Pegasystems Inc. (PEGA) Earnings Call Transcript & Summary

Hey, everyone, thank you for joining. Delighted to have here Alan Trefler, Founder and CEO; and Ken Stillwell, COO and CFO, here on the stage. Guys, thank you for joining us.

Thank you, Pinjalim.

Thanks, Pinjalim.

Why don't we start with maybe a brief introduction by yourself and maybe a little bit about Pegasystems for the people in the audience that might not know about the company.

Sure. So I'd describe myself as a Founder and still CEO. But it's been since 1983, so I'm feeling pretty secure in all of that. Pegasystems is a company that delivers software to do AI-driven decisioning and workflow automation. And we have been around a long time, been through a lot of technology transitions and are very excited about the ones that we're in and what we're going to be able to do for our clients.

And I'm Ken Stillwell. I've been with Pega for -- been here for coming up on 10 years. We've made some really big shifts in the last few years, starting with the movement into a subscription business, followed shortly thereafter by really doubling down on cloud and committing ourselves to be a Rule of 40 company. And I think of late, with the introduction of Blueprint, which I know you'll ask us about at some point, I think we've really given ourselves or positioned ourselves with the opportunity to further expand the addressable market that we can attack at Pega.

Great. So maybe, Alan, I'll start with you. 40-plus years Pegasystems has been around, right? And the architecture you designed quite a bit ago, it has evolved over this time, but it's still relevant today. So talk about kind of that journey, that evolution of the foundation of Pegasystems. And how does it kind of help you differentiate your AI versus other AI solutions in the market?

Well, conceptually, we started the business with the goal of bringing businesspeople and IT people together to empower them to use their technology more effectively. And I think that's ever more relevant, and this world of AI gives us tremendous latitude in which to do it. Obviously, the generations of software, and we're on our sixth conceptual rewrite of the platform over all of these years, is enormous on a technical basis. But from a functional basis, what we're really trying to do is capture business intent and from that business intent, simplify the ability of businesspeople to take control of their businesses. And now with generative AI and statistical AI and the other things we've been able to put in, we can see that really accelerating, and we can see ourselves doing that better than we've ever done before.

Yes. So I guess the talk of the town whenever we talk about Pegasystems is Blueprint, right? And that's kind of the topic du jour. To my understanding, Blueprint kind of compresses the life cycle of application development from -- I don't know how you want to characterize it, but...

So I would say it's more even than just that. When we would go work with a client who maybe wanted to renovate the way they onboarded customers or they wanted to handle either a back-office process or a front-office process, it wouldn't be uncommon for us to have something we call the catalyst exercise. We send a bright team of people in for 1 to 2 weeks. They spend time at a whiteboard. They would draw things. We had funny-shaped stickies that they would paste up on the wall, and they would conceive of what it is that they wanted to create. Today, with Blueprint, you can actually put the goals, the input of what you want, pieces about your business, you can actually take documents that you use in the day-to-day execution of your business, and you can feed that into Blueprint. And what used to take weeks literally now takes a morning and is staggeringly better. And so I think that, that really starts much earlier in helping people conceptualize how they can use technology in a whole new way as opposed to just the noble work of trying to make it easier.

I think to add to that, I also think that what Blueprint allows us to do is it allows us to engage with the users in a way that they don't have to already know what Pega does. They don't have to already understand what workflow systems are, what they -- you can really -- so that means new logos. It might mean new divisions within our existing logs that may not be super users or really experienced around what Pega does. And that's really part of that compressing the time frame because much of the time that we spent were the 3 to 5 meetings that happened before we actually showed the client Pega. And now that's in the first 5 minutes, and that's transformational.

Maybe before I go into customer conversations, maybe talk about that differentiation. AI is kind of the topic everywhere, right, nowadays. So maybe talk about the differentiation of Blueprint, what Pega brings to the table versus your next Agentforce and there are so many other application platforms, AI application platforms that is.

