Okay. Hello, everyone. I'm Pinjalim Bora, SMID-cap software analyst at JP Morgan. Welcome to the conference. I'm delighted to have here Ken Stillwell, CEO and CFO of Pegasystems. Ken, welcome to the conference. Thanks, Pinjalim. Maybe you can start with just a brief introduction about yourself and maybe a few lines on Pegasystems for people who don't know about the company. Sure. I'll hit on a couple thoughts. Pegasystems has been around for a number of years. We started off as, I would say, an alternative to custom code development for applications. What we landed on was, you know. Or kind of earlier in our history, we landed on this concept of process, workflow and process, and helping companies execute certain activities that might happen at scale. Typically, something that wasn't an application that you would typically be able to buy kind of off the shelf. It wasn't. We didn't focus on ERP use cases, but we typically focused on adjacencies to ERP use cases. We then kind of, matured to create a case management structure and then had a series of acquisitions that helped us in areas like robotics and mobile and social and process mining and data analytics, Customer Decision Hub, which was, which essentially was our version of AI, you know, 15 years ago, which actually helped us with a lot of our differentiation around things like Next-Best-Action, Next- Best- Offer, which what those are ways that Pega can take the information that we know about, transactions around the workflow and around other data that might be available to the application and serve up things like, "What should I do with this customer? What should I do with this person that hit a URL or website? What offer should I give them? About... When I started at the company about seven years ago, we were a largely perpetual-based software company. Which was not dissimilar to other software companies. We were probably a little late to the moving to a SaaS solution. The reason why we were typically behind is because we sold to large enterprise companies who actually moved to the cloud in general later than smaller organizations that had a little bit more ability to go cloud native. We've made that shift, went through a subscription transition about five years ago. We've moved to SaaS. Right now our business is now all recurring. Our SaaS solution we call Pega Cloud is the fastest-growing and now about 50% of our ARR. We've made quite the transition over the last five years to moving from an on-premise, you know, typically perpetual license business to a Pega Cloud SaaS, business that sells typically, on a volume or consumption-based model. Yeah. That's, that's quite an evolution. I guess, you know, as we think through this, right, you started in, as you were saying, in the, let's call it like a digital process automation platform. Over time you have kind of productized a few things like the Customer Decision Hub, the customer engagement, I think you call it. Mm-hmm. The customer support side of the things as well. You have productized some applications. Help us understand kind of the mix between that platform and the applications. Is there a part which is kind of strongest in the portfolio that is resonating well with customers versus some of the things that might be coming up the curve? Sure. What you're really referring to is the evolution of how we learned about the common use cases that we supported with our clients. When we saw use cases that were very similar, The first step in that was to create common implementation frameworks, as we call them. you know, probably going back 15 years or so ago, we actually started to see very common trends. Like customers wanna use it for a digital contact center, digital customers for CSRs to interact in, you know, in a screen where you would be able to interact and interface with other applications, pull things together, serve up the next... As we started to see, well, let's not... Why would we wanna build each one of those custom? There are components of that we would productize. That's an example where we went from 0% out of the box to maybe 70% or 75% out of the box, and you would kind of configure that last mile. Another example is our customers, our one-to-one customer engagement, as you mentioned, which is really a marketing automation solution where clients, for an example, if you have a credit card company where prospects and clients are coming into a website, you wanna be able to know who they are, where they're coming from, what their history is, and what you should do. Should you offer them a new credit card or they already have three credit cards? Really what you wanna do is connect them to the rewards site. Do you wanna throw a video up that helps educate them on actually how they can deal with, you know, the digital contact center? Those are examples of very repeatable use cases. If you look across our business and you say, "Well, what do you sell now? Like, is, do you sell more, you know, custom digital process automation, where every use case is different? Do you sell kind of out of the box where, you know, it's like shrink wrap software, right? Do you buy staples?" We're clearly neither of those. We do have some situations where clients will leverage the Pega platform for a more customized use case. I would say that is very much in the minority now. There are a handful of use cases that clients, you know, tend to be more common use cases. Things like think about managing events, managing issues, managing transactions. Things like onboarding a new customer, changes that happen to customer information, issues, disputes, resolution. Things like a process like I always use the loan origination process, where you have, you know, where it might seem very simple if we say, "Well, how do I