UiPath, Inc. ($PATH)

Thank you for joining us for the UiPath session at the Growth Stock Conference. I'm Patrick McIlwee, and I'm an analyst here in the software group at William Blair as a part of which I cover UiPath. I'm required to inform you that a complete list of disclosures and potential conflicts of interest are available at our website, williamblair.com. We're very happy to have the UiPath team back at our conference this year, including COO and CFO, Ashim Gupta; as well as Allise and I think, Jake as well from the IR team here in the audience. UiPath is one of the leading automation and orchestration software providers for the enterprise enabling businesses to automate repetitive digital workflows across applications, systems and business functions. The company just reported their first quarter results last Thursday, and their positioning to benefit from the adoption of AI and the enterprise is increasingly clear. So I think it's a great time to be digging into this story. So that's my quick 2 liner on the business, and I'll turn it over to Ashim for a better overview of the company.

Awesome. Thank you, everybody. So I'll put the safe harbor up for a second. It's actually really great to be a part of this team and to see everybody here today. I would say we came off of one of, like, to me, one of the most foundational quarters that we've had. And the reason why I look at it is there's 2 parts of a quarter. It's kind of what you deliver and the foundation about -- that you're building to deliver kind of the next stage of growth for the company. And for UiPath right now, if you look at where we are, go back to founding of UiPath, 5 years, we took RPA and made a $1 billion revenue business. In 2019, we branched out from RPA. And I -- if there is kind of a couple of bullets I would impress is like we are not an RPA company. RPA is one part of our platform. But in 2019, we began adding to our AI portfolio, both IDP in terms of Intelligent Document Processing for structured and unstructured data, process intelligence, communications mining. When you look at where we are today with 18 months ago, launching our agentic -- our business process orchestration, which is Maestro that orchestrates humans, robots and agents. Our AI ARR now is $200 million. That is not switching a metric, changing a definition. That is solid ARR that is coming from real value that we are providing customers with our AI platform and look forward to talking more about it in our breakout sessions and within our Q&A. Then you look at fundamentally where we are. $480 million of revenue, that grew 17%. Our ARR growth rate at $1.9 billion is 12%. And when you look at that, that is now stabilized. I think 1 of the big questions for UiPath was the trajectory. And when you look at last 2 years, we had decelerating ARR and revenue, really some execution missteps, but also some of the change in macroeconomic conditions, et cetera. Right now, if you look at our last couple of quarters, especially solidified in this quarter, we have stabilized the business and the growth rate at greater than 10% as a company. And that is kind of on the backdrop of what continues to be a pretty macroeconomic variable environment. The other big important thing is we're not spending money to get growth. We're not buying growth necessarily. So we are GAAP profitable now. And that is our first, first quarter of GAAP profitability. Again, you look at trajectories, 2 years, we had fourth quarter where we were GAAP profitable. This is the first quarter that we are profitable for our first quarter. And you can just start tracing the trajectory of our stock-based compensation going from greater than 23%, down below 13% or at or below 13%. And when you look at that together, foundationally, we have a strong AI platform, solid growth at scale, but which we're not fully satisfied with and we'll talk about it further, and a really good profitability equation, both on a GAAP and non-GAAP basis. So here's our platform. When I say we're not an RPA company, you can see RPA is 1 box there. I don't want to discount RPA. If I called RPA tokenless automation, or if I call it, deterministic automation. That really resonates in terms of the applicability that it is with the customer. So this isn't basic screen scraping. The deterministic parts of our platform are powering significant enterprise grades of automations in highly regulated industries. But look what's now built around it. So we are one of the few platforms that can have human in the loop, build deterministic automations and deploy them on our platform, build and deploy AI-based automations or agenetic automations on our platform. We are not vendor locked in, so people can bring their own models, their own agents to our platform. Our goal is to orchestrate the workflows for regulated industries and complex enterprise processes globally, that ties robots, agents and humans together. So one other misnomer that you may hear, agenetic orchestration is different than business process orchestration. Agentic orchestration is orchestrating agents. Agents are 1 piece of the equation if you want to drive enterprise automation at scale. These are our advantages, and we'll touch base on them more, but we are a truly unified platform for what I just talked about. What is exciting is we are an incumbent. So we are not trying to go -- if you think about the hundreds and thousands of automations that are there on a deterministic side, one of the ways we were able to grow our ARR base is by looking to the left and to the right and being able to get agenetic processes or agenetic steps that were not previously automatable and then wrapping that around orchestration. And then besides governance, which is something really critical we'll talk about in Q&A, we have deep vertical expertise, health care, financial services. It's not enough to have software in code. You have to understand the processes and that is an expertise we've been building over the last 5 to 6 years. So these are our customer metrics. You can see our largest customers are growing. We are super proud if there is a metric that is there to look at. It is our customers greater than $100,000 and our greater -- customers greater than $1 million. You can see that customers who know us, these are Global 2000 customers as the majority of them they are growing fast with our platform. That should show you that our platform is not just relevant today, it is value-added. And then last is the partner ecosystem. We'll talk about it, but we value this not just because it's a page that is important to all software providers, but it really speaks to the openness of our architecture and how we can partner across every different cloud base that is out there. Every different technology company that is there. We're not married to anyone. So with that, I'm really excited to answer questions. And I thank you for everybody, and I look forward to your questions as well.