Yes. So I'll try to be pretty specific and explicit because I think there are some very important elements to this. There's so much buzz and so much hype and so much noise. I think it's easy for things to get lost. There are some people who believe that the way you should create agents to automate portions of your work is to go to some prompt studio and author some textual prompt that, in conjunction with some data, will go off and do something. And you might have not just one of these, but if I listen to some of the companies you mentioned, you might have 6,000 of them doing specific elements of digital work. Now when we think about that, we say, well, boy, it's a creative to use the language model to help you reason and help you think about what to do. But that just seems to us to be the completely wrong way to do it. What our view is, is that you should use -- and Blueprint is our tool for this, you should use Blueprint to harness the power of LLMs to harness our experience, which we've captured, to harness actually going out to the Internet and asking the Internet, hey, what's the best practices for this particular business problem, the thing we're doing? But to not do that at runtime, not do that when you're engaged with a customer handling an answer, but to do that in advance, to do that at design time, and then having taken that step to understand and do the reasoning to be able to map that out, to be able to show somebody in advance how you're going to handle certain types of requests, how you're going to make certain types of decisions so that a person or an auditor can say, yes, I like that. That makes sense. And with the power of AI, you can suddenly become extremely prolific in making all the different workflows to handle all the different situations. So you can really anticipate but have it all laid out in advance. Then at runtime, we think, no, no, you don't want to reason at runtime because you don't want to have the risk of a hallucination or something that was unpredictable. You want to at runtime just use the language model for semantics, for language to be able to interpret what somebody is saying, what they're asking and hook that up to the right workflow and then feed the workflow what the person says and feed the person what the workflow says using the language model for that, which is absolutely safe. There's no risk of hallucinations in that. And in addition, it's really super powerful because it's predictable, it's reliable. It's going to actually treat the 2 customers who should be treated the same way the exact same way. And you don't have to write a single prompt. So that's what we see the difference between a Blueprint-architected solution and something that just uses the language models to try to candidly cut corners from my opinion and avoid the advanced preparation. When -- the advanced preparation is important if you want a predictable business, which the customers we deal with generally want a level of predictability, I'd say.

So best practices in the design time, and you have an advantage to do that because of the history that you have.

Well, that's where the 40 years and all the gyrations around understanding workflows and rules, which is the heritage of this business, we've been able to put that into Blueprint. So it's not just using the language model and saying, reason it out. It's saying, hey, this is the way to think about a workflow. This is the way you think of stages and steps and how you think about the personas who might be involved and what they're allowed to do and what they're not allowed to do. And all of those elements with Blueprint makes visible and allows you to curate. All of those come from our history and our IP and our agents, which represent what Blueprint is using to actually do this at design time.

Maybe help us understand it through an example of a customer that might be using either agentic or nonagentic kind of an AI based on Blueprint.

Yes. So Blueprint is -- so the trouble with the word agent and agentic and whatever is they're getting used all over the place in so many ways. Blueprint itself is an agent in that it uses language models that can run in a variety of ways. You can just e-mail it something and be able to figure out what to do with it. But I'll give you a real-life use case of somebody who's actually going to talk at PegaWorld. One of our customers, great customers is a big SAP customer, Mondelez, and they wanted to create a master data management system. And that master data management system sits in front of SAP, and it makes it so you can record changes to your suppliers and to your products and all the different things that they need to put into SAP but is not very attractive to put into SAP. And it certainly doesn't have the right sorts of controls and ability to let lots of different channels do it. By being able to create models and blueprints of this stuff, customers are able to build, to design, build and then continue to optimize their workflows, but still the comfort of workflows even as they speed it up. So it takes the things a customer wants to do, makes it reliable, makes it predictable, stimulates them to think differently and then makes it highly efficient.

I see. So that was an MDM use case, you said?

Yes, that's master data management. That's -- MDM is a fine use case, but other use cases that customers -- remember, Blueprint is not a whole new product. Blueprint is just an addition to the Pega Infinity engine, the engine that powers all of the $1.5 billion worth a year of customers that we have. So this is not something that people have to worry about being new. The new part is how easy and how powerful it is at stimulating thought.

