Happy to have the Chief Financial Officer, I'm gonna still say the relatively new Chief Financial Officer, from Appian, Serge Tanjga. Serge, thank you. Welcome back to the TMT conference, this time as the CFO of Appian. Good to be here. Awesome. I'm ready. Before we get into the conversation, let me just go through the disclosures. For important disclosures, please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. With that, maybe to kick off the conversation, you joined Appian in the middle of 2025 after spending, you know, over a decade at MongoDB. For those new to the story in terms of Appian, can you pinpoint the problem or problems Appian is solving for customers? Yes. Appian is a process automation platform that focuses on mission-critical use cases, especially in highly regulated industries. That's a mouthful of catchphrases, so maybe I thought I'd just make it real. Yeah. With a few examples. For example, one of the larger asset managers in the world, the one that has a lot of people running around these halls today, has automated a process to onboard and manage their customers on Appian. Before that, they were using largely a manual process, so this was a cost-saving and revenue growth exercise. A top Australian bank is using us for credit dispute, credit card dispute resolution, and they were replacing an internal app that was clunky, and it wasn't scaling. A medical equipment manufacturer that's using us from order to install process for their equipment, and they had a point solution from another vendor that also wasn't performing, so they replaced that at Appian. Since we are a big government player, a large civilian agency is using us for automating a process to identify and resolve fraud. Before that, they were doing manually while pulling information from multiple systems and obviously involving a tremendous amount of person-hours. If you take those examples and kind of boil it down, we work with large enterprises and the public sector to automate mission-critical processes that usually span across different silos of information inside the company or frequently involving the customer. We usually replace either manual effort, underperforming custom-built application or any number of legacy solutions. Mm-hmm. We've been in the business for over 25 years. We've got into roughly $100 million of revenue. We think it's a very exciting opportunity ahead of us. Yeah. I've been around for every single Appian quarter, and I think, you know, in your answer, I heard the word process... [crosstalk] Mm-hmm. Multiple times, I think there's still some of that lingering impact from when we did the IPO in 2017. Mm-hmm. before your time, around being a low-code platform. Mm-hmm. I think there's still a portion of the market that still thinks that Appian just builds, you know, low-code websites. Yeah. Those types of things, and not necessarily, tied to a process. Let me talk about that because as a relatively recent outsider turned insider, there was a moment where it sort of dawned on me on how wrong this is. Mm-hmm. What I mean by this is this idea that we're, you know, there's this low-code, no-code space, that over time has become associated with, call it a citizen developer who takes a few hours of training and then goes build something relatively rudimentary to help in the day-to-day job. That was what people in this room and myself before coming to Appian would have probably thought about. Then I realized almost all of our software is implemented by a third party, either ourselves or... [crosstalk] Mm-hmm. Any number of our partners, ESI, smaller companies, and so forth. The customers pay us from five to eight figures for these implementations. Once I kind of put that together, the reason why that realized to me is like, what we're doing is not easy. To implement and build the software on our platform actually requires, you know, expertise that most customers do not have. All but relatively small of our largest customers have. I think that, I think, puts the moniker low-code into perspective because it's low-code in the sense that, like, you're not hiring $250,000 developers and keeping them on your platform to build custom code for you. You're using a third party that implements a composable reusable solution. What we do is hard and very sticky, as you can see from our numbers. Yeah. let's dive into, 'cause that's not only the core debate with Appian, but core debate across software... [crosstalk] Mm-hmm. Is sort of defensibility in the age of AI and the risk of AI and disintermediation. When we look at, like from your customer conversations, what specific use cases or system requirements make customers conclude they need the Appian platform rather than building AI native automation solutions or working with one of the research labs to build their own sort of agentic autonomous solutions when it comes to automating their workflows? Yeah. Let's dive right in. You know, I've been in and around Wall Street for close to 25 years, and I say that Wall Street time and Main Street time, the clock ticks differently and sometimes completely differently and unrelated. I can't remember a time when there was a bigger dichotomy between investor conversations and actually what we hear from our customers. In rooms like this and in the room that I've been all day and going back to after this, there's