Awesome. Thank you, everyone, for being here today at the UBS Global Technology and AI Conference. My name is Radi Sultan. I cover the mid-cap infrastructure software stocks here at UBS. Next up, we have Pegasystems, Ken Stillwell, COO and CFO, and Peter VP of Corp Dev, and runs IR as well. So, first of all, thank you very much for being here today.
Absolutely. Thanks for having us.
Awesome. Maybe just to get started, for investors who are newer to the Pega story, can you provide some background on the company?
Sure. Pega is, you know, we've been around for quite some time in the workflow automation. We drive AI. We use AI to drive decisioning largely and significantly around different customer engagement use cases. So we're really trying to help to automate, speed up work that's done at scale, to drive better decisions across the workflow, and to work as the orchestration or the middle layer around all the different various types of work that are done at large organizations like UBS.
Awesome. And maybe just to start, Pega's had a fantastic 2025, accelerating growth, free cash flow. What have been the sort of biggest drivers behind that momentum in 2025?
So I think there's a few, and I probably would, some of these would even blend together in terms of the impact. But we went through a very important sales transformation a couple of years ago. And what we really focused on was making sure that we had a significant percentage of our sales team that was deeply engaged with our clients and spend a lot more of our time in those sales activities versus a lot of the lead gen and the marketing type activities that really isn't as relevant for a target org model like Pega. Excuse me. The next element was we released Pega Blueprint, which I'm sure we'll talk about through the course of the morning. Pega Blueprint is our way of leveraging AI as a design agent of sorts.
It helps on that front end of the ideation, the design of the application, how that application is materialized into a production product, and many of our clients are adding new workflows, but also increasingly trying to move off of legacy applications into a more modern environment. Some of that's because they want to get on the cloud. Some of that is because they want to leverage AI in a much greater way. The third piece is that we have kind of started to increase our focus on new logos. When we went through our sales transformation a few years ago, we really dampened down our focus on new logos so we could get the transformation right, so I think we've really seen ourselves hitting on a number of dimensions. The sales productivity change, leveraging Blueprint to build faster, early stage pipe and advance that.
That helps us become more relevant with our clients and help their needs.
Awesome. ACV growth was mid-teens in 3Q 2025. How does that impact your confidence in sort of the full year 2025 ACV growth guide of 12%?
So we guided, as you're pointing to, we guided 12% at the beginning of the year. We do not re-guide quarterly. Through the first three months, excuse me, the first three quarters of the year, we're at 14% annualized ACV growth. And that's about 50-ish% constant currency increase in net ACV growth. So it's a pretty significant increase over last year. I think it probably is, it goes without saying that if we landed the year at 12% after where we are through three quarters, that would be a very disappointing finish. That said, we don't re-guide. So we'll work hard through the rest of the year and look forward to our results in early February.
Awesome. Maybe just drilling down into the cloud side, Pega Cloud ACV grew 27% year- over- year in 3Q. What's been driving that traction? I know you mentioned modernizations, but maybe you could just speak to what's been driving traction there.
So it's interesting. The early adopters of moving to the cloud, there was a lot of momentum around moving applications to the cloud. They were typically the more simpler use cases or they were net new applications. What you've seen clients now start to hit are things like ERP and moving more complicated applications to the cloud. There's still a desire to do that, but some of the momentum is a little harder as you get to some of the more sophisticated applications. However, we are seeing our clients, like UBS and like your tech team actually talked about earlier today, is a big desire to move faster to the cloud for a number of reasons. One is security. Two is the usability, both internal employees like yourself using internal apps or customers like Pega using your technology.
Also, you can't really leverage AI with a lot of the old COBOL mainframe applications that are built. So really, there seems to be a lot more momentum connected to AI, connected to security, usability to be able to get to the cloud faster so that they can leverage new technology. So what I would have said was barely a top 10 initiative with clients five years ago, which was digital transformation. I would say is probably in the five to 10 range. I would say now is in the top three.
Awesome. Maybe just following up on that, a question I get actually is sort of how the competitive landscape here has evolved, especially over the past 12 months and maybe as you think about the next 12 months. Just maybe spend a little bit of time talking about sort of the competitive landscape, how that's evolved, and what you see as the biggest sort of competitive differentiator as a Pega.
