 From around the globe, it's theCUBE with digital coverage of UiPath Live, the release show. Brought to you by UiPath. Hi everybody, welcome back to this special presentation. theCUBE has been covering the RPA space for quite some time. UiPath just had recently a huge launch and Daniel Dinez, the CEO and founder of UiPath has set forth a vision of a robot for every person. Pretty substantial goals that he has. And Brandon Nott is here, he's the Senior Vice President of Product at UiPath. Brandon, good to see you, thanks for coming on. Thanks for having me. So that is a really ambitious goal and we're going to poke at that a little bit and ask you to sort of defend it, give us some proof points and help us understand sort of why you guys are so confident in this vision. You guys are obviously the leader in RPA, growing like crazy, you've shared some metrics, very transparent, so we'd love to have these transparent and open honest conversations. So I'm going to start with sort of the basic. I mean, people understand RPA just as, in terms of automating a lot of mundane tasks, these tasks are often very repetitive or rules-based. They're sort of interacting with existing applications. Now in the early days of RPA, these are stable legacy apps with people sitting in front of a screen. So just my first question to you is, some of the criticisms of RPA have been that if the app changes, the robot breaks, so first of all, is that the correct way to be thinking about the state of RPA today? Is that an outdated view? And then let's get into it so we can understand how we achieve robot for every person. Your thoughts. Sure. So I think it's a fair point in that RPA by definition is built on top of applications and it's always been the case that you need to be in coordination with your release teams, with the application teams to understand what's happening there. Do I think it's a fair statement on where the industry is? I don't think so. I think that is a small component of what the Center of Excellence looks at. And when you look at RPA at scale today, there are many considerations, governance, change management, training, things that make these companies successful and these companies that are embracing it as part of their strategic plan for digital transformation. So for sure, it's a part of the story, but I would say it's just a small part. The bigger part of the story is really about how you bring RPA into the culture. And that's what I think we'll talk about some more with the robot for every person. Yeah, definitely. And I want to get back into that, sort of how you make RPA strategic, but before we get there. So a lot of people have said, okay, well, you're interacting with existing legacy applications is it stable? There's no problem. You kind of sort of refuted that. But a lot of people also talk about a point to sort of the API economy, that APIs are really a way that your platform or other your competitors platform can interact with applications. And that begins to sort of widen the opportunity, sort of modernize the, both infrastructure and applications. Where does the API economy, the whole vision? Sure. When you look at RPA, we shouldn't look at it as just a narrow set of implementations. RPA is capable of connecting directly to APIs, directly to interfaces, to mouse and click style integrations, as well as deeper levels, connecting directly to the lower levels of the application, bypassing the mouse and keyboard entirely. So think about RPA, not just as keyboard and mouse automations, but also benefiting from all of those APIs that exist. Also being able to span the full spectrum of automation. So I want to talk, sometimes I joke, tongue in cheek, it's sort of a pejorative, I say, hey, RPA sometimes paves the cow path. But you know what, if my cow path works and I could pave it and allows me to go faster and automate, so what? There's other opportunities I can attack. So my question is, where are you seeing people really applying RPA today and how rapidly are they going forward? You know, really transforming, you mentioned digital transformation and you guys announced a ton of product to get into. Where do you see them in terms of glomming out to some of those more strategic areas? Yeah, absolutely. So we've had lots of conversation around what the right methodology is for RPA. Kind of like you said, should I just automate the process as it is or should I break down the process, assess it, re-engineer it and then automate? And the answer is we have customers all over the spectrum and there's a lot to be said for automating a process as is if a robot can do it in a minute and a half as is, but if I re-engineer it, it can do it in a minute flat. Where's your time best spent? And I think the biggest consideration that companies need to have right now with regard to automation is just really around opportunity costs. If I can automate a process as is and put my re-engineering team onto a bigger problem that's going to get a bigger lift for the organization, deploy those people there, right? So what you end up having is this kind of mosaic of opportunities. How much does it cost to automate? How much does it cost to re-engineer? What's my benefit going to be from that automation or from that re-engineering? And now you have different tools that you can apply to your backlog. So for sure, RPA can automate things as it is, as is, as well as do take that re-engineering approach and make sure that you are getting the most out of that automation. In terms of the strategic nature of it, again, all over the map, we've always said automate the mundane, automate the repeatable. I was a customer before I was an employee. Some of my automations were actually my most critical things, the things that I couldn't let fall through the cracks under any circumstances. So while they were maybe relatively easy for a human to do, the compliance pickup that I had, the guaranteed delivery pickup that I had, to me made it worth it. How does artificial intelligence address some of this in terms of making RPA more strategic? In one hand, it's going to inject some simplicity into the process. On the other hand, people are concerned about AI. Where does it fit? In what form does it take? Is it natural language processing? Is it actually taking actions like systems of agency? How should we think about that? Sure. I think about it as, again, a spectrum. So many of these questions, there's not a single answer there. It's really about what you want to accomplish and how you're going to approach it. So for instance, let's say I'm a company and I want to build the next best action AI model or ML model, right? I'm going to start with the data that I have for my operation. So I may want to use RPA to help extract data out of processes to build the repository that I'm going to build my model off of. Or let's say we have customers that are implementing complex models to help with their customers and they have those models being surfaced through RPA. So now I have the model, but I want a human to review it before it takes action. I can surface that in an attended automation in a form or something that's pre-built that gives the agent guidance on what to do. And then at the fully autonomous side, you have AI and ML models attached to chatbots that are hooked into RPA processes that can serve as customers in real time. You know, I want to ask you about sort of product versus platforms. In their book, the second machine age, Andy McAfee and Eric Brynjolfsson, MIT professors years ago, sort of laid out, they said products or platforms beat products. And I think a lot of the criticisms of RPA are around point products. You guys made a big deal in your last release. You didn't really talk specifically about this, but to me, one of my takeaways is you're building out a platform. You talk about a spectrum. You know, you've got Studio X, which is low code. You've got the studio, which is for RPA developers. You've got Studio Pro for hardcore, you know, you want to do quality assurance. So you really got a spectrum of capabilities. So it strikes me that one of the ways in which you get to a robot for every person is that you've got a platform that can evolve, you know, with the market. And I wonder if you could sort of talk about that and really try to plug it into that vision that Daniel set out a couple years ago. Absolutely. You know, to be honest, this has always been a blessing and a first for us, right? When you install UiPath, you have all of these tools, all of these capabilities, and you've got some places that you can start immediately. We place a number of pre-existing code bases and modules up on our marketplace, for instance. We have sample code that you can use that we provide. But still you need to take the platform and customize it for your applications, for your business. And when we talk about the platform mindset, really what our primary goal is, is to build something robust enough, flexible enough, reliable enough that any company can use it within their operations. And you see that, that's borne out on our customer list that we publish and we talk about. You have every industry covered, every region covered. And that's our challenge, is really to make something robust enough to be everywhere, but intuitive and understandable enough that anyone can pick an entry point and begin to use the platform. So when we talk about a robot for every person, I want a little better definition around a person. We're talking about every worker or is it even more sort of ambitious than that? Sure, more ambitious because it's not just a worker, an employee. It includes students, teachers. Take the broadest definition and think about how taking advantage of automation or being able to write your own automations is beneficial. There's no limit. My son is in first grade. He's taking a class right now as part of his curriculum on the basics of coding. He's doing loops and retries and step-based algorithmic teaching. This is something that's ubiquitous. This applies to everybody. That's awesome. Scary at the same time. So talk about this idea of bringing your own AI to the equation. You guys reference that a little bit of your kind of fabric approach, but can you clarify sort of how you see that playing out? This goes straight back to the platform concept, right? If it's the case that you already have an existing model and I talk to customers almost daily who have some form of intelligence existing within their platform today, right? It could be a model that helps with payment processing. Could be that next best action model, right? Data science has been on its own rocket ship for the past couple of decades. And by now, most enterprise companies already have models that they're using for somewhere, for something. We don't want to come in and say, rebuild that model with us. We're not a takeout company. We're an integration company. So we want you to be able to use those existing models, connect them directly to Orchestrator. And once it's connected to Orchestrator, that means that your developers can access those models directly within the automations that they're riding. So the ability to attach what you've already had those assets that you've already been working on and make it one click, one drag and drop accessible to your developers is huge. It is huge. I mean, I think that's, you can observe markets, the ones that have less friction in terms of, you know, their deployments tend to have greater adoption. You're not asking people to rip and replace. This is really sort of additive and you can get some quick wins. I want to come back to, you mentioned security, you mentioned that you got to be in sync with your teams. What's the right regime? I'm particularly interested in the security and compliance piece because a lot of times users when they hear IT, security, compliance, governance, they go, slow me down, say no. How do you help square that circle? Yeah, it's a great question. And it's funny because the narrative has changed so much. A year and a half ago, we were educating people on, you know, the fact that robots won't go rogue. They won't all of a sudden just start doing things that you haven't pulled them to do or haven't programmed in, right? It was very much a fear of the unknown. I don't have those conversations anymore. Now the conversations with customers are really around, I will enable people to build drone automations. I want to democratize RPA, but I don't want people to automate things that I don't want them to. For instance, I have a legacy database. It has a limited amount of bandwidth of capacity. So if all of my developers hit that database at once, I could slow down the access to that database. So maybe I want to blacklist that from my development environments because that's off limits for automation. And from our standpoint, we're completely okay with this. We want customers to use RPA for the right tools for their organization and give them the ability to build governance into the development tools and into the overall framework so that it's very much in line with their expectations. Brandon, I really appreciate you helping me wrap up this sort of RPA market analysis, the post UI path, let's, and so people, folks, you can DM me at D-Velante or hit me on Twitter and love to hear your comments. UI path, as I've said, very open and transparent organization, go hit them up, challenge them as I have. Brandon, again, thanks so much for coming on theCUBE and helping us with this program. Great, thanks for having me. It's always great to be here. All right, you're welcome and thank you everybody for watching. Dave Vellante for theCUBE. We'll see you next time.