questions about AI becoming self-sufficient and, you know, obviating the need for software, including Appian. There's a question about, you know, agents, you know, running other agents, reporting to sort of across different silos and enterprises, going to some things called control towers. New competitors are, you know, emerging to displace people like us that have been in the business for a long time. That's what I hear in investor meetings and kind of find myself discussing. Customers are in a completely different place. Customers are still looking, for the most part, for the first successful use case of AI in production. I don't mean give your employees a copilot or a tool that makes them productive, makes them write better emails. I'm actually talking about at scale with high accuracy inside a process that's, you know, runs thousands, if not millions of times a year. The reason why customers are struggling with that because AI is a, and I know you've learned this term now, but I'm gonna repeat it anyway, a probabilistic technology. Mm-hmm. That needs to be fit inside a deterministic system to produce the outcomes that is needed when you're doing something mission-critical like customer onboarding, like procurement, like budgeting, like the kind of stuff that Appian gets involved with. With them, the conversation is different. The conversation is, "I wanna see value. I believe in your vision in terms of delivering that value, meaning as AI as a node in the process as opposed to some replacement of the process. You guys have the credibility to do that because I've worked with you and my peers have worked with you for a long time, so let's partner together and do that." I'll give you an example. A North American insurance company who's approached us about doing the first in production case of our product called DocCenter, which is AI-enabled document extraction. Again, there are plenty of tools in the market, low accuracy. What we're doing inside a particular process is capable of getting to high nineties or better accuracy. We partner with them. First use case, 400,000 documents per year. It took us a couple of months roughly to implement it because, again, you wanna tune it such that it's accurate enough, and they're over the moon. We're talking about the second one. Mm-hmm. The second one is 1.2 million documents per year. Most customers are still before that first use case. When they are engaged and when they're ready to talk about AI adoption, we see our win rates being meaningfully higher than they are normally, and we're happy with our win rates as they are. Which again, speaks to our vision of AI as a process is an essential enabler of AI is really resonating with the customer market. What we're gonna see over time is more use cases, ability to upsell customers, and we generally think it's a great tailwind for our business. Yeah. When we think about, you know, one of the aspects about Appian as a business is 80% of your revenue, roughly 80% of your income, comes from like highly regulated industries where customers value compliance, audibility, reliability. When you think about what's gonna keep Appian defensible for the next several years, is it the governance framework? Is it your implementation domain expertise? Is it the support, or there's something more fundamental to how your platform is architected? Yes, you're correct. We operate in the most demanding, most highly regulated, most risk-averse industries that are out there, so 80% of our business comes from government, financial services, insurance, and healthcare. We have, again, a long history of subject matter expertise and individual solutions provided in that space. As you think about, sort of our framework around process generally, is that you wanna deploy a best tool at every node of the situation. Mm-hmm. Historically, those were, you know, business rules engines, then there were RPA bots, there was process mining. AI is another worker to drop into the process at the right moment, under the right circumstances. You certainly don't wanna use AI indiscriminately simply because it's not the best tool for the job. You wouldn't make AI do math, for example. We bring that framework to our customers, and then on top of that, we provide them with incremental functions like security, like auditability, like compliance and certifications, which frankly, you would not ask AI to create. Mm. That comes all in the context of complex workloads that need to have higher level of accuracy. Those are the things that we think are particularly difficult to for AI to ever replace. Yeah. Not just in any particular near-term moment in time, but generally speaking. Let me kind of take that to an extra credit level of answer. One of the things that I've heard in my meetings today, and there's generally speaking, is some flavor of, "Okay, I get it that this is a near-term positive for you guys. I get that AI fits in the process, but what gives you confidence that's gonna be true five, 10 years down the road?" That's always a difficult question to answer because it's hard to disprove a negative, particularly when the market seems to be as bearish and as scared as it is right now. I'll offer you two arguments. The first one is, I think implied in that question is some sort of capability of AI to become self-sufficient. No need, it's gonna self-govern. Fundamentally, as