Would you say -- in your customer conversation and the live projects that you have today, would you say Blueprint is kind of starting to accelerate workload development on Pega at this point? Are you seeing that kind of flywheel, people creating Blueprint, putting into Pega, a live application goes into production and people start using it, that kind of flywheel starting to accelerate?

Well, Blueprint is pretty new. And when we first introduced it -- a year ago, actually, in June at PegaWorld, we showed Blueprint and we made it available. Blueprint is available on pega.com. So everybody can go use it and try it and see what it is. And we've been enhancing it every 1 to 2 weeks. Significant additions are made to Blueprint because it's a SaaS product sitting on pega.com attached to a Pegasystem there. And it doesn't require a license or anything to go ahead and do this. So we're getting an enormous uptake of people experimenting with this, trying it and then starting to really, really use it. In terms of the flywheel, I think the flywheel is coming, and we can see evidence, but it's still early in the grand scheme of things. We didn't really push this into our sales force until January as part of this year's kickoff.

Yes. So the example, that MDM use case that you gave is good, but you have also been talking about legacy transformation as a potential use case, right? Talk about -- is that resonating with customers? Are customers kind of starting to use Blueprint for legacy transformation?

Yes. So we've had the first several clients who have begun legacy transformation projects with us on the back of Blueprint. And it's super exciting because what Blueprint lets you do, and you can see this, is it lets you upload, say, documentation about an existing legacy system. So you can take the user manual, you can take the test examples, you can take screenshots, you can take schema definition of it. You just upload all of this information. We're also working with companies like Accenture and AWS to take their code analysis tools, and we'll feed in the output from those also into Blueprint. And then from all of this, you get the user input as to, hey, what do you want to be different? And then Blueprint grinds and grinds and grinds and creates the workflows, creates the schema for a cloud-native database to be created to hold the data for that application and creates all the other elements. Whether it's a conversational interface -- if you want a conversational interface or if you want a screen interface, it will actually generate all of those artifacts using the standard Pega capabilities that are, I think, very well respected. And I think legacy transformation is going to be a very, very important way for our customers to use Blueprint and also for our partners to come in and use Blueprint with their customers.

One of the biggest opportunities, as I kind of alluded to earlier, is the pace at which legacy transformation or digital transformation is happening is, quite frankly, very slow, right? I mean we are 15 years plus into this. And if you ask AWS, they'd say 10% to 12% of it is -- and maybe 80% being the target. So you're 1/8 of the way there or something like that. So I think one of the challenges is the amount of investment that is needed to get started on projects in the traditional model. You have to go out, you have to get a client to pick an app. You have to go through a lot of heavy, typically professional services with your teams, whiteboarding documents, mapping. You got to go find a solution, put together a prototype. And after that whole process, there's somewhat of a kind of a cost or energy fatigue that could happen because you could be years into a prototype and you've been -- things change. Then AI comes out, scrap that. Let's start with the next way of doing it. And I think what Blueprint is really targeted to do is to say, cut that all out as much as possible. And you turn that into -- I mean, hopefully, it's a 1-hour discussion, a 1-day, a 1-week, not a 1-year. And that helps to get the juices flowing on innovation to be able to pick those projects and get working. And by the way, if you go through an ideation process with 20 projects and you end up with 18 of them not really being worth it, great. That's a few hours of investment, a day of investment versus in the traditional way, that would have been hundreds of people for months to try to build the consensus to get -- so that to us is a really big opportunity that helps our clients move faster on digital transformation. Most of the applications that need to be digitally transformed are workflow-based applications. They're processing some level of activity through a series of steps and stages. And I think that because of that, it's very relevant for Blueprint and Pega to help our clients pick the ones that are most important to move. And they likely are going to move to the cloud, which then gets the advantages of AI, getting off legacy technology and really reimagining the experience, all that kind of bundled into Blueprint.

Yes. I want to ask you about the last mile, right? Blueprint gets you to certain part of the process, right? It helps you with the schema, the personas, the steps and all that stuff. It spits out a file and then you kind of put it into Infinity, right? So from that point onward, what does that like last-mile effort look like from that point to like go-live application?