Sure. It's interesting. What AI has done, I really think in an interesting way helped reinforce what Pega's differentiation is. Because what it's done is it's really caused a lot of conversation around where are the best use cases for AI. The best use cases for AI are places where you don't have to force the models to operate through a very specific structure. The models are built to be flexible, built to be like a human would kind of explore. And I think there's a lot of use cases where that works really well and that you don't need 100% certainty, you don't need a repeatable process. But there's also a series of activities that need to, maybe because it's a regulatory situation or because it's your own differentiation as a company, or it could be internal controls, etc., that it has to follow a very specific workflow.
And when you have that, what you do is you get the best of both. You've got the structure of the workflow, but you have the agents actually executing all of the activities at each stage and step of that workflow. So most of the conversations I've had with investors are really around this, understanding the differentiation between deterministic workflow structures and really semantic-type communication AI. And I think it's really been helpful to be able to help the market understand the differentiation of those two.
Yeah. No, I mean, I cover UiPath and that distinction, I think, in a lot of the, especially in the regulated industries, between deterministic and sort of this generative and sort of the outcome is a little bit less reliable. And they struggle, I think, with that sort of side of the equation.
Yeah. I mean, a very simple use case is if you go, if you have a problem with a washer or dryer in your home and you said, "I'd really like to understand what happened here." You can scan the QR code on the washer, you can get to a website, you can go through a search and explore, as I might call it, around what might be the problem. And if it gives you the wrong answer, it's not the end of the world, right? You keep looking, you keep searching. So that's a use case where we expect it to be less precise.
But if you go through a loan application process and one person is approved and one person is denied, and then you say, "Well, what was the process you went through?" And the model says, "Well, for Radi, I did it this way, and for Ken, I did it this way." The first question is, "Well, was that discriminatory? Was that actually, do you have a higher credit quality or lesser credit quality?" You start to get into regulatory bodies love to understand why do you have a different process for one person versus another. So I think that it's really in real life very easy to see the use cases where you really need the structure. The AI is still doing the work, but it's doing the work as directed through rules and workflow and process, as opposed to the AI is doing work freelance, right?
Because that use case is fine to support that.
Awesome. And maybe let's transition to talking about Blueprint. A lot of buzz around Pega Blueprint. Maybe you can just talk through a little bit of the background there. What have been sort of some of the early use cases where you've seen the most traction?
So when AI, when we first landed on ChatGPT in, I don't know, February of 2023 or whenever it really started to get into all of our minds, we immediately went to, "Okay, what's the biggest problem that we have at Pega?" The biggest problem that we had at Pega was that our platform is so powerful and so highly configurable that it takes a long time. It could take a long time to build it, and there's a lot of variability in how the build happens.
So we then jumped to, "Well, if we could use the AI models to help using a structured approach to be able to build these workflows and build the application much more in the design phase, we could completely change our business and how we interacted." So that's where the Blueprint origin started from, was trying to fix that implementation, that upfront design, very time-consuming, very costly, lots of variation, lots of collaboration. Our first version of Blueprint was you would go through a couple dropdowns and maybe a little bit of free text, and it would produce a PDF document. That PDF document would print out, and that would be your starting design document. If you fast forward to where we are now, you go in and you start with that same experience, but Blueprint actually shows you what the working app is going to be like.
You can actually run test data through it. That app is further and further built into the final version. Where we hope to have Blueprint in the next year or two is that the majority of the actual app building is happening in Blueprint. Now, it may still require some level of AI-assisted configuration to build the workflow, to connect the integrations, etc. But it's a world that we never envisioned before AI, which is a world that doesn't require deep technical expertise on Pega. It doesn't require clients to have to wait for resources to be available, and the speed of iteration is fast. And then lastly, if you build an application the way it should be built using the best practices, it's much more scalable in the future. You don't have to worry about code changes and modifications as your business changes.
And how does that impact the go-to-market? You think about maybe any sort of pull-throughs to your core business as well. So maybe you could just talk through how that impacts the go-to-market and then any pull-throughs you're seeing across the business.