a probabilistic technology, it's just very, very difficult to imagine a world in which that happens. Mm-hmm. It always needs a set of guardrails and protections around it in order to deliver the outcomes that the enterprise want. The second question in this sort of, you know, infinite bearish sort of scenario is, okay, fine. AI needs that, but why can't another player, a new player, a new breed provide it? Then we're just talking about competition. Yeah. You know, the market's always been competitive. You know, what we do is exceptionally hard, which is why you see very, very few companies have succeeded and scaled versus many who have tried. If another competitor comes and needs to build that enterprise readiness, support, confidence from the customer, particularly in our verticals, I would flip the question. I would ask you, why wouldn't you logically avail yourself of all these tools, all of which are, you know, available, and we partner with all of them, to implement properly inside the process in a way that we've done it for a long time and generate value that way. Why reinvent the wheel? Mm-hmm. That makes a ton of sense. Let's talk a little bit about the AI monetization story at Appian. Understanding that's still pretty early, but on the last earnings call, you noted that AI usage on the platform is up 14x year-over-year. From a bigger picture perspective, what are the AI capabilities available to customers today, and how is that monetized? Yeah. I'll start with the framework, and then I'll walk you kind of through the progression. For us, even before GenAI became popular and became usable, we were implementing earlier versions of AI and ML as a node in our process. Obviously, when the GenAI opportunity became clear to the general public, we sort of rolled out a series of features with increased complexity to effectively deploy AI capabilities in the right way. First came a set of things that we called AI Skills, where you can effectively call an LLM inside the process to produce the exact output that you wanted to produce, and that was very popular as sort of like the early use case for customers. Came DocCenter, which we already talked about a little bit. Yeah. which is perhaps the most horizontally applicable use case of AI, and there's generally a feeling like this is easy and can be done out of the box, and nothing could be further from the truth, especially, you know, in enterprises that use decades of old documents to actually distract value from it. We've launched Doc Center in late 2024 in a number of successful cases in production across industries last year, and we're really pushing that as something that is broadly applicable and should be a driver of more adoption of our advanced tier in 2026. More recently, we've announced Agent Studio, which is a more comprehensive agentic offering to provide more autonomy and more use cases, and we're seeing first customers come to production, and we hope to tell you more of those stories as we go through the year at Appian World at Investor Day. The final step is, you know, what the product called Composer, but more generally Modernization. You've heard about it, talked about it as well. AI offers the promise of modernizing legacy technology. Decades old portion of a software stack just kinda sit there and deploy resources and are very inflexible and difficult to manage that now with AI can, at a lower risk, be transformed into a modern platform like Appian. Very, very early days. We're partnered with customers, and we're seeing some early traction, but that's like kind of the Appian journey with AI from, you know, from the past all the way into the future. We think about those capabilities that you laid out across those different dimensions that's mostly available in the advanced subscription tier today. For customers wanting to consume these AI capabilities, there's a upgrade or land potential on the advanced subscription tier. The question is, you know, there's also a premium tier. How do we think about the roadmap of the premium tier, what's gonna be offered in premium versus what's offered in AI? Yeah. One thing that I would argue is perhaps different for us versus many of the other companies who are claiming the AI mantle is that we charge you explicitly for it from the outset. If you wanna put a use case in production, you need to pay us. You need to pay us a 25%. That's the average realized price of what customers are paying us to go from standard to advanced tier. Then you get to deploy in production, then you get to get incremental use cases. We said two quarters ago that a quarter of our customers are paying us for the advanced tier. As evidence that we, in fact, are monetizing, we're past the product market state of our AI modernization story. Mm-hmm. For the time being, the game is still adoption. We wanna demonstrate success, and we wanna be the trusted vendor that the customers do their first, second, third AI use case with. We can sell more of the advanced tier to our customers who already have some licenses on the advanced tier. Obviously, we can drive that number of 25% higher. That's still the medium term, if you will, goal. You're right, we have a premium tier, which is another 25% to 35% uplift. We actually have relatively limited number of features in there. Surprisingly, we do have a handful of customers