originate a loan?" You might say, "Oh, well, you have an application, and then you fund the loan." Well, no, there's 17, 18 steps and 15 different systems that need to be managed through that. By the way, heavily compliance and regulatory environment, so you need that structure. You think about scale companies, scale transactions, you wanna automate as much as possible. You wanna get human interaction, which is very expensive on the customer service side, and very poor from an NPS score on the consumer side. Consumers don't want to interact with a human. They wanna be able to do things very quickly. What Pega's really differentiated on is that fast end-to-end work automation of any type of process, activity, issue, resolution that's gonna happen that isn't kind of an open close, like a simple use case. Like, if you wanted to schedule a, you know, if you wanted to go in and schedule a haircut, and you went in and said, "I wanna pick this time," I mean, can Pega do that? Of course we can. Is that how we differentiate? No. When you wanna go in and actually execute, you know, you wanna go in and add a child to a cellphone plan and change the plan, and there's all variables 'cause you might need a device, et cetera, then that's a sweet spot. Yeah. It's pretty broad overall, right? When investors think about Pega, they struggle a little bit about who does Pega compete with? Is that the BPM players, the digital process automation players, or is it, you know, Microsoft's CRM, Salesforce CRM, you know, those kind of guys? How would you kind of characterize the competitive landscape? It's interesting because, if you asked me this 10 years ago, I would've differentiated between those two things, but I think they're all the same now, right? If you go talk to or look at the messaging for, you know, say Salesforce or Microsoft selling to enterprise clients, they say they do process management. They say that. I don't think that there is a, you know, if you look at the enterprise space, maybe that's the way to differentiate it. If you kind of do the pyramid of very large companies, mid-size companies, and small businesses, we would compete typically at the top of the pyramid, which all the names that you mentioned compete there as well. We're not gonna compete with off-the-shelf commoditized applications as much. You will still see that happen from time to time. We're competing with, if you look at the list of, you know, Microsoft and Salesforce and ServiceNow and Adobe, and, you know, all the players that have enterprise platforms. Where we really differentiate against any of them is the depth, breadth of our platform and the change management aspect of our platform. That we use a model approach, we don't write code, which means that you can change the application in the UI. You can decide you wanna have an evolution. I wanna add a step, take out a step, add a stage to a step. Things that you can do where you don't need to have, you know, a Java developer do that, or you don't have to have someone that knows the proprietary language of some of our competitors. That's a very big differentiator, which is our enterprise clients love the breadth of use cases, the flexibility of, as we call it, future-proofing. Once an application is live, being able to actually iterate and change. Because naturally, the, you know, the, you know, the requirements of any application change. Yeah. The low-code/no-code aspect of it is definitely interesting. Before I go there, you know, generative AI is a big topic nowadays, and I know Pega is one of the companies who actually outlined a few things that are, I guess, coming down the pike. I think I read Q3, Q2, Q3 in one of the press release that, you know, you're releasing a few things that might be coming out. Yeah. Talk about how are you thinking about generative AI, across kind of the product set. What is it going to enable Pega customers? Sure. You know, it... What is interesting is that, if you go back through, if you did a search through, press releases of Pega, you'd see us talking about AI in, like, 2006. In fact, we stopped talking about AI because it had such a bad, like, kind of 1984 tone to it, like, of like, you know, people are gonna be looking over you. You can't have AI. You can't talk about artificial intelligence 'cause people will be threatened by it. We kind of actually toned down, and we started talking about our own framework, which was our Customer Decision Hub, which is our AI engine. Just to help clarify, we have Pega... The way that Pega operates is there's a series of rules that you can establish. What is a rule? It's like an if-then statement, right? You say, "If this happens, do this." The combination of all of those rules, you transact, and you see information, and you see what happens, and you learn from that information. Our application has the ability to not only establish a set of decision criteria that would say if-then, it also has the ability to learn from the transactions and make suggestions on how to change the rule set, how to evolve the intelligence engine. That, that was what our version of AI back, you know, 10, 20 years ago. I think the when you think about what AI, what we've seen now in the last, you know, would seems like just a few months. Yeah. Right? Where we've actually the use cases that we see are tremendously complementary to our, one of our core differentiators, which is our ability to offer up decisions, to offer up the Next Best Offer, Next-Best-Action. What should you do? What should the system do? The limit that we had without generative AI is that we're really confined by the information that is resident within the Pega system, which we have a lot of data, but we don't have all the enterprise data. Now you plug that into an AI