Well, look, I spoke to my users about it at PegaWorld. And I told them with what we had created, I believe we had reduced that last mile, the total effort here by more than 50%. And I haven't had any come back to me and tell me I was wrong. I think we can do more, and we're actively working on doing more. But what's exciting is not just that you can do the legacy transformation, it's how good the AI and our experience is at making that a better system. Lots of these are old -- just working with an old 3270 mainframe system, God forbid. These do critical things for companies. And they're not just ugly and hard to use and impossible to maintain. They're really confusing. And when you're able to turn that in to, hey, what are the data structures here? And what are the workflows that update these data structures and control them? You can put security on that. You can open it up to different channels like the Internet. You suddenly get whole different ways that this transformed application is not just replatformed, but it's really rethought. And that's how we are describing it. We want you to rethink and replace the legacy systems at a pace that you would not have believed possible.

I was just going to add one thing. I also think that something that is a subtle difference that Blueprint enforces is this level of prescription and structure that happens early in the process that can be leveraged later in the process. So the last mile, as you talked about, we really want to try to take the art out of actually redesigning applications because there's a best practice way to approach things. And the more that it is unique and bespoke, the less likely that you can leverage new technologies, that you can keep those applications current, that you're doing it in a way that you know they'll scale. And so that's one of the real challenges with enterprise scale applications over the decades is there was too much art put into those applications that made them difficult to keep current.

And we were, frankly, guilty and complicit in perhaps encouraging people to be a little too creative at times in places where we now actually, particularly with the power of AI and the best practices being able to be built into the Blueprint agent, being able to have it like tell you the right way to do most things. Gets rid of a lot of the degrees of freedom that historically have been candidly when problems occur. They're very often where somebody has gone off the path. And it's much better to keep them on them. So it's -- I think it has long-term ramifications for our long-term engagement with our clients also.

So tremendous kind of uptake of Blueprint. I think you had said 1,000 blueprints a week or something like that in the earnings call, I believe, right? But at this point, how many are live? How many have gone through that last mile at this point, would you say?

I still say we're in single digits. But the number that are in process is many times that. So you're going to see more and more and more and more. But let's face it, it's quite new. And as with all AI things, there are a lot of people who like to poke at it. Getting people to really adopt it and take it live, that for me also is really what the test of this is.

And I think another measure of -- maybe of momentum or progress is when you think about the -- how many -- how evident is the value in Blueprint and how adopted is Blueprint and how -- we start with what does every sales discussion for a new solution start with at Pega? It starts with Blueprint. And so that started in January, kind of toward the end of January. So we believe that everything that will actually happen with Pega will be driven or influenced by Blueprint. It's just a matter of the gestation period to maturity.

So let me go to Q1 results now, right? And I had heard something like 25% to 50% of the deals you closed in Q1 were Blueprint -- was involved in some ways. Is that right?

Yes. But what we meant was in the deals that were closed in Q1, Blueprint was used in some way in the selling process.

In a genuine way. And every customer who buys these days has seen Blueprint because that's what represents the future of what they'll be doing. So I would say 100% of the deals had people who had seen Blueprint. What we're talking about where was Blueprint a central element of how we work with the customer during selling.

Why would you say -- let's say, 50%. Why would you say the rest 50% -- why is Blueprint -- it's part of the discussion, but it's not driving...

It would have been because the conversation started in October when Blueprint was not as mature or the salesperson was not as comfortable.

Or -- and another scenario is a scenario where the client may have expanded their commitment on an existing application that was built. That necessarily wouldn't be a design process happening there. Those are in that -- in the other percent, yes.

Yes. So obviously, Pega Cloud accelerated in Q1 ARR on constant currency. Talk about -- what is the driver? I mean Blueprint, how much of -- it seems like it's a major driver. But how much of that acceleration was also driven by kind of the go-to-market changes that you have put in place earlier or several quarters ago now? Talk about the drivers of that.