who are already paying us this. As we achieve, you know, sort of seeding the adoption and move into more modernization, we will put more features into that tier, and then we'll repeat the game. That's what I like about the playbook, in that we know how the game is played over a period of multiple years, and we're well along the way of demonstrating that the first step of that process is working. Understood. From a pricing strategy perspective, you know, the market's been concerned on seat-based pricing models. In your government business, you actually don't price per seat, you guys price per app. In the commercial opportunity, there's still significant exposure to seat-based pricing. As we look at pricing over the next 12 to 24 months, how do you think pricing is going to evolve, and what's the timeline for the company to potentially see consumption or utility revenue start to hit the income statement? I think of our pricing tools as sort of a matrix. What I mean by that is on one axis, you have all the different ways in which we charge, and those are per user, per app. We have enterprise-level agreements that are sort of unlimited in nature. We have consumption both as a overage to other models as well as individual ones. You have sort of ways within each of those models to drive incremental pricing. Those tiers, it's pure price increases. We increase pricing every year. We have multiple tools at our disposal to kinda drive the customer where we want them to go. The one thing I will say, though, is, this is what's different about Appian today than would've been the case two years ago. It doesn't get discussed as much as I think it should be, which is our go-to-market transformation. We've always had a good product. It's always very sticky. Our customers rely on us to solve the most difficult problems, that's generally just quite remarkable to see when you sit in the room with them. Mm-hmm. Where we haven't been as strong consistently is on our go-to-market execution. What we've done, and you know this 'cause you've been with us for a long time, but roughly two years ago, we began to more aggressively focus on the upmarket. We focused our efforts there. We actually reduced our sales org about 18 months ago in order to just focus on the top end. What that really means is selling value. Mm. For example, in the first quarter, we talked about a customer who signed a seven-figure deal with us. It's an aerospace manufacturer. In the process of designing the solution with them, you know, prototyping it, if you will, we concluded we can save them $60 million, and they agreed. When you have an agreement that you're saving somebody $60 million, then the question isn't, "Oh, it's this many users times this price." It's that, "I am gonna do this. I can do this for you. We both agree that I'm uniquely positioned to do this, so I deserve a portion of that." You know, P x Q might change. Mm-hmm. If you're selling value, and that's the marching order number one for our sales org in 2025 and 2026, a mindset shift to sell value, and if we sell value, like, you know, the units will resolve itself. Yeah. That totally makes sense. Let's talk a little bit about some of the growth opportunities in specific parts of the business in specific verticals. Let's start with Federal. Last year, there was a big concern about DOGE and the impact of what DOGE could have on software spending overall. I mean, you guys did fantastically well last year when it came to US Fed growing, you know, well above the growth rates in the business. I have it at sort of mid-20% growth in 2025 and accounting for 25% of total revenue. As we go from 2025 to 2026 post-DOGE, what do you see as the prospects of the Federal business going into next year? Yeah. DOGE was an unequivocal positive for us. You know, I imagine if I had been here a year ago in this seat that I would be receiving quite a bit of skepticism on that point. Sure. But what it did is focus the government on efficiency, particularly when it comes to their technology spend, working directly with the vendors as opposed to the intermediaries and really beating the drumbeat of automation. Automate or die. That's the world around easy when it comes to software these days. The reason why. Obviously, that plays to our core strength, the efficiency to streamlining, to eliminating manual processes, consolidating legacy platforms, legacy solutions onto a single modern platform. We've seen that demonstrate itself. There was a little bit of disruption in the first quarter where we weren't sure, like who's who. Since then, we've just executed really well. I will also point out in the fourth quarter, much of our revenue B was driven by the federal space where we exceeded our expectations despite the fact the government was closed for 1/2 the quarter. Mm-hmm. I should say one more thing. Particular achievement from our perspective, which didn't help the numbers in the fourth quarter, but is an indicator of the journey that we've made in the government, but arguably more broadly, was the framework agreement with the Army. We issued a press release that we have a framework agreement of up to $500 million in spending with the Army over the next 10 years, and that's really a hunting license to go and find new use cases and more quickly pursue ability to get more demand onto our platform. To me, that's