Good to go? All right, perfect. All right. Well, thanks everybody for joining us in the last session of the day for day two of the Citi Global TMT Conference. I'm Steven Enders, part of the software research team here. With us today, or for the final session today, we have Serge from Appian. Serge, thank you so much for joining us.
Thank you for having me. Great to be here.
Great. Maybe just to start off, maybe we can talk a little bit about just the main use cases that Appian evolves and run through the high-level story for Appian today.
Yeah. Appian has been in business for 27 years, and what we do is we automate complex business processes. That's a lot of words, so I'll give you some examples. We automate fraud prevention for financial institutions, mortgage or health insurance applications for healthcare and financial services companies, a variety of public sector use cases. One of my favorites is we run inventory of ammunition for one of the branches of the U.S. military, so that's as mission-critical as it gets. What these use cases have in common is a few things. Number one is they tend to be cross-functional. They tend to be mission-critical, and accuracy is very important. They frequently involve the customer in addition to the company itself, and accuracy is exceptionally important. The other question that usually comes with that is, okay, well, what does Appian replace?
The answer is, there is always something in place. Sometimes it is just a paper process that becomes automated for the first time. Other times, it is a homegrown application that is now having trouble scaling or simply cannot keep the functionality what the business needs. Or it could be a rudimentary automation tool, a third-party automation tool that, again, cannot meet regulatory requirements or security requirements or accuracy requirements. Appian steps in and replaces it. The answer, whatever it is that customers use us in order to have greater flexibility, greater agility, lower cost, and in many cases, direct revenue outcomes for using us, and that has been our story for the quarter century now.
Okay. No, that is great to hear. Maybe we can talk a little bit about just the demand environment and the business environment that you are seeing right now. I think the business has been accelerating for almost a year now. Every quarter, cloud has been accelerating the past few quarters. Just what is driving that, and how do you think about those factors and sustainability of that moving forward?
Yeah. We are seeing a very strong demand environment, and it is really driven by our AI capabilities. Appian has been out there for multiple years now talking about AI as this powerful technology. It has tremendous benefits, but it needs a framework to actually operate at scale. We talk about this as AI in Process, and now you have heard a number of terms that have emerged for this idea, whether you talk about an agent harness or talk about orchestration layer. It is this idea that AI needs something in order to be effective and accurate at scale.
Because we have been out there, consistently talking about AI in this context, and because our product actually delivers AI capabilities and functionalities and strong returns while adhering to accuracy and performance requirement that our customers need, which are highly regulated industries in the public sector, we are seeing the demand grow. We are seeing strong pipeline that is converting, and I liken that to a wave. We have a wave of demand coming our way, and then it is our job to surf that wave or rather convert that demand into actual revenue, and we are doing a great job.
Happy with execution, continuous improvements in sales productivity, and you combine existence of demand with ability to close it, and that's been the story of Appian for the last couple of quarters and the story behind our acceleration that you mentioned on our cloud revenue in particular over the last couple of quarters.
Okay. I think we hear a lot about people adopting AI, people adopting agents. Can you just maybe help crystallize it a little bit more fully? What are the use cases that your customers are using Appian AI for, and how do you think about the repeatability of some of those use cases to potentially spread more fully across the base?
Yeah. So front and center for us right now is a use case or a functionality that we call DocCenter.
Okay.
DocCenter is AI-enabled document processing at high accuracy and already a part of your process. So you're not separately processing your mortgage applications in one silo and then feeding it into some process. It's all integrated in a single process and with high accuracy and ability of AI to reason and send for your next action, whatever it needs to be. The great thing about document processing is that it's a very horizontal use case. Every enterprise is drowning in documents of some sort. So it applies in every one of our verticals. It applies in every one of our geographies. And more importantly, everybody has more than one use case. So an example that comes to mind for me is a health insurance company here in the U.S. that implemented its first DocCenter use case in June.
They already need to buy incremental AI usage just to satisfy their use case, and they're talking to us about the next couple of use cases that will only further drive the need for their spending on our platform. I think about DocCenter as kind of the tip of our AI spear, and that's probably a multi-year cycle because, again, doc processing is such a pervasive use case across enterprises and certainly in our industries.
The next one behind it, I would say, is agents. We GA'd our agentic capabilities last year, and we're seeing strong interest. It's obviously earlier on, but we're seeing very broad use cases from relatively straightforward, simple agentic deployments to very complicated ones and very sophisticated ones and sort of across the board. We're working this year to continue hardening the product, to continue improving our ability to implement, and that's something that we're going to put more arrows and more focused on as we look into 2027. I think DocCenter, number one. Agent's the next, and the overlapping driver of demand. Then the third one is various products that make it easier to build applications with Appian. Composer is the one that we talked about.