Well, I think one of the biggest -- one of the best things that we did in the last few quarters was to really lead around Pega Cloud. Pega Cloud is our solution that we go to market with. That is -- it's not to say that we don't have cloud choice when clients need it, and that will happen from time to time. But our sales teams, our price list, everything is Pega Cloud. So you start with Pega Cloud, Blueprint or not. Take Blueprint out. Act like Blueprint never happened and just talk about the sales transformation for a second. We went through a very significant sales transformation about 1.5 years ago, where we focused on sales cadence, the muscle around the sales process, the way that we engage, focusing on the right organizations with a very structured and consistent way of managing. We're using the MEDDPICC process, right, in our selling process, which is an enterprise kind of approach. That tied with Pega Cloud being our lead, obviously, is going to help lead us to higher Pega Cloud in terms of new bookings. And there's a massive focus now with Blueprint on our solution consultants and our sales teams looking for new work, new workloads, not just expanding the existing applications that our clients have invested in with Pega, but new transformation opportunities, whether that be a new use case that they've never done before, whether that be a transformation of a use case that they -- may have existed on one or more legacy systems. So there's been this confluence pendulum around the operating model really anchoring, introducing Blueprint, Pega Cloud being our lead and us focusing tremendously on new ways that we can expand our relationships with our clients, which tie to the contracting mechanism that we deployed, which is we call adaptive subscription, which is a way of making it flexible for clients to start and scale. It's really -- think about it as more of a usage-based approach so that clients can get started and scale without having a lot of the contractual hurdles that might exist in the traditional way of selling licenses.

I have not heard adaptive subscription before from Pega. Can you double-click on that? Is that more of a flexible licensing term? Is that...

Yes. It's -- cases are very common measurement in Pega, usage-based measure. It's a way for our clients to have the flexibility to adapt their relationship with Pega, get started without necessarily knowing what their volumes are going to be and not going through a legal and contracting process because they have that agreement in place already. So it is very much -- and other enterprise software companies use something similar. I mean AWS and GCP and Azure have essentially an adaptive subscription model with their usage on as hyperscalers. So it's analogous to that.

So on that point then, maybe it's because of go-to -- go-live timing. But there is a delay between ACV growth on cloud and then revenue kind of at this point at least, right?

Yes.

Is that mainly because of the go-live timing? Or what does that...

It's a combination of a few things. Sometimes it relates to go-live. Sometimes it relates to when -- if a client is actually doing a transformation and the time that it might take to actually go live, get the system. It could also be some of the redundancy that happens if they're running an on-premise application as they migrate to Pega Cloud. There's a lot of components. The simplest way to think about it is when we book ACV, the revenue typically happens 2 to 3 quarters after that. So if you're -- and that's important to understand because many times, the models that we put together in the investment community is you look at the ACV and you kind of multiply that or divide that by 4 for the next quarter and you say, that's my revenue for the quarter. And our model, typically, that delays by about 180 days or so. So that's just something that's -- that's not -- we're not the only company that, that's the case. But I think an easy way to think about it is just in that 2 to 3 quarter range.

Let's pivot quickly to macro. It seems like you're not really seeing any negative macro impacts at this point. You said something like you're seeing high level -- extremely high level of engagement with your customers. Maybe talk about those customer conversations. And Alan, you have seen many cycles. What is your kind of gut feeling in this cycle in the second half?

I think that the uncertainty period we went through was among the greatest that I have seen. And hopefully, it's quiescing a bit. We've got some good tools to work with clients and make them a bit reassured. Cloud choice, for example, is -- for some of our European customers who occasionally have been having, I think, not rational, but not entirely justified panics about working with U.S. software companies, we, for example, have -- dealing with them, we say, look, you're running on Pega Cloud. You can run on Pega Cloud. Any time you want, you can pick it up and you can run it yourself with cloud choice. All of your data is encrypted with your encryption key. So we can't even see it. You don't have to worry about us being ordered to turn your data over. Not only won't we do it, it's impossible. It would all be gibberish. And so having these answers given our architecture, I think, has enabled us to quiesce some of the macro conversations. The other thing is that people are very interested in saving money, and that's good for us. So we've always done well in recessions.