an indication of, A, our success with one of our best customers, meaning the Army specifically, B, some of the changing sort of tailwinds, which I think are structural. We think all of those are positioning us well for growth next year and in the future in the federal space. You know, the pipeline is looking very strong into next year. kind of goes to, like, when we think about the overall growth rate of the company, you know, what potentially hopefully gets better is, like, the commercial business. You mentioned, I think in fourth quarter was one of your best commercial bookings quarters. Through the lens of, like, what you're seeing from a sales productivity side, is there a potential for the commercial business to start to get on a similar growth path as the federal business? Yeah. We've had better performance in Federal over the last few years compared to the commercial, which isn't a function of the end market, it's a function of our execution. Mm-hmm. As we think about all the changes in the go-to-market that we've done, that's where more of the changes have been focused on the commercial. When we call that commercial North America, the reason for that was because that's the first commercial theater where we made meaningful changes in terms of leadership, in terms of process. That was done at the beginning of 2025. fourth quarter is a quarter, but it's the largest quarter, and the performance was significant. We said best growth in commercial North America in more than three years. That's an indication of when you sharpen your execution, when you focus on selling by value, what's possible. As we look at it going forward, whether it's federal, whether it's North America, whether it's EMEA, whether it's APAC, we think we have the ingredients in place. Product has always been there, and then improved go-to-market execution, which is gonna carry the growth going forward. Yeah. Said another way, that commercial momentum that you saw in fourth quarter wasn't because of some product release. It's basically the multi-quarter effort around... [crosstalk] Yes. Around, go-to-market focus and sales productivity. Great. As I mentioned before, about 80% of subscription revenue comes from government, financial services, insurance, and life sciences. What's the runway in these four industries? You know, I get a lot of questions like, "Can Appian kind of be the pseudo vertical company? And in terms of meeting the growth and profit expectations that you guys hope to deliver, can we just focus on these four opportunities?" What's your sort of perspective on that? Say we have multiple levels of growth. First, I would say is plenty of room for penetration inside of the existing customers and inside of the existing verticals. That's in the context of just the amount of processes that still need to be automated, newer legacy, that we can go after and that we are very well positioned to go after. Point number one. Mm-hmm. Point number two is there's plenty of new logos in that space as well. We sell to some of the largest players in that space, but there's plenty of white space, if you will, in terms of ability to acquire new logos. The other thing that I would say is, as you think about AI as a node in the process, it sort of increases the TAM of automation. Mm-hmm. As we get past this early adoption stage where people are still concerned about actually getting value, we think that it will turn from, you know, fear to greed in terms of everything that could be done, and we're very well positioned about that. The final thing I would say is there's nothing magical about these four verticals in the if you fully expand the period of time. We have success in manufacturing, we have success in retail. We focused our go-to-market investments where we are seeing the best productivity over time, but as we build our execution muscle, that aperture will also expand. That will further be additive to growth over time. Yeah. I think you mentioned when we were having the AI discussion, like things like DocCenter... [crosstalk] Mm-hmm. Can be like a horizontal... [crosstalk] Yeah, very horizontal. Horizontal play that can drive a penetration outside of just those core four verticals. Let's move the conversation to profitability and capital allocation. 2025 was a pretty big year for margin expansion. You guys have been very clear that you guys wanna get to a pace of a moderate pace of investment in sales count and in engineering capacity. When we think over a multi-year timeframe, how should investors think about, you know, the operating margin trajectory, and how should investors think about the pace of margin expansion beyond 2026? Yeah. Let me talk about history first and then maybe a little bit about the present and the future. Appian, and this predates me, so I don't get to take much credit for this, it did a tremendous turnaround when it comes to its focus on profitability. Right around the time when we decided to focus up market, we generally decided to improve our focus and efficiency across the company. One thing about Appian is that, you know, when we choose to move, we move rapidly. You've seen this. We've gone from negative 8% EBITDA margin to positive 11%. Even in my time there, I think my first guidance was for 7% at the midpoint, and we ended up closing the year at 11%. We basically kept OpEx flat. However, what's