We also have a functionality called Dev MCP, which allows you to use your favorite vibe coding tool and use that to connect to the Appian platform and build apps using natural language on the Appian platform. What those products will do is they will just reduce the cost of building on Appian or rebuilding on Appian, and that will be an incremental driver of growth. Obviously, that one, in my opinion, is sort of the longest in terms of the duration and very large, but the one that's earliest on.
Okay. Maybe on the agent piece of it, I think that one's a little bit maybe earlier in terms of the adoption curve for you all. I think when we talk to CIOs and people, it seems like agents, in their view, is a little bit slower for adoption, but just maybe where are we in terms of that adoption curve, and are there certain agentic use cases that are starting to pop up today for you all?
Yes. The challenge with agentic is that true agentic really requires the right use case.
What I mean by that is that it's this case in which you need adaptive reasoning. You have a sufficient amount of ambiguity that you both want and need to deploy AI more broadly. You still do it because it is more cost-effective than applying a human, but you need to make sure that it's accurate and reliable. Again, the agents, you want them behaving under the set of rules that you are operating. That's sort of the sweet spot. But we see a lot of customers coming to us thinking that they have an agentic workflow, and we tell them that they're actually better off applying a more of a deterministic process with more narrow AI capabilities, which will be more accurate and less expensive. That ends up being the better outcome for the customer.
It's not a traditional agentic use case, but it's AI powered, and it's very valuable to the customers. Again, it comes down to ambiguity where a lot of context needs to be driven from multiple different places, as opposed to one or two, where incremental pieces of information are needed to kind of evolve in step-by-step reasoning. That's where agentic is meant to be better used, and if you apply it more broadly, which some have done, not with us but in general,
you end up probably in a place where you're either spending too much money or you're not getting the accuracy that you wanted to get, and then you end up going back to the drawing board.
Okay. When people go back to the drawing board, does that end up creating an opportunity for you to then step in and take on that use case?
Yes, absolutely. What I've generally seen is that a lot of the vendors that we run into, I feel like, have overpromised on AI early on.
Yeah.
This idea that AI can self-govern and just turn it over to AI and agents, it'll be fine. They're backtracking a little bit on that message, and it helps our credibility that we've been pretty consistent and that we can then back up that consistency of message with the quality of our products, and that's why we're seeing the demand that we're seeing.
Okay. No, that's great to hear. Maybe kind of staying on the line of thinking but maybe turning more towards the monetization opportunity with AI, just how do you think about how that kind of develops for you moving forward? Is it more about tiering? Is it about consumption? Is it about incremental SKUs? Just how do you think about that adoption curve and how the levers kind of evolve from here?
There's multiple levers. The first one I would say is actually the tiering. Just to take a step back, we introduced tier pricing at the beginning of 2024. We're two and a half years into it. Basically, we created a Standard tier, but to get access to our latest functionality, and most importantly our AI functionality, you have to upgrade to what we call the Advanced tier, and that runs you roughly 25%-35% more. Just to have access to our in-production capabilities, you got to pay us out of the gate. We talked about nearly 40% of our customers having some portion of their ARR on the Advanced tier. In Q2, we also mentioned that 85% of our new logos in the quarter actually off the street came in and bought the Advanced tier.
Which I think speaks again to the quality and credibility of our AI message. Our Advanced tier ARR has been building consistently and will continue to do so. That's step one. Still plenty of room to go. Step two is usage. Our Advanced tier and other ways you can buy AI come with what I would describe as a moderate amount of usage included, enough for a single use case. For example, the healthcare company that I talked about, their first DocCenter implementation already depleted what's included. Now they need to come back and buy more AI bundles from us, more usage. As they implement the third and the fourth use case, then obviously all that is accretive. It's early days. Relatively few customers are at a point at which they need to buy AI usage.
I think that sometimes in conferences like this, it's easy to forget that AI is still very early in terms of adoption, really in enterprise when it comes to mission-critical applications, particularly enterprises that we serve. It's early days, but it's building, and we think that's another medium-term level of growth.
Yeah.
The third bucket is we're going to play this game again. Above Advanced tier, there's something called Premium tier. Very few customers are in that level now. But over time, we'll start to put more advanced AI features there, and we'll ask for another 25%-35% uplift. We think that there's plenty of opportunity. If you think about it both from the perspective of use cases and ability to monetize use cases, we're in early innings, no matter how you think about it.