Awesome. Thank you, Ashim, for providing that perspective on the UiPath business and the toolkit that you provide to these businesses. With that context, can you just set the table by kind of in simplistic terms talking about the distinction between deterministic automation and then more probabilistic automation?

So deterministic automation is rules-based automation. So where you need the same answer every single time. Probabilistic or a genetic orchestration is given software the agency to make decisions. And as it does that, it will make a different decision every time. I'll give 2 quick examples. And for time, I'll try to be brief. Daniel, our founder actually gave me this challenge when I -- when we were talking about it. Go into cloud or OpenAI and ask it to calculate 2 large numbers. It will rely back on a calculator because that is deterministic. But if you say, do not use a calculator, will you be able to produce the same answer every time? The answer actual response is, no. Because LLMs or the models that are there, they're probabilistic, they interpret data each time differently. When you look at processes like claims, mortgage accounts, I shouldn't, my Chief Accounting Officer and Deputy CFOs in the audience, we don't want to have 2 different calculations for revenue depending on the mood of a model, right? You need deterministic automation. If you have a healthcare claim, you need to be able to look at it. So deterministic automation is super important for enterprise-grade processes because it is low cost, low complexity and the highest level of dependability. Agenetic has its place. There are things that deterministic automation can't do. So when you put the 2 together and then you wrap it with the ability to orchestrate it, you have the chance finally to get to a fully automated enterprise, which we are super excited to be a part of.

That's great. And so you guys obviously provide a platform that encompasses both of those capabilities, deterministic and probabilistic and there's some harmony between the 2, right? But historically, you've been kind of the undisputed leader in RPA market using bots to automate repetitive tasks. So as AI continues to make its way into the enterprise, how do you see those RPA workflows evolving alongside this technology?

They're very synergistic. When you look at our customer base, no 1 really sees a bit, if -- no 1 has come to us to say, we are going to take a process that is working that is low cost, that is highly dependable. And we're deciding to move it to a higher cost, lower dependability solution, right? Area -- the only area where we see -- where we have seen that piece of it ever come in is personal productivity. And I think 1 of the misnomers for UiPath. In 2019, we launched something called a Robot for Everyone, right? That is a very low part of our base. That means if I want to go and download an e-mail or summarize a document, right? Those are things our platform can do today. And it was part of a strategy back in 2019 -- 2018 and '19 in terms of where we are. When you look at our business today, it is regulated industries, and it is high complex enterprise grade automation. That is the majority of our revenue. So when you look at from where we stand today, you need deterministic and agenetic to really drive that in that tier of relationships.

Got it. And before you move on, given we have a lot of journalists here, can you just talk about your pricing model, how the digital bots are priced, how your orchestration solution Maestro is priced and how you present the ROI to your customers and your sales [indiscernible].

Yes. So one thing is like a great advantage of view. I thought that we're not really seat-based pricing is not a major component of our pricing. So let me tell you what it's not to start with. The second piece is we don't have tokenization at this moment. So there's no like large-scale token consumption that is driving a short-term revenue boost in [indiscernible] which way. The way that we price is server-based pricing for our key deterministic parts of our platform like unattended robots. We have -- what I would call kind of subscription consumption-based pricing which is you buy a certain amount of units, right? You buy $1 million worth of units. And for every page, you deduct [indiscernible], right, as an example, that you process. for every execution that you do on our orchestration, you can retire x units that are there. Those are the 2 primary methods of our pricing.