engine, by the way, any AI engine, right? We're not gonna be captive to one. Any AI engine, you're able to cascade across every data lake, any piece of information, whatever you wanna define that to be, to be able to be that much more educated with that. Things like, you know, we're running some tests, and I won't share too much because we have PegaWorld in a couple of weeks, and I would ask everyone to tune into that because I think you'll see some pretty awesome examples of how AI, how we're thinking about generative AI. Just to give you a couple teasers, one of the examples we have is we actually have an AI chatbot that's established with inside our internal communication channels, like if you think about like Webex and Teams. Essentially, you can ask it anything you want. You can say, "Can you write a note to a prospect coming to PegaWorld that's tight on budget, that has a data science need, and which session should they?" It'll draft a basically note, two seconds, right? That's Imagine that in a customer service? Imagine, "What should I say to this customer? What language should I speak in?" Now take the customer service personnel and make it a chatbot. It's just tremendous. That's a, that's a really valuable and interesting use case. Another interesting use case is if you any enterprise platform, and I don't know how much people would, how much of our competitors or even our some of our partners would actually acknowledge this, but it is challenging to deploy enterprise scale applications. It's not something that you just hit click, you know, go install, right? There is time and effort that's take. Once you deploy it, you have to make iterative changes. What AI can do is speed up the implementation, speed up the change management process. I think that that gives the power of enterprise platforms to a much different segment of the population. It actually almost can take it down market, right? Because the barrier to entry for companies that have smaller scale volume, you don't have that. Like, you know, I have to do an implementation plan. You can actually speed that up, and it should make our partners incredibly more efficient with managing that change. Yeah. Interesting. How much of those, newer capabilities, I guess, the Customer Decision Hub was already there in your Client Cloud as well? Yes. Right? Some of these generative features that you're adding, would that be in the Client Cloud as well? Or would that be mainly in the Pega Cloud? Great question. Pega Cloud and Client Cloud. We have two. The way we frame it is Pega Cloud is our managed service. That's our SaaS offering where we manage everything. Client Cloud is the exact same technology stack, but the client manages on the cloud of their choice. They can manage it on AWS or Google or Azure or servers if they wanted to. They can manage it in any environment they want. The way that our architecture is a microservices-based architecture, which means that you can externalize services or you can embed services. Inside what Pega does, you can actually have like a search engine that runs within Pega, or you can have a search engine that runs outside Pega. Think about AI now. You can actually embed the AI in Pega, is our Pega Customer Decision Hub, or you can actually integrate with an AI, with a generative AI tool outside. Essentially with an integration. If you're in Pega Cloud, you can actually embed an AI tool. I think that will be less common, and I think what will be common is that you're leveraging an external AI tool, either something that's managed in a SaaS environment, or it's managed by the client inside some virtual private cloud. I think it's very, we're very flexible, and you can pick which one. You can change. You can use multiple ones. Our, and then I think that's, you know, probably not a, not shocking to think that we don't wanna tie ourselves to any AI engine, given that there are so many and you don't know who's gonna win and who's gonna have better tools for different use cases. Yeah. Where I was going with that question was. I was thinking if you are offering more of these generative capabilities on the managed SaaS offering, would that be kind of a forcing function to go more cloud or Pega Cloud versus Client Cloud? It seems like it might be in both the places. I think which cloud you pick is really dependent on the customer specific. For example, if the customer has, is leveraging Pega to integrate with a lot of applications that may actually be inside their own virtual private cloud, they might lean them to more look at Client Cloud. If they're actually having us integrate with applications that may be third-party clouds anyway, they would probably want Pega Cloud. I think it really depends on the use case, where the data is. For example, in some cases, you have to manage the data with inside certain countries. That would lead them to have Pega Cloud and have us manage it with inside that specific zone that we're in. Really it's a... That's why we've chosen cloud choice, because we just know that clients, you know, can't just be given one option because their, you know, their requirements are more sophisticated than that. Yeah. I wanna go back to one statement that Alan made in the earnings call. I think he around generative AI. He said something like he thinks low-end low-code/no-code platforms would be commoditized. He said higher-end enterprise-grade solutions like Pega will benefit. Can you make that distinction? Why would that be? What I think Alan is connecting is there are use cases that are very, they're no-brainers for generative AI. If you think about what, you know, my view of generative AI is the two of the things that it helps the most is it speeds up something that a human would otherwise do, and hopefully