagine, and companies don't know how to cope and manage all the technology well. And this where, I think, RPA is really, really useful, because it can help you change the processes, modernize the processes without having to go change, rip and replace those existing systems. You know, do the work that you were going to hire humans to do in moving data, moving processes from one system to another. Do that through robots. And that's what our robots can help free the humans, to be able to focus on the things that matter, the things that they care about, right? That's really what the beauty of the RPA is. >> So I wonder if you can help our audience, you know, understand UiPath a little bit better. You know, Daniel talks about, how is it that UiPath has ascended so quickly? And you appear to be achieving escape velocity. You kind of started out, you know, third, fourth, whatever it was, and now you're sort of number one in all these quadrants and waves. And so yesterday you talked about five pillars. And I want to unpack them a little bit. Open platform, rapid results, which I think is around ROI. Path to AI, scalability, and trust. So here's my question. Any one of your competitors could say the same thing. "Oh yes, we're open. "Oh, we get rapid ROI." So what makes UiPath different? >> I think actually not just saying those words, but making it happen, right? So anybody can say we've opened, we've done something, but do people actually have 400,000 community members that have actually using the platform on an active basis? Can you actually go to a website over the last two years and download the software and use it? How long does it take you to sign up for a cloud service that we have made available? What does it take for you to do that? I think all the things that we've invested in, in really enabling engagement with the community, right? Making it open, not just from a technology perspective, but from a people perspective as well, are the things that have differentiated ourselves. And those can be very generic terms, that you're right, other people can use as well, but I think we live those terms, right? We actually do everything in the product, from the business perspective, to make sure that openness is embraced. You know, when we look at building new capabilities, new products, we focus on, is it actually going to help our customers get quicker value, right? Is it going to help them reduce five clicks to be able to get that process done? And if so, then we should build this feature because it will make it easier, and engage more people in the audience, more people like the customer to be able to get work done. So we're super excited about bringing all those capabilities >> Okay, so the big part of that is the product. I mean if you have a great product, that always helps. It's not the sole condition, but it helps a lot. >> Param: Yeah. >> Many times we've seen leaders that don't have the best product, but I'm guessing you feel as though you have the best product. So architecturally, what is it about UiPath that's different, that differentiates you? >> Yeah, I think the core difference is, I'd say, fundamentally at a company level, is in our culture. This is a culture that's built around customers. This is a culture that's built around humility. This is a culture that's built around getting things done, and being fast about it, right? You saw a lot of product innovation that we did. If we told you a year ago, we're going to do all this, you would've laughed at our face, right? We're continue to do that pace, at the pace the market wants. And I think that is the fundamental difference in us, versus the rest of the companies out there. I'd also like to believe that we are, from a technology perspective, we have an edge, because we didn't start with the legacy of doing RPA many, many years ago. We have a much more modern stack. You alluded to the fact that we came in from behind, and we've taken to the number one place very quickly. I think part of that is the architecture decisions that we've made are more modern, are not vetted in a lot of legacy, that are helping us bring more rapid innovation to the market. That are helping us build more resilient technology, that's helping our customers achieve those outcomes, the goals that they want to be able to do, more easily on our platform. We have a number of our customers that actually did not start with us. They started with one of our competitors, and they said, "We started, we thought it was going to work, "it didn't. We came to UiPath and we saw that "it actually works." And that's a testament to the technology that we built, that's actually helping deliver the results that our customers expect it to. >> Rebecca: So, >> Dave: You know, >> Sorry Rebecca, go ahead. >> I was just going to say that, one of the other things you said this morning, was that bots allow you to focus on you, focus on the more creative aspects of your job, and you brought up some customers, PepsiCo and Nielsen, too. Can you describe sort of, how you're helping customers focus on themselves, these employees who are now, you're taking away the tedium, and that's great, and they're giddy about that. But how are they, then, channeling that energy into strategy, innovation, and the sort of more value added things? >> Param: Yeah, you know I'll give you a really quick example of a customer, that I worked with, it's a bank. And in this bank, it's a retail bank, and what used to happen before we deployed UiPath, was the banker had to go to like six different applications, and pull reports of the customer they were about to go meet, print them all out, review the data, and be able to suggest what the customer's unique needs might be, right? So for that half an hour appointment with the customer, it used to take that banker another half an hour to get ready for that appointment. After the deployed UiPath robots, UiPath's robots now go pull up the data for the customer, from those six different core banking systems, and be able to feed that to a machine learning system, to suggest