Got it. Okay. And I think it's clear, we'd kind of be beaten around the bush if we didn't acknowledge there's some fear of disruption associated with some of this technology. But when speaking to your customers and customers of your peers alike, it seems like they're leaning more into your trusted platforms than they are trying to move away from them in this environment and as they execute on their AI strategies. Can you just talk about that dynamic and what your customer conversations look like at this point?

Yes. I mean, look, put yourself in the seat of any kind of company executive. You have this wave of AI that is going with these really loud and important voices, OpenAI, Anthorapic, right, Google, et cetera. So I think there's a mindshare that is being taken up right now that we have to acknowledge at the corporate levels, trying to explore what's possible in AI, right? That creates some level of disruption, that creates some level of fear, that creates some level of uncertainty of what is there. The way we -- the way our customers have responded is usually what's happened is as they process, where do they really want to deploy these models? What's the real impact of it? There is a place for those companies, and there is a place for UiPath. And UiPath is actually a great channel for a lot of the models that come in, right? In terms of pure-play competitors, we don't really see. There's not -- if you go and say, which companies have RPA unstructured document capabilities, processing capabilities agent capabilities and business process orchestration, not agenetic orchestration. There are very few companies that do it. So really, the discussion with our companies is really targeted. And so we're selling more and more into lines of businesses with specific outcomes in mind, and that is really helping us. And the second piece is we verticalized. I think 1 of the things that people have not seen, and I think we can do a better job showing it is, we used to be purely a horizontal platform. Now we have products and capabilities for revenue cycle management and healthcare. We have processes for procure to pay software for procure to pay in the office of the CFO. And I think that is also driving further differentiation for us. SP1.

Okay. Yes, that's great and very clear. So I think it's a good segue into my next question. Maestro is your control play and your orchestration playing for agent processes, which makes a ton of sense, given how embedded you already are in these workflows. How do you see Maestro [indiscernible] with competing solutions from other platform players, other AI management solutions? And do you ever or at all see Frontier model providers as competition or more so as partners?

We see it more as partners. LangChain is an example. We have actually a great integration, a great partnership with them, just to give an example of it. From our standpoint, the differentiation is, 1 is trying to manage AI, and we are trying to manage processes, regardless of the third and piece of software embedded or an AI automation in there or deterministic automation or a human or 2 or 3 of them. And that is really our key main difference. The other piece is observability. So what I would ask everybody to is Google Maestro UiPath. When you do it, look at the click on images, right? You don't have to read all of the technical documentation. You can, if you wish. But look at the image, you actually will see the process. And if you click on video, you'll actually go and be able to see the process moving. So transactions move through the process. Imagine a world where you have digital workers, that you can now see as though it is a factory floor. That is for us, that is kind of how we think about Maestro. No, we do not think about the Frontier models as competition. We think about them as integration points that we have to continue to drive it with our customers and within our partner ecosystem.

Okay. Great. And on pricing, so as you embed AI into these RPA workflows, into your broader platform, you win the orchestration layer, it becomes capable of executing more complicated multi-step processes, right? So what is the typical pricing outlook see when you sell those solutions? And is there a point in the future when those kind of become table stakes?

Two ways I can answer it. One is like our pricing scheme, I think, is dissimilar to what we talked about. We are experimenting with outcome-based pricing that provides significant offlift, but we take some upfront risk as a part of that. There are several customers that we're exploring that with. If you put that aside, if you look at first quarter, 16 of 20 deals were based on, you had AI components as a significant component as a part of the platform. It's 6x larger than all of our other deals. When you look at process -- when you look at our $1 million-plus customers the majority of them have large attach rates for AI. So from our standpoint, the more value we generate, the more software gets pulled through, the less discount that comes in, those all go to higher and higher ticket sizes. And where you see it show up is our $1 million-plus customer accounts and our $100,000-plus customer accounts, which are up 11% and 16%, respectively.

Okay. And then kind of to shift gears. You've also talked about how these coding agents can lower the time to value, the implementation time for these workflows, ultimately allowing you to go after more of the long tail of these automation opportunities in the enterprise. So can you talk us through that dynamic and how significant that reduction in time to value can...

Yes. You're talking from months to weeks or from weeks to days. It is really significant. And from our standpoint, like the best metaphor, our CPTO Rego Malpani gave us. our goal is that you can 3D print processes, 3D print workflows. And why I think that matters is if you thought about like today, the experience of building an app unlovable on rep on some of these platforms, which are incredible, Imagine being able to print a process in the same way. And then as you do that, the question I get is, hey, why don't you do that on those other platforms? Well, think about it this way, like if you've made an app on 1 of these platforms, you know the difference between an app and a process, right, what it can do. And so from our standpoint, from week -- from months to weeks, from weeks to days, that's the goal. And we've already launched our first set of coded agents. This isn't hyperbole. The results are actually super processing in terms of what we're seeing with our early customers.