I think the thing that is -- the one thing that's happening, whether we enter a recession or we don't, there's always going to be a push for efficiency, for trying to do more work with less people, right? And that -- and the entire push on DOGE was largely around trying to figure out how to do less with more, trying to get efficiency. That is our value proposition. That is the value proposition of actually automating work using workflow system to be able to streamline and save the human steps. By the way, that's the gen AI value proposition too as well, right? So the confluence of or the convergence of gen AI on a platform like Pega with a tool like Blueprint to be able to streamline and automate both the design and the actual running of the application, I think there is never going to be a shortage of companies that want to try to get that value. It's just a matter of their capacity at different points in the economic cycle.

Yes. The other thing I'll say is that relative to some of the DOGE and other sorts of things, we stopped many years ago selling user-based licenses. We sell licenses based on a quantity of work, right? And the reason we were doing that is we routinely automate a customer, reduce their staff by 30% or 40%, and then suddenly they had excess users. And that really didn't sound very good. And so we didn't have the problem that a lot of companies had where they looked and saw that there were a lot more licenses than people at certain government organizations. So I'm quite happy that -- that was a good decision made a number of years ago.

And it's very logical for our clients to say that the more that the system automates work, the more value they get, the more value we should share in that. I mean it's a very -- it's not a stretch to say if the system is doing more work, we should receive more value as the vendor.

Yes. Let me see if anybody in the audience has questions. No. What -- I completely understand your point, but federal exposure, have you disclosed that publicly?

We are -- our U.S. federal, both civilian and public, is kind of high single digits.

Yes, high single digits. I want to ask you your -- Ken, Q1 performance on ACV has been tremendous. And if we look at the guidance -- and you don't change guidance once you give it, I understand that. But it's somewhere around $165 million that you have to add to kind of hit that 12% number, right? And you've already -- I think Q1 was like a $74 million addition or something like that. So it does seem like there's a chance for you to exceed that number. But at the same time, when I look at the kind of the model, I think Q2 and Q3 looks like a little bit of a tougher comps for you. So maybe talk about that dynamic. How do you feel about the rest of the quarter? And should we expect growth to dip a bit and then maybe take up towards the end of the year?

Sure. So full disclosure, our Q1 was more like $61 million constant currency. And so your $165 million or approx was fair. So just in full disclosure, $74 million was -- we had some currency tailwind. So $61 million was a great start. So we were kind of originally thinking we were going to do $35 million to $40 million. So $61 million is a great start. Last year, the shape of our bookings curve was unusual compared to any other year. Q2 and Q3, it was almost Q1 through Q4 were all almost about the same. Q4 was slightly more. That is unusual for enterprise software in general. I think all of you that know enterprise software would know that Q4s typically tend to be larger because they're buying -- they're at the end of the buying cycle. Salespeople have accelerators. There's lots of like pressures. You have a lot of renewals in that time period. So you -- so last year, that just was not the case. This year, we guided that Q4 was going to be a more normal, like higher quarter. And then Q2 and Q3 were going to be more like the traditional seasonality cycle. And then Q1, we felt like we would start off kind of a little better than we did last year. So there's -- we're 1 quarter in, and the only thing that's happened is we started off Q1 better than we thought. But we still -- there's nothing that's changed in our business. And we do have visibility of our pipe in terms of the timing and the shape. So we -- that typically -- that doesn't change dramatically, so the visibility. So this year looks more like a traditional year with Q4 being a little higher and Q2 and Q3 being more subdued.

We have 20 seconds. I would just want to ask you, cash flow has been tremendous for Pega. You've made a $200 million a quarter, I believe. Talk about -- is there more juice left on free cash flow? How should we think about kind of the room left for -- in that metric?

Our focus -- now that we've completed the subscription transition, optimized our sales team, we have Blueprint in front of us, and we've got our free cash flow levels, let's just call it, at the 30-ish percent range, if you kind of normalize the business, there is not a better time for us to be thoughtful around how we expand our selling capacity to increase our growth rate and still expand margins. So I think our business is really built now to be able to expand margins and grow. We were not in that situation ever in our history before. So this is maybe the first time that we feel like we can really swing at both.

That's a great position. Thank you so much for taking the time.

Thank you.

Thank you.