Okay. On the Premium tier, I guess, what are the capabilities that you get incrementally versus the Advanced tier? I know it's still early, but longer term potential, where could that potentially go in terms of the penetration within the base?
Right now, it's a handful of features. Right now, it's more included AI usage. We are very much still in the seeding the market stage, which is what we're doing with the Advanced tier. Once we feel like that game is largely behind us, which I'm not suggesting it's this year or next year.
Yeah.
At some point, we will start putting the incremental feature there, and then it will be the next chapter of that story.
Okay.
Chapters one and two have a long way to go.
Okay, that makes sense. I want to ask a maybe high-level question on AI and the opportunity set that you see here. I think we still get the conversation or the questions around build versus buy, and what that means within the customer base that you serve, and how they think about when it makes sense to use Appian, when does it make sense to use custom code, and how does that kind of view evolve over the next few years. It would be great to get your perspective on what that looks like.
Thank you for saying custom code, because I sometimes need to remind people that custom code has always existed.
Yeah.
It is not a new concept. It is not something that began with vibe coding. You can always go hire yourself a bunch of developers at $250,000 a pop and have them build something custom for you. That has always been competition for platforms like ours. Nothing is really changing from the perspective of this competitive force always existing. Okay, so now comes vibe coding, or ability to use natural language coding to accelerate the process of custom coding, and it is very powerful, obviously. We have heard the customers' position change, I would say sort of in April, May of last year, in that what we were hearing before that is, "Well, these are interesting tools. We are learning what they are good for.
We would never use them for something that is very mission-critical and core to our process, but there is probably other things around that this would be an interesting alternative for." To now the conversation changing a little bit of, as exciting as those tools are at the beginning, you start discovering costs associated with them down the road, and the word maintenance suddenly starts coming up. One of our partners talked to me about, and this is a large systems integrator, who built a meaningful app using natural language processing in the hopes of demonstrating internally and externally that it can be done, and then it becomes a business for them. They soon found that this app requires a couple of dozen people to be maintained. By the way, these are people who have far more technical expertise than an average enterprise.
For them to be in that situation shows you that this might not be tenable anytime soon for a traditional enterprise, which is always struggling to get technical talent on board. We see interest from customers. We see apprehension. If anything, the balance between apprehension of interest has switched, I would say, over the last four or five months, more in the direction of apprehension. I am sure they will have a role to play, but we do not see them impacting how our customers make decisions about processes that they would consider deploying on Appian.
Okay. At this point, it is not having any impact in terms of deal cycles or their decision-making to move forward with an application on Appian versus them choosing to try to build something themselves?
Not at all.
Okay.
Demand is strong, and deals are continuing as they have been.
Pipeline looks good?
Pipeline looks very good.
Okay. All right. That's great to hear. Maybe shifting gears a little bit, with this being a big Fed quarter, I think that's about a third of the business, something like that, for you all?
Federal government 25%, total government low 30s, yeah.
Okay. Just maybe we can talk a little bit about the demand trends that you are seeing within that vertical. I know that there has been a lot of automation initiatives with DOGE over the past couple of years. There is the massive $500 million ELA there as well. Just how do you view that opportunity moving forward, and any kind of views for what that means for this quarter and what you are assuming in the guide at this time?
Yeah. So there has been a positive structural change in the federal sector for Appian last year. What I mean by that is the government is focused on efficiency, the government is focused on impact of its technology initiatives. Ongoing, never-ending projects are out of favor, and dealing directly with vendors who are going to sell you software and implement that software so you can deliver flexibility, agility, cost savings, whatever it may be, to your use case is what the government wants. That simply put us in a better competitive position than we have been before. We are more frequently directly competing as opposed to resellers. There is greater focus on the value of the software as opposed to just its price. That speaks to our strengths. We have had a very strong year across the board in federal last year, including a strong close in Q3.
Frankly, to me, the question was, is this a one-time thing, meaning the first year of the new administration, or is this an ongoing change? Sitting here six-nine months later, I can tell you that it feels like an ongoing change. So that is why it is not a one-time thing, but a secular demand driver. We expect to have a very strong quarter in Q3 in federal. That is part of our guidance for the year. We expect to have a strong year in federal next year.
Okay. I guess the U.S. Army ELA that you have, how do you view what that means, and I guess the repeatability of that with other agencies within the federal government at this time?