also happened under the surface is that our productivity, particularly in our go-to-market org, has improved to the point where I think our sales and marketing payback on our sales and marketing dollars has become acceptable. Now our LTV to CAC has always been strong, but our sales and marketing payback wasn't great, which was always an impediment to growth. It's improved so sufficiently that we've earned the right to growth. That was my sort of internal drumbeat when I showed up, and I saw the numbers, I said, "If we can hit these numbers, then we've earned the right to grow moderately," which is what we're doing. We're investing in go-to-market, we're investing in overseas R&D. We're still expanding margins after two years of dramatic expanding margins. Again, because of the moment in time that we find ourselves in, this moderate pace of investments while still expanding margin is very, very important. We obviously just guided for 2026, we're not gonna expand, you know, beyond that. What I will say is that we see the opportunity to do both. See the opportunity to drive healthy revenue growth while continuously driving margin expansion. It's really the combination of two that we think is very important. Awesome. I'm getting a lot of questions on around the topic of capital allocation and particularly on a couple of different topics, and this is kind of across software. Wanted to get the Appian perspective. One, the importance of share buybacks as share prices in software, including with Appian, have come down. What level of share dilution should investors expect going forward, and how important is it for the company to get to GAAP profitability? The fun fact, we were GAAP profitable last year. It's $1.2 million. Hey, it's in the green. Yeah. Let's start there. This is exceptionally important to us, and we've always been very cognizant and careful about dilution. Our stock-based compensation as a percent of revenue is less than 1/2 of the average company our size. That actually matters as you think about sort of compounding growth over time. I know some people try to think about it as, like, free cash flow minus SBC, you can use that framework, it's the same answer. I'm more comfortable just thinking about it on a... [crosstalk] Mm-hmm. On a non-GAAP basis. We just issued a $50 million buyback. That buyback is not a reaction to our stock price being where it is, it's a reaction to where we've come as a company in terms of improvement in profitability. Last year was the first year in which we generated meaningful cash flow. What we said is like, yes, it's a $50 million buyback, that's important, but think of it as the beginning of consistent capital return policy, which we're now in a position to communicate to our investor. The other interesting thing, because we dilute so relatively little, that $50 million buyback essentially offsets dilution for us. If you then take a step back and think on a multi-year time horizon, which is how we're running the business, we think we have, like, four ways to deliver value. One is continued revenue growth, and I'll just use numbers from this year as an example, 11% at the midpoint. 16% cloud, 11% at the midpoint for the total. EBITDA is gonna grow faster than revenue, so that 100 basis points of margin expansion means low twenties growth in EBITDA. You have net income that's gonna grow faster than EBITDA, pro forma net income, because we don't need capital to grow. We will delever in absolute and relative terms, and that will mean the net income grows faster. Finally, as we buy back shares, this year we're roughly offsetting dilution, but over time, free cash flow is gonna grow more than dilution, so we're gonna start shrinking the share count, which is hard for most software companies to do. Yeah. As a result, pro forma EPS is gonna grow faster than net income. This year we're guiding to its midpoint of the range, sorry, pro forma EPS growing 46%. As long as we can deliver on all four of those metrics over a period of time, we think we can really compound value and deliver an interesting return to, obviously, to our customers, through our innovations, to our employees, as well as to our shareholders. Awesome. This last question for you goes back to the guide. I think we exited fourth quarter at about 16% constant currency cloud growth. Mm-hmm. I think the guidance assumes a similar level of growth. What gives you the confidence that cloud growth sustains throughout 2026? Yeah. I would say a few things. Number one is we actually had a very good fourth quarter in terms of, new business, but it was somewhat back-end loaded, so you'll see more of that... [crosstalk] Mm-hmm. Hit us in 2026 than it helped us in 2024. That, you know, 16% is a little misleading that way. Second of all, there's a little bit of benefit of currency in first quarter. As you think about the two 16s are not comparable, like, one is constant currency, the other one is total. Fundamentally, it's about execution and our confidence to go and do it out there in the market. We have a pipeline, we have a sales org, which has done a remarkable job of, you know, delivering a good year while rebuilding. Now the goal is to grow and continue improving productivity, and we think we can do it. Awesome. Thank you so much for giving us the update on the Appian story. Excellent. Thanks. Awesome. Great.