Another challenge that we had because of how deeply technical the platform was and how knowledgeable you had to be to work on the platform, that also required a ramp time for salespeople. You typically wouldn't hire a salesperson, bring them right in, and they'd start selling Pega. There was normally a 6-month - 12-month training, enablement, certification, mentoring, peering. With Blueprint, for any of you who have seen Blueprint, you can go to our website and you can actually see it for yourself. All you have to do is put your email in. Now a salesperson can actually start Blueprint in the first meeting with a client. If you hire someone that already knows, say, a client, UBS, they don't need to wait 6 to 12 months to figure out how to pitch Pega. They go in with Blueprint and say, "What's your first problem?
Let's actually show you how we can help with digital transformation." So that's how it's helped on the selling front. What we're seeing now is faster pipe build, faster pipe progression, better win rates, less resources needed in that selling process because you have a salesperson and a sales engineer that can pretty much do everything that happens through the selling process, where that was typically not the case before. You had to bring in someone that knew the vertical, someone that might have known the use case. There was more of a need for more resources.
Does that change when you think about maybe the longer-term growth algorithm of sort of new customers versus existing customers? Because it is easier to sell. Does that change the longer-term growth algorithm to more new customers? Or maybe how do you think about that?
Yeah. It's a really interesting point because three years ago or two plus years ago when we actually went through our sales transformation, we actually banned focusing on new logos for 2023 because we just didn't want to take any risk because we knew that we weren't going to hire new people. Well, now when we think about the opportunity set, you start to say, "Well, Pega has 700-800 clients, 250 of which give us more than $1 million a year." So the majority of our business comes from 250 clients. But if you look at the addressable market, it's probably 5,000-15,000 companies that have workflows that are completely relevant to Pega. That doesn't even count the fact that most of our existing clients are not 25% of the way through their digital transformation journeys.
So I think it opens up both addressable market with our existing clients because you can go after more of that transformation business that's out there. And also you've got all these companies that Pega has never sold to. And so that changes our, that puts some interesting pressures on how we think about our go-to-market changes to be able to leverage that because you can't do that all with direct selling, right? You have to start thinking about the ecosystem more.
Got it. Got it. And your Chief Product Officer recently announced some updates to Blueprint, including enhanced business rules. Can you just walk through those product updates? How does that impact the TAM, your ability to sell Blueprint, how that opens up the market?
I think there's a few things that I think are worth mentioning around the continued advancement. One is the ability for Pega Blueprint to ingest information from other systems like AWS Transform. Quite frankly, you can take a video on your phone of watching over the shoulder of someone using an application, and Blueprint can figure out what's happening and actually build the workflow. All of the various protocols around agent to agent and agent to communications and how that feeds in, we've embedded actual agent assist in the Blueprint, meaning if you're on a field or you're trying to do a step in Blueprint, you can actually ask the agent embedded in Blueprint to help you to explain it, maybe make suggestions, what common use cases you would expect.
I think the really interesting and I think one of the most powerful things that we've added recently is the ability to see the working app as you're building the Blueprint. So what you can do is, as you start to get through, there's a certain amount of fields that you have to complete, and it's not much, but to be able to establish the base workflow. You can then click "Preview My App." It actually shows the application functioning. When you make changes to the app Blueprint, the application changes in front of your eyes. You can add stages, add steps, add different fields. You can add workflows, I mean, anything that you do. So it really allows you to, as you're making changes, experience what that might look like in the application.
Got it. And as Blueprint evolves, you add more features and functionality. Does that change who you compete with? Especially everyone seems to be spinning up their own agent platform here. Everyone throws around automation, but maybe can you just talk through how that is sort of impacting the competitive landscape and where you see that going?
So for us, it starts and ends with that workflow automation and AI-based decisioning is what Pega does and what we do better than anybody else. So we are the leader. We are not a leader. We are the leader. We've been the leader for 25 years. The hurdle to our growth was addressable market and getting to enough clients because of the need for this deep expertise. So as we start to compete more, we will compete with more vertical players. We will compete with more mid-market players. We will compete, quite frankly, with a no decision from a client, a decision of UBS saying, "Well, I'm not going to go after those apps because it's just too costly to do it." We're competing with that legacy decision of saying, "No, it's much cheaper now.
It's much faster." So I think there is a different selling approach than, say, just competing with Salesforce or Microsoft or ServiceNow. It's much more around the lack of action and the fact that these applications maybe were never even envisioned that they could be modernized.