It was an important milestone for us because it sort of demonstrates a physical manifestation of what I just talked about.
Yeah.
Like increased visibility that Appian has inside a major part of the U.S. government. It is a framework agreement to spend $500 million over the next decade, I guess nine years at this point, with the Army. It is not a commitment, but think of it as a purchasing vehicle that dramatically accelerates or simplifies ability to get new processes on top of Appian. It does two things. One, it has the potential and has demonstrated so far that it benefits us specifically pursuing new business with the Army. But more importantly, it also serves as a badge of distinction, if you will, with the rest of the, not just the military parts of the government, but also the civilian as well.
If a portion of the government views us as such an important partner, to be willing to create this framework, it just opens other doors for us. Again, it speaks to the strength of the federal business over time.
Okay. No, that is great to hear. Maybe we can shift gears a little bit and talk a little bit about go-to-market. At this time, I think there has been a lot of focus on incremental hiring and headcount and investing in the go-to-market and trying to drive more ramp coverage. Where are we in that investment cadence and turning that spigot back on and where do you view the biggest areas for incremental opportunity to go invest behind?
Yeah, so let me take a step back and just talk about the chapter before the current chapter.
Sure.
In 2024 and 2025, Appian was very focused on sharpening our focus at the high end of market, so enterprises, large strategic deals, improving productivity of the sales org. Frankly, our sales org didn't grow in 2024 and 2025 because we were focused on improving our productivity and returns. We succeeded in that.
Yeah.
We showed some data on this in this regard at our Investor Day. We've improved our productivity and returns and paybacks to the point where I was saying internally and externally, we've earned the right to grow.
Yeah.
That's great because our sales force is tiny compared to the opportunity that we face. You want to grow it once the return is warranted, and then as you grow it, you want to make sure the returns continue improving or at least remain stable. Halfway through this year, we feel very good about that. We feel good about the performance that we showed in the first half. We feel good about the pipeline and the forecast for the back half. We said to ourselves, "Okay, here's an opportunity to start hiring early for 2027." As we think about the back half of the year, you're putting together your structure, your territories, your comp plans.
So wouldn't it be great if we can get those people a few months earlier than otherwise, in order to put them in a position to be ramping and to hit the ground running into 2027? And again, with the revenue outperformance, there was room in the P&L to do that while still expanding margins, and that's what we decided to do. As you think about where all these heads are going, the same places. There's no need to put them anywhere else. We have plenty of coverage opportunities in our core verticals, and so there's no need to, anywhere near the need to try something new or dramatically different in order to grow the sales org. We can just keep doing what we're doing, serving the markets that we're serving for years to come, and just keep growing our coverage in order to grow our revenue.
Okay. And I guess with these headcount additions, is there a way to dimensionalize how much we're growing this, and I guess secondarily, there's been a big focus on rep productivity for you all, and like that chart that you have in the investor deck showing that trend and show that increasing. Should we start to expect that to level off and maybe decline as those reps get ramped up? Or just how do you think about what that means moving forward here?
I think the key thing to think about is balance, right? So you want to grow the rep headcount, but you want to make sure that you are doing it in a way that they are as productive as the base and not dilutive.
And so you don't want to do too much at once, because if you do that, then you will have lower productivity, you will have attrition, and you will have the need to kind of reset, and you don't want to put yourself in that position. Instead, what we're hoping for is consistency of growth. So adding rep next year, adding rep to this the year after, and so on and so forth, while maintaining or improving average productivity over time. Because again, what we're trying to build is a consistent compounding return story that begins with revenue, goes down to margin, further down to net income, every metric per share, but it begins with consistency of revenue. So I think companies frequently make a mistake where they extend themselves for that incremental percentage point of revenue growth, and take operational or execution risk.
Instead, just given the size of the opportunity, we are going to grow at a healthy rate, while at the same time maintaining our productivity and expanding margins.
Okay. No, that makes sense. As you think about the partner opportunity, where do they fit into this investment cycle and where are we in terms of them pulling you into incremental opportunities and, I guess, leaning into them a little bit more as a growth lever?
There is a lot of opportunity to do better with the partners. First of all, there is a lot of implementation works that our partners already do, and we are happy for that to be the case, because it provides them incentives to be engaged. We have rebuilt our partner org and increased focus on key partnerships because we want to invest in people who invest in us. So it is better to have a smaller number of very vibrant partnerships than a peanut butter approach to a larger number. Second, what we are seeing from our partner community is that they are interested in new ways of doing business with Appian. Because they are a traditional implementation business, as you think about it in the world of AI, there are a lot of questions around what that looks like.