increases the decision quality of something that a human would do. If it does those 2 things, I'm sure it will do others, but if it just starts with... Simple low-code, open close, simple use cases that you wouldn't otherwise wanna write code for that simple use case, you might actually have an alternative to that. I think that things like screen scraping, things like low-end low-code where the use case is really simple, like I just need an application that tracks badge usage, you know, who walks in and out of a door. It would give you another option. Doesn't mean that it would completely, it wouldn't change the value of low-code or no-code, but it just, it would give you another option. On the enterprise grade, AI doesn't solve those use cases. AI doesn't. You don't say to AI, "Hey, build an application that integrates with 72 different feeds, and I'd like you to set up the workflow to be compliant in these six countries, but deal with the conflict between the regulatory..." I mean, like how would you even? Like I can't even envision. Yeah ... a scenario of that. What it can do though, is it can say, "You've looked at the configuration of my enterprise application. Identify the bottlenecks. Tell me where you think those bottlenecks could be mitigated, and what would be the changes that we would need to do to that application, and present those to me." That then a developer could say, "I like that one. I don't like that one. This one has this unintended risk." That's where I think it could be helpful. Yep. Yep. Understood. Okay. One last on AI, I guess. Another thing that kind of a little bit surprised in the earnings call last time, I think you said vast majority of your licenses or contracts today are outcome based or value based versus seat-based. Because there is this debate around as productivity increases because of, you know, as companies kind of drive AI usage within their products, that might put pressure on the number of seats if you're, it's a seat-based model. Seems like for you guys, it's, you have already kind of made the jump with vast majority of your license contracts not being seat-based. Is there a way to understand what does that mix look like? Is that 75% value based, more or less? Sure. maybe just a little connection of how did we get there, and then I'll answer your question. Sure ... about the percentage. There was an interesting conversation that I had with Alan Trefler, who's our Founder and CEO, where I said, "You know, this business is ripe for being a SaaS-based recurring business. We should not be selling perpetual licenses. We're actually." At that time, we were selling about 2/3 to 75% of our deals were perpetual license. Remember, this was 2016, right? This wasn't 2005. This is. Alan's point was, "Yes, I think you're right, but how do you make that transition? And our clients probably wanna buy perpetual licenses." Almost like the, you know, we were kind of, we were almost validating our own view by speculating how people wanted to buy. What the other side of that was, I said that I observed that we were really on the forefront of moving away from user-based licenses. I mean, we were moving away from user-based licenses in 2006, 2007, 2008, and 2009 because we knew that the whole value proposition of Pega is to reduce the number of CSRs, not to increase them. A user-based license makes no sense when you're actually selling to a client, you want to reduce the. Consumers were going to start coming in as users, and you don't want to pay the price for a consumer, like a consumer license versus a customer service rep license. How do you. We basically went to our clients, you know, decades ago, literally, and said, "You need to stop this user-based stuff. You need to base, buy based on the amount of activity that the system does. As you have more activity, naturally your price per activity measure goes down. Any activity the system does is a deflection away from a human. Clients bought into that really significantly. Alan and I connected those two themes. If we're gonna have an activity-based license, why would you sell perpetual, right? Why wouldn't you actually have it be? We first took the move to move to recurring. Now, recently we've moved to a more consumption-based model, where if you think about, like, I'll just use AWS as an example. If you think about the way AWS licenses, they basically say, "Here's our price per unit, and you get two discounts: how much you spend in a year and how many years you commit." Essentially, the more you commit, the more you're pricing. We're not that dissimilar to that. We basically tell clients, "Listen, you, we're gonna help you deflect all kinds of activity away from CSRs, and we're gonna speed it up, increase the NPS. Customers are gonna love it because they're gonna be able to go in and your teams are gonna be able to scale more customers without actually scaling people, not having to worry about processing centers with thousands of people." We connected those two themes. To answer the question that was behind that, our estimate is that we have less than 25% of our contracts that are solely a user-based contract. Some have a little of both. That was, you know, that's up from if you go back, you know, years and years, probably 100%. I would also tell you that what we're doing is not dissimilar to what a lot of our competitors have been doing. They've been moving away from user-based licenses as well. I, so I just think there was a... Just like it was hard to get people to cloud, and, you know, you'd have countries that would say, "Never, we're not moving." I mean, even this conference talked five years or six years ago about, "No way, we will never go to cloud. Yeah. Now look where we are, right? I think that we all learn. I think