what their unique needs might be. So they need five minutes to get ready for that appointment. They're more ready for that appointment, and they deliver a better outcome. People want to help other people, right? They don't want to go to systems, and print reports, and read them, and understand what it might be. They really want to be able to go meet with the customer, and help solve their problems, that help the customer, but also help the business goals for the bank. And that's what makes the people that are using our technology more happier, right? It makes them free enough to say that, instead of now spending half an hour printing stuff, I now have that extra 25 minutes, because I still need five minutes to get ready, I have the extra 25 minutes, to think about, what else can I do to further more creative aspects of my job? Or maybe I don't have to work as hard as I did in the past. >> I wonder if I could ask you about, I've been drawing parallels today with another company, ServiceNow, that I've been tracking for a long time. And they started out in this kind of narrow, change management, ITSM space >> Param: ITSM, yeah. >> And then expanded their TAM dramatically. And you shared with us, yesterday and today in the keynote, You've got RPA for devs and testers, you know StudioT, that targets 2% of the market. and then you've got the citizen developers, that's StudioX, that expands up to 10%. Business analysts, which is Explorer and Insights, that gets you to 25%. And then apps, where automation is the apps, that was a little fuzzy to me, so I want to dig into it a little bit, but that's 100% of the market. That's your, whatever it is, 20, 40, 50 billion dollar TAM. My question is this, I was going to the event last night, and I ran into some business analysts. So you're already working with those folks. So it seems like you're learning from folks that are sort of using a product, that was maybe developed for testers and devs, but they're using it today as business analysts, and you're improving that. Can you help us just understand your product strategy, just in terms of what you've announced, and how it dove tails into those segments that we just talked about? >> Absolutely, so you know, our product strategy isn't tied to like, what are we going to do to grow our TAM, and other stuff. Our marketing organizers can get super excited about that, Bobby is all over that, but really everything we've done in the product today, is about listening to customers. Understanding what their needs are, what do they want us to grow into, and what capabilities they want us to go build, right? So we've expanded the StudioX, not because we thought everybody should have StudioX, but we actually had customers that took our product, the Studio product, and said, "We want to roll this out "to every single user within the enterprise." Because they thought that every person has unique needs and they should be able to build a bot for themselves. Well they came back and told us, well we wanted to do that, but this isn't really quite ready for all of our accountants. This isn't quite ready for all of our business analysts. Can you actually make it simple? All of these people use Excel, can you make it look like Excel? So we took all of that feedback, and that's what we focused on, building StudioX. So we can make sure we meet the needs of the market. And every single pillar of the investment that we've done, has focused around making sure that we're able to meet those requirements around those. Automation is the application, now I'm going to go to that. And that also came from, you know, there's different kinds of, if you look at, take a product like Analytics, right? Or Reporting. Different people within the organization have different kinds of needs. There's people that are like, "Hey I want to create my own reports, "I want to slice and dice, I want to understand the strands, "and I'm going to use it this way." Then there's somebody who says, "Oh, I want to bring more data into that, "and I want to do data joins, "and I really am going, I'm a data junky, "I'm going to build a data model around it." And then there's users that are like, "I just want to use the report, I want somebody else to build them, I just want this report every Monday morning." Those are more executives, they're like, I just want to look at the data, let me tell you my report, and I'm just going to use it, I'm just an end user. And that's what we're trying to do, is from an automation perspective, there's people that have different types of needs. There's going to be people that are true developers, RPA developers that we've targeted with Studio, then there's people that are business analysts that are like, I can do some stuff with it, I'm not going to spend 8 hours a day every day working on it, I may spend two hours, once a week, building something that's relevant for me. And that's what StudioX is targeted to. But then there's a whole lot of other users, that are like, I don't want to build anything myself, but I want to use it, things that are relevant for me. These are people, maybe like contact center agents, that are taking orders from customers. So, let's say, in a typical Fortune 500 company, if you hired a person to take orders today, you'd have to go train the person in at least 10 different applications to be able to take orders, right? You'd have to show them how it works, when a customer calls, if it's a material order take it in this SOP system, if it's a this order that came through an acquired company, take it in that system. That takes a lot of time. What is the call center agent, the order taking person, doing? They're essentially capturing some very basic information from the customer, that are saying, I am this customer, I want this, this, and this product to be shipped at this address, and tell me when you can ship it, and what is the price for that? What we're trying to do with that application, is give that order agent a very simple interface, where they can punch in the three things simply, and get the results back