However, if there are ways that we can go to market together, produce solutions together, figure out new ways to share revenues, it is all incremental to us because, again, they carry the distribution. There is a lot of early discussions and excitement, particularly when you marry that with our AI products, which have resonated very strongly with them. That is another opportunity for us over time.
Okay. I want to ask on maybe the financials a little bit, shift gears. It does seem like there is a little bit more balance today between investing and driving growth versus letting things flow down to the bottom line. Just how are you kind of thinking through that framework at this time and what should we kind of expect moving forward here?
I would expect the balance to continue, and it is a key word for us. We are in a fortunate position to be able to grow revenue while continuing to expand margins, and we want to do both over time. We do not want to invest aggressively and then put the risk in terms of our productivity profile or our returns profile. Also, we do not want to start the business from investment for a continued improvement in margins, a rapid improvement in margins, but that reduces our ability to kind of drive long-term growth.
This year, for context, we are going to grow revenue 17% at the midpoint of our latest guidance. We are going to expand margins by 200 basis points. That is up from 100 basis points original guidance while investing in the business. We are starting some of that hiring earlier that we talked about. We are happy that we can do that. By the way, both of those things, meaning revenue growth and margin expansion, have a multi-year run one way for Appian, which I think is an appealing part of our kind of returns algorithm for our investors.
Okay. I guess as a piece of that, is there a way to think through free cash flow versus EBITDA and driving that conversion to free cash flow?
Right. If you think about what is between EBITDA and free cash flow, we have interest expense. We have done some work this year in terms of refinancing our debt in order to get better terms. There is an ability to kind of dimensionalize that based on our financials. Very limited CapEx here and there. We will open an office, so not a big deal there. We mostly get cash up front when we collect from customers, so that is to offset some of those elements of the contraction. Roughly speaking, they are going to be growing in tandem with each other. Our most important sort of capital allocation commitment is to, over time, effectively return all of our free cash flow to shareholders in the form of share buybacks. We are doing a $100 million buyback this year, and we will continue doing strong buybacks as we go forward.
That will more than offset the dilution that we have from stock-based comp.
Okay. I know you are leveraging AI more into the product set, but what does that mean, I guess, for internal usage of AI? Where are kind of the core areas where you are deploying that across the various teams and what that means for further expenses or where you can find more cost savings moving forward?
The place where we are leading is with our R&D org. Credit to our engineering team, they are seeing great products, great improvements in productivity, and more to come. They are, in fact, reimagining the entire software development life cycle around AI, and that will sort of continue improving our engineering productivity. What that allows us to do is, for the same investment, put more innovation out in the market, which is great from the perspective of helping drive revenue growth, while at the same time driving operating leverage, because if the expenses grow slower than revenues, then you get operating leverage. We are having early successes, mostly actually using Appian platform itself across our G&A line items, whether that is in finance, whether that is in people or your hiring process. Our quoting processes all have Appian AI deployed.
I'm starting to see benefit, and what that allows us to do is as the business grows, we don't actually have to grow headcount dramatically to support the growth in the business in some of those support functions. Those are some of the areas. There's plenty more that we can be doing. Again, it's all in the context of generating leverage, showing margin expansion, while at the same time revenue growth. We have all the normal scaling tools, if you will, at our disposal, plus all the AI tools to further cement that runway for us.
Okay. I want to ask a little bit on the competitive environment and what you're seeing there. I think there's a lot of organizations and companies in the space talking about agent orchestration or talking about this kind of next phase of leveraging agents internally at enterprises. Just maybe what do you kind of see there and what do you kind of view as the differentiators of what Appian does versus others in the marketplace?
First thing I would say is we don't see any significant changes in the competitive environment.
Okay.
Occasionally in conferences like this one, we get asked about the new players, about the model providers, do we see any of them as competition? The answer is no.
It is the same competitive set that we have faced over the last few years, with one distinction, which is our win rates are significantly higher when AI is a specific factor. When we get the RFP, when we get into the competitive situation and customer really cares about AI, which is not always, but when it is, our win rates are significantly higher than they are on average, which again speaks to the credibility of our AI offering and frankly, the quality of the product. We are still very much living in that stage.
Yeah.
The stage of the first or the second use case, the stage of getting agentic to work for the first time.
Yeah.
As you now try to imagine a world, which to us does not feel like it is happening