that what we've learned is clients want flexibility. They want you to manage it as much as possible, and they don't wanna have to do this massive shelf where pre-buy, which is essentially what users end up being. It's just another form of perpetual license. Can I double click? Yep. ... on the consumption part that. Yes ... talked about recently? Can you elaborate on that a little bit? Sure. you, like, as an example of how that works? yeah. I mean, how that model has changed prior to previous. What is there a change in rev rec? What we used to do was we used to sell. Let's go through the evolution. We sell, we say, "You have 200 users. You're gonna pay us this much per month, per year," whatever the rate is. We move from the 200 users to, "We're gonna actually give you a four-year, five-year contract based on a certain amount of volume per year." Why does that second model, what's different? Well, first of all, you get off of users, you get to outcome-based. The second thing that happens with that model, though, is you give clients a hurdle to adopting new applications and use cases because they have a contract. The contract is fixed, the purpose clause is fixed. If they want to roll out, say, a new use case for Pega, they've got to go to procurement. You know, business users do not wanna go to procurement. They don't wanna open up a contract, they don't wanna. It ends up being a lot of friction. What we did was we basically said, "Listen, you can have a three, four, five-year, whatever contract length you wanna commit to, but inside that duration, you can deploy any new application you want, and all it does is trigger to your usage." We even have been flexible with clients to say, "Wait till you go live. We'll let them kind of almost giving them an incentive to say, "I don't have to pay anything under this contract for a certain period of time." The contract ends up being, having the flexibility of scaling up in usage. Naturally, you have to still get the higher spend approved, but that's a much different contracting element 'cause all you need is budget for that. You don't have to go through an actual legal procurement process. We found that clients love the flexibility, and it doesn't cost them anything. Yeah ... to do that. Interesting. Okay. One question on macro, which is obviously topical, nowadays. I'm sure you have spoken to a lot of customers since you reported earnings, but what is your sense of the kind of the macro environment at this point? You know, how would you characterize kind... the demand environment or, the business confidence, today? It's interesting. You know, this is always one of those things where you have to, like, try to separate, like, objectively what you see versus what you philosophically believe versus, you know, like. What I would say is that, if you look at enterprise buyers, they are... The biggest disruption that we're seeing right now with our enterprise buyers is this confusion around generative AI, for sure. They don't know what it means. They're trying to figure it out, like, what's... Like, they don't wanna be behind. You know, like, they're testing it out. Take that aside, the buying environment in the enterprise space, I think, has been relatively stable over the last couple of years. I actually think it was worse at the beginning of COVID than it is right now because of the uncertainty that COVID provided. I think you know, large clients, you know, like JP Morgan, they know what they have to get done over the next few years, right? They know what's important. They know which applications have security vulnerabilities. They know what use cases, they know the scale, they know the employee problems that they have. I think that has been relatively consistent. When you start to go to smaller companies, and I say smaller, I don't mean like mom-and-pop shops. I mean, like, when you start to go from the top 10 in every industry down, you do have, I think, concerns with companies that are highly leveraged, that are not generating profitability. They have a little bit. We don't have a ton of those, but we have a few of those. You can kinda see them being a little bit more focused on improving profitability and maybe even doing some things that might not be smart long term, but they kinda maybe don't have a choice. You step over to the next big uncertainty, I think is self-inflicted. It's, you know, it's the debt ceiling debate things. It's things that, like, we do not have to have these. You know, they're unintentional distractions. I think if you take away some of the self-inflicted, kind of political kind of distractions that we unfortunately have globally, but seemingly more now than 10 years ago, and then the second part of it is this, like, new technology. If you take away those 2 distractions, I actually think the underlying activity we've seen at clients is relatively healthy. Now, I know I've just said 2 really big things, but like, I don't think there's, like, a structural problem. I think it's much more of a, you know, there's some self-inflicted stuff that we're doing. Hopefully we get through that, right? The inflation, by the way, one last point on inflation seems to be moderating in our client base. If you look at annual increases, if you look at things like, you know, we've started to see those numbers kinda, stabilize, I would say, and maybe even start to tweak down a little bit. Okay. I'd conclude that with consistent versus Q1, as, at this point, I guess. Not any worse. Okay. Not any worse. Not any worse. Okay. I guess if you have questions, please raise your hands. I think we have mics. Can we get some mics here? I think there's someone right here. Two up here. Mm-hmm. Hi. Ken, a couple of questions. One is, how big is your international