Okay. Great. And I think 6 months ago, you launched a forward deployed engineering team. So can you talk about how that ties into that strategy?

Yes. So the piece we didn't talk about for time to value is, I think there's 2 time to value equation. One is how do you make development on your horizontal platform faster. The second is when you go across an industry like health care, most every health care provider that we see is looking for certain solutions that they have been automating, prior authorization, claims denials, revenue cycle management. When you go across the financial services industries, mortgage processing, HELOC filings, et cetera, right? Our verticalization, our FDs have twofold areas. One is to be working with our customers so we can enhance our product to get greater verticalization into our product as we launch our vertical solutions to be there to perfect them, to add features and functionality that's there. The second is we use our FTEs as we deploy the first wave of agents. Many of our POCs were bolstered by FTEs for 2 purposes: ensuring success. And the second piece is getting the feedback back to our product. That's kind of in the early wave of where we are. As we go forward, we really think FTEs are going to become more and more a tip of the spear type area for our key customers, because this place is going to be very fast moving. The demands are going to be higher, the complexity is going to be higher, and they really serve as that connective tissue between what was a services organization and the product organization.

Got it. Okay. And does that have any margin implications? I know it's early on.

No. Actually, what is -- so investing in FTEs alone, of course, as we add headcount. However, the way our approach has been, we are investing in 4 deployed engineers, key R&D areas like coated agents and vertical solutions and sales capacity. These are kind of 3 key areas that we're investing in. We are devesting in every process that we can [indiscernible] by ourselves. So when you look at our margin, I feel like this is the area that's there. We're not in cost-cutting mode. We are in really strategic capital allocation mode. So when you look at whether it's geographic territory, whether you look at management layers, whether you look at it centralized organizations, we are constantly driving efficiency into those areas, and we are increasing our capacity and our capability into the areas I just said.

Okay. Got it. And I'm going to jump to 1 of my last questions actually because it's on the same topic. But you made some really solid progress on your margin on the bottom line over the last few years. And given that progress, you raised your long-term operating margin target to 30%. Can you walk us through what levers you have in mind as you think about making it to those targets? Or if it's more of kind of a North Star [indiscernible].

No, I think -- look, I think every quarter, every year, I feel for the last few we've significantly improved our margin. I personally think free cash flow margin and GAAP profitability are the 2 most important things. The 2 most important things I look at. So if you look at our free cash flow, like last year, we were at $370 million. The year before that was significantly lower. This year, we've kind of given a modeling point of around $425 million in terms of our free cash flow, right? So I don't -- the first thing is it is a North Star, but it's a North Star that is reachable. It's not something that we're just directionally going after. The levers we have are 3. One is, frankly, cut non sense out, be a highly efficient, be highly focused and prioritize its basic capital allocation, prioritize your -- both your human and your expenditures where you have the highest return, that's the first principle. The second area is as we do that, as we identify processes internally while investing. If we can keep our cost base relatively flattish while growing top line, you naturally get there very quickly. But we are not afraid to invest to be able to grow. We actually feel like right now, we're kind of in [indiscernible] of where we are as a company, act 2, act 3, 12:43 PM we are going to invest to make sure that. We can take a -- take a large part of the market that we have in front of us. So I would say long-term goal, 30% where I think 23%, 24% already, 6 points of operating margin between leverage and discipline completely within our grasp. And then the only question is, if we see market opportunity, we'll pace that accordingly.

Okay. And is there a portion of that where you're leveraging AI to drive operational efficiencies as well and to use the term, I have recently kind of eating your own cooking.

Yes, yes, drinking your own champagne, whatever it could be. Eating your own dog food has been like in -- put away. [ Hitesh Ramani ], who is our Deputy CFO. He's actually in the audience. He's leading that effort across a lot of our back-office functions. We have 70-plus agents, I think, in production already. And we're still feel like we're just at the starting point, right? We were able to significantly drive transactional efficiency. We're able to transform functions like marketing, we're able to transform and get productivity out of engineering. So in the past, if you look at our product road map, I would say our product road map is probably 3x the surface area, but it is with the same number of people. So that is coming from coded agents and using the tools even in the engineering shop in terms of the productivity they're getting. So we are kind of -- we're doing that. And within our own platform, we continue to drive automation. We continue to drive agents. And the orchestration and differentiator in terms of doing it now larger at scale, but still being able to have the right controls in place being a public company.