Yeah. Maybe just transitioning to the relationship with Amazon, given this is overlapping with re:Invent this week. In July of 2025, Pega announced a five-year strategic agreement with AWS. Can you just walk through the AWS relationship today? Anything you can quantify around traction you're seeing there? Sort of any pull-throughs to the business?
Yeah. It's been a wonderful partnership. When I started at Pega 10 years ago, we had a handful of what I would call were hosting relationships with clients. I mean, we may have referred to them as Pega Cloud. They were far from a cloud solution. They were basically just running on VPCs at AWS. And through a series of very strategic partnering investments, we were able to influence the AWS roadmap. We were able to get things changed on how AWS identified advancements in their own platform. Specifically, we're FedRAMP High, and we took AWS with us into that certification. And we said, "Look, there's solutions like Lambda and other capabilities of the control plane that they needed to adopt." And so I think AWS has been a great partner. And interestingly enough, we are one of the largest number of VPCs as a client for AWS.
So of all the companies in the world, Pega has one of the highest amount of workloads actually running through AWS. And it also ties to the level of efficiency that we can actually get that at our scale, we're able to run that much volume. So it's been a great partnership. AWS, Google, Azure, all the hyperscalers need everyone to move to the cloud, right? It's their business model. And so they benefit from digital transformation, from legacy transformation, from app modernization, whatever the buzzword is that the industry is using. And so they're very vested in this. If you go to the legacy transformation website or site on AWS, you will see Pega as the sole software provider that they partner with. So we feel like our relationship is very deep. We also have a newer but growing fast relationship with Google as well.
We also are AI-agnostic, which means we'll use Bedrock on AWS. We'll use Gemini on Google. We'll also allow clients to bring their own models or run it through their gateway, etc. So we feel like the partnership is great, and there's enough business out there for us to have similar partnerships with other partners.
Awesome. And maybe just drilling into Pega GenAI Blueprint works with AWS Transform for mainframe. So maybe can you just talk through how clients use Transform and Pega Blueprint together and how big is the opportunity there?
So the amount of legacy workloads that were built on COBOL running in mainframe environments is massive. Way more are there than have been transformed. So there's just, and it is a problem, right? There is a technology gap that I think large organizations or mid-size organizations, governments, are trying to solve. So AWS Transform essentially looks at the COBOL code. It basically forms what it believes that application is doing. And that's a map that is ingested into Blueprint that actually builds the workflow. So we have a very tight partnership where when the client's working with AWS to transform, AWS might be talking to them about moving those apps to the cloud. Pega's talking to them in partnership with AWS around modernizing those apps and getting them on the best platform in technology. And so that's kind of how the relationship has been working.
Is there any vertical or sort of the set of verticals where you think there's sort of a bigger opportunity there? Like I imagine regulated industries still have a lot of that COBOL exposure, but maybe just sort of any sense of where you see the biggest opportunity for that Transform?
So this is not, I don't think this is an industry-specific problem. I don't think you're suggesting that, but really look at where the spend is. Financial services has a percent of revenue as spends a significant amount. I mean, the number of software engineers that companies like yourselves have is massive. And those engineers are retiring. And most of your CIOs would say, "I don't want to continue that model." So I think financial services is a big one and public sector, governments. I mean, government technology, take the political angle out of the DOGE discussion. There is no doubt that running 50-year-old systems in the government for constituent management is not smart and is not safe. So there needed to be a modernization. And so I think those are two examples. But you could go across every vertical. I just think there's so much scale in financial services.
The public sector, you're more aware of the opportunity there.
Yeah. I mean, maybe just zooming out a little bit when you think about this sort of legacy transformation opportunity, right? It's clearly a big opportunity to help these enterprise clients move from mainframe SAP to Pega Cloud. Can you just talk through at a high level, what have sort of been the biggest trends in those digital transformation modernization conversations where you're seeing the most traction?
Security has been a pretty big one. As things get exposed to the internet, as you start to let remote work was a really big impact in terms of thinking about the security perimeter because when people are working at Pega or UBS, they're not working from secure locations. They might be on a Wi-Fi at Starbucks. They could be on a Wi-Fi at their home that is not properly secured. So when you get people outside of your physical locations, it introduces a risk. When you start to have customers more engaged directly with the workflows, which a lot of companies are doing more to get CSRs or customer service reps out, that exposes risk. So I think security has been a big one.