business? And in particular, how are the large markets like Germany or Japan? We have a probably not a dissimilar split of 60% Americas, 30% EMEA, 10% APAC. Not that dissimilar to other enterprise. Japan is not a huge market for us. I would say it has underperformed rest of world for the last few years, and I would say not much. We don't see a lot of change there. European markets seem to be doing a little better this year than they were in the past. I would say in general, the European markets have been very disappointing in terms of performance probably the last five years in terms of it's really we had much more growth from the Americas than we actually have outside, that's currency adjusted. I would say you are starting to see, it's surprisingly better given what's been happening in Eastern Europe with the Ukraine, Russia conflict. I think it's better now than it was a year ago. When you look at the numbers in your deck on the projections of the marketplace, I think two years out, you have yourself at a marketplace TAM of about $125 billion. Let's just assume you double or more than double where you are today. That only still gets you to about 2.5% to 3% of the marketplace. It doesn't make you an industry standard, and makes me wonder questions like, do you have to do something different in your commercial execution? Do you have to spend more money there? Do you have to get better at execution? Are you defining the market maybe too widely? Or the last one might be, do you need to be part of a bigger organization? I mean, I'm just, you know, start to lay out some questions about where you are because if you're not at that standard, you're this iterative purchase in the other per... you know, in a JP Morgan purchase cycle, so. Yeah, that's a really good question, actually, and a fair one too. What I think, the way that if you use round numbers and you say we're 1% market share and we wanna get to two, and just use those just to. That's a simple example. I think that we maybe over the last few years, we had over the last few years thought that we were gonna get there in a way that I don't think was possible in the near term, which was, let's go out and get a bunch of new logos, and let's actually go find new partners, and let's go into companies that we have typically not sold to. For us, the cycle between when you get a first deal and you scale that client to a number of millions of dollars takes some time. It doesn't happen in a year. It might happen in a five- or 10-year period. That's a long road. Versus if you go to the existing few hundred clients that already spend $1 million or more, that already know us, that already. We haven't even scratched the surface in the penetration in those clients like JPMorgan Chase. Right, where it's much easier to, I don't even see double. Like, if you have a $10 million client, just trying to add $2 million every year is much more achievable than going out and trying to find a new $2 million client and scale that one. The argument against that is, "Oh yes, but you'll be sold out in your organizations." I don't know. I don't know how we're sold out in JP Morgan Chase. I don't know how we're sold out in any of these, any of the peers. I think that we, yes, if we're getting $50 million to $100 million to $200 million from a client, which by the way, we are not right now, then I would say we start to get to a point where maybe you need to throttle your expectations. Most of our clients are between $1 million and $10 million a year. Every single one of those clients could be spending $25 million. On the focus one, we've absolutely shifted to focus on where we think the low-hanging fruit is. That said, our. We have to prove out our execution on that, because our execution has, you know, We just did that last year, we really need to just not be shifting our strategy all the time on that. That needs to anchor. In terms of whether being part of a larger organization or partnered with a larger organization would help, I think it would only help in the new logos. I think the existing logos, we actually have really good brand recognition. I don't think we really need it there. I think if you, if you went and talked to Lori Beer, and you said, "Do you know who Pega is?" I think she'd say, "Yes, we know who Pega is." I don't think that would help us. I think it would help us with new logos. I think right now our focus is the 500 or so organizations, maybe even quite less than that they should all be spending $10 million with us. That in of itself would give us room to double, triple, quadruple our business in the next X number of years. We don't even need to focus on anything else. No. No. Last 30 seconds. Seems like you're outperforming in free cash flow. How should we think about free cash flow for this company going forward? I think that, unfortunately, we went through a cloud transition where the numbers are all obfuscated on revenue. We knew we were gonna have to go from billing up front to billing over time. I mean, that was... We actually said that, we signaled it, but I still think it's tough to see. You know, you go from a company that's making money to seemingly losing money. Now we're coming back out the other side. Our free cash flow into... What we talked about guiding in the beginning of the year is more than we've ever generated in free cash flow in any year in the history of Pega. That's just the start. I actually think the biggest upside that I'm most optimistic about is our commitment as a company to generating increasing amounts of free cash flow as we exit the cloud transition. We're done with the cloud transition right now, so we don't have that overhang. I think where we are in 2023 is just the start. Okay. With that, thank you so much, Ken. Thanks, Pinjalim.