that the customer cares about, without having to learn how to jump hoops across these 15 different applications to be able to enter that. Because robots can learn those applications, and take what you have put into that interface, and do the work of putting in, cascading that data, and extracting information from those systems. That is the concept behind, automation is the application. >> Sounds like a killer app. >> Yeah, it is. Yeah I like to say it that way as well. >> I want to ask you about cloud. Cause you guys announced the ability, and I did it, I went and downloaded, not downloaded but I signed up, it took seconds. I mean it was simple, and now I got to invite other people, and start, you know, digging in. But we saw this with CRM. Email, Service Management, HR, now even analytic databases, all got SaSified. >> Param: Right. >> I'm curious as to why, not really it took so long, why didn't you start with SaS? Is there something unique about RPA? Is it cause Daniel was a Microsoft guy, pre-Azure? And will this industry eventually go all SaS? Or will it be hybrid, or? >> Param: I think it's like any other workload in the enterprise, there's some customers that are going to want to remain on premise, because that's who they are, that's what they do. >> Governance, compliance, all those, security, right. >> Governance, compliance, you know, we're special. And then there's other customers that are like, you know, we're going where the rest of the world is going. We're going to let this data center work in a cloud, that we believe is secure, has the governance and compliance. So I think we're meeting customers where they are. We're going to continue to support on premise deployments. We will continue to support deployments for customers that want to deploy on private cloud infrastructure. And we'll keep deploying customers that want to use in SaS. Your question was why did it take so long for this to go to that? I think, my theory behind that, is that a lot of the automations that are happening, are touching systems that are only available on premise. Some of these are affecting systems that haven't moved to the cloud, So companies are saying, well I've got to put my robot on premise, because it's got to touch this application that's on premise. I might as well deploy the whole infrastructure on premise. And what we've done with the cloud service, is we've given you the options. You will definitely run their infrastructure in the cloud. That manages and governs the robots. And you can decide to run the robots on premise, or you can decide to run the robots in the cloud, as VMs and machines in any data center. >> So if I can put it in my words, the data lives on prem. >> Param: Yes. >> So you're bringing the automation to where the data lives, independent of the cloud, so that's really why. So the latency issues, we mentioned the other ones, compliance, governance, you know, security, etc. But there's going to be performance implications as well. If you've got a lot of data on-prem, you want to be on prem. >> Again, yeah, it just depends upon, if you've got a lot of data on-prem, and more importantly the business applications that you're using, let's say you're trying to automate a process in a mainframe application that hasn't moved through any cloud yet, that's sitting on a server in the on-premise environment. And the robot can only access it if it's deployed on a machine that sits within the same network, then you've got to put the robot in there, that can access it there as well. >> Dave: It makes sense, it's not a standalone application. It's automating other apps, and touching others, it's got dependencies all over the place. >> Exactly, it's sort of like the lowest common denominator. If every application your touching is the cloud, there's no reason you want to put the robot on premise. You would want to put the robot in the cloud as well. But the reality is that people have moved some applications to the cloud, but not every application to the cloud, that the business process is touching. >> Dave: Well a lot of ERP, a lot of financials, I would imagine the folks I talked to last night were insurance industry, so. >> Yeah, those industries have a lot of homegrown systems, built a long time ago. >> Rebecca: So there's been a lot of exciting product announcements at this conference, but I want you to talk about what's coming up ahead. What are some of the things that you're working on, that are most exciting to you, as these bots become smarter, more durable, and more able to take on complex tasks? What are we going to be talking about at next year's UiPath? >> Yeah, I think that's a really interesting question, and I think you'll hear talk next year about a few things. One is, we started a lot of initiative this year, and we're going to release the version one of many of our products this time. We're going to keep focusing on making sure we make them enterprise ready, we take the feedback across the customers, and make it ready for what they're able to do. I think another key initiative that we're focused on, is contact center. We see mass adoption of our technology in contact centers, and today what we do, is we give our customers the components that we will deploy in call centers, but we don't actually have a finished solution for call centers. Call centers have a lot of automation opportunities, we'll build a more finished solution for contact centers. The other stuff that you'll hear us do more next year, is the concept of applications. We have some ways to build applications today, but I think we're going to grow that ability to create applications, compose applications, very quickly, and you'll hear us do a lot more next year there. >> Rebecca: Well we'll look forward to hearing about it. >> Param: I really look forward to telling you next year about it. >> Dave: Thanks for coming on. >> Rebecca: Thank you so much, Param >> Thank you so much. >> I'm Rebecca Knight for Dave Vellante, that wraps up day one of UiPath Forward, come back tomorrow for more. >> [Electronic Music]