And there's a lot of certifications and new standards that companies like Pega have to keep up with to be able to be competitive in that market. Another one is usability. I mean, there's a very big drag on employee and customer satisfaction interacting with some of these legacy systems. I mean, they're just, mobile is one dimension, but it's really just the overall ease of experience. I mean, every bank, every large organization has spent a lot of focus and a lot of money on trying to differentiate the digital experience. You don't have the luxury anymore of being able to be face-to-face with your clients. Your clients don't walk in branches. They don't walk in stores at the pace that they did. Their experience is in the digital storefront. The digital storefront's terrible. Constituent management is another one.
One of the biggest things we hear when we go and talk to our elected officials is the amount of feedback they get from their constituents about how hard it is to do basic things with the government. And a lot of that is technology. So we've partnered with large organizations in both civilian and defense to try to change the customer experience. And it's not just because you want it to be efficient. It's because there's so much drag on the system when people have to use paper and do the things that the IRS is a great example. I mean, you get a letter from the IRS that says, "Hey, you were missing adding $100 for a 1099. You have to respond with a letter." They respond back, "Thank you. We'll be back within 90 days." And they respond back, and you respond back. It's really silly.
That happens in every agency and still, unfortunately, happens in large organizations like ours.
Yeah. I mean, maybe when you think about the pace of cloud migrations more broadly, I mean, I think there was sort of this thought that AI would be this huge catalyst, and it hasn't necessarily come through, I think, fully to that extent. There are obviously moving parts there. Maybe you could just talk through sort of the rate of cloud migrations and sort of over the next 12 months, how you see that changing.
The size of the Pega Cloud business has been a massive change from 10 years ago. We went from under $50 million in ACV, and that's been an almost 15x increase in that number in a matter of eight years or so, really. But not everybody has moved to the cloud yet. Just like UBS is making strides to move there, and we're working with you on some of those initiatives, but you have a pace in which you can adopt change. Many of the applications that need to move are mission-critical. Like the bank or the organization is running the business on that application. They cannot afford to have it go down. And so there is a pace of adoption of moving to the cloud.
So I think that we will see our business kind of approach 70%-75% of our ACV will be on Pega Cloud in the next few years. Will it be 100%? I can guarantee you it will not. Will it be 90%? It might be. Will it be over 80% at some point? Yeah, more likely than not. But there's just going to be use cases that just for whatever reason can't get to the cloud. Specifically in financial services, you have regulatory hurdles because the regulators will not approve certain use cases to go on the cloud. So I don't think we'll ever get there 100%, but we've made a ton of progress. We're probably two-thirds or more of the way down the path of where we'll probably steady out.
Yeah. Maybe speaking of the next few years, at your investor session back in June, you set the long-term target, $700 million plus of free cash flow in 2028. How does the business need to evolve to meet or exceed that number?
What's really great about a recurring model is that it is very predictable. What now looks obvious was not obvious to investors three or four years ago when we did $22 million of free cash flow and we said, "Next year we're going to do 200, then over 300." Now you're seeing that play out. I think there's a very low risk of our free cash flow range because of the amount that's recurring. It really is heavily tied to our growth rate and our investment profile. Because our business is high retention rate and very sticky, it doesn't take a lot to see what needs to be done to get to those levels.
I'm probably most proud at Pega of our ability to get out of the subscription transition, to pay off our debt from the convertible, to get our cash flow levels up to 30% free cash flow level, and we're hopefully going up from there over time, and to actually meet or beat the commitments we've made around free cash flow generation.
Awesome. Maybe just to wrap it up, you talked to a lot of customers, a lot of CIOs. What do you see as sort of the biggest CIO priorities in 2026? And then how does Pega help fit into that equation?
I think the biggest question that CIOs are asking right now is how and where AI, right? It's like, "How do I use AI? Where should I use AI?" And that becomes a, "Where shouldn't I?" as well. And I think it's a really important process that our clients are going through to make sure that they advance as far as they can, leverage AI as much as they can, secure their proprietary assets and customer base, meet all the regulatory environment. But I think it's AI and it's the, "How should we use it and where should we use it?" Because it is not everything everywhere. It needs to really be targeted.
Awesome. Thank you so much for being here.
Awesome.
We'll wrap it there. Thank you.