Got it. Yes, that's very interesting. And something that you and Daniel have talked more about recently that I think is very interesting is the test cloud opportunity as these agentic workflows proliferate. Can you just talk through exactly what that product is for the audience and how large that [indiscernible].

Yes. So test is like -- it's a dark horse for us. I think I purposely also let it be a dark horse for a bit, but you're going to see us kind of like more and more emphasize it. If you just take what application testing is, everybody, I think, should be pretty familiar with it, right? You have upgrades into your software and then you have to have scripts to make sure before you put that software into production, the key transactions are flowing. So about 4 years ago, it was a very logical thing is that if you're automating the actual process, why are we not operating in the scripts that have to be written to ensure that the applications are in good standing as they get updated and moving. So if you take about -- take every S/4HANA implementation that's happening, you have a massive amount of transactional testing that has to be done. A lot of that is manual or a lot of the software in the space is archaic. We actually have the most modern platform now. It has been recognized as a leader by Gartner in terms of the category in which it's in. What's exciting is that it opens up a different buyer base within our company. So we're now selling into true CIO organizations in terms of QA/QC, extra. And we've seen -- we haven't disclosed it at this time, but that -- the ARR growth on that has been super exciting. It's kind of operating like a startup within a startup and is a really second throttle of growth for us as a company.

Got it Okay. Yes, very interesting, but we'll leave it at our course for now. So we have a few minutes left. Anyone in the audience want to jump in with a question. Otherwise, I can ask a couple more to finish this up. [indiscernible] the breakout for questions as well. Okay. So Ashim, you've continued to maintain best-in-class gross retention rates, high 90% range. But your net retention over the last couple of years has depth out a little bit until the most recent quarter, right, when we saw it step up 2 points to 109%. So as we think about everything we've just discussed, can you talk about what's driving that inflection? How you all are driving customer expansions and just walk through the mechanics of those expansions a little bit?

Yes. I think, I would say 5% to 6% of it is just better execution, which Daniel has really driven over the last 2 years with getting the field flatter, getting it close -- getting management closer to the field, driving more disciplined motions. So we have lost touch I think, 2 years ago with our customer base. And we openly talked to that. I think what you're starting to see now is kind of the rebuilding of both trust and relationships and that intimacy with the customer base that is, I would say, a foundational ingredient of driving more and more software and more and more processes through our platform. The second piece is we have more products to cross-sell. So when you look at Maestro, when you look at [ IXP ], which is advanced unstructured document processing, when you look at WorkFusion, which we acquired, PEAK that we acquired, you have more and more parts of our platform that you can sell across our installed base. So our installed base is super powerful. And as we get more products as we're closer to the cutomer, that is that gives us a real chance to drive that leverage. And what we're cross-selling in is both deterministic as well as AI. If you look at leading segments, healthcare. Healthcare, it is all AI all the time, and it pulls through deterministic automation that is needed. But if you look at the public sector within Europe, RPA is the hottest topic. So attending on the market, we're able to continue to drive upsell across our platform. And what's exciting is, I think U.S. healthcare is actually a pretty bleeding edge type of industry. when it comes to technology, and it's led. So now I have a lot of confidence that says in the European market that same dynamic can start coming.

Okay. Great. We've got 1 more minute. So I'll sneak 1 more in. So you talked about the kind of credit base, retire the credits over time as you execute on these workflows. How -- is there any way you'd expect that to change over time as you continue to iterate the platform?

The answer is, I don't know. Just in all candor. I think we have a monthly pricing council. I think the world is evolving very fast. What we don't want to do is like major react to change our pricing model to like jump on a bandwagon, so to speak. Our best and most reliable source is our customers themselves. So what customers are really nervous about today.is like just unguarded token consumption, token burn. You've seen public companies come out about it. You've seen different posts and different narratives being there. So our advantage point is like we want to give predictability of cost to our customers. I think if you have unpredictability cost, it hampers a long-term adoption. It may feel short term, but it really hampers long-term adoption. So from our standpoint, predictability is going to be a key pillar, and then we'll see how the industry evolves.

Okay. That's great. Well, thank you so much, Ashim for being here. Thank you all for attending the UiPath presentation. And I believe our breakout is in [ Adler ] upstairs. So we'll see you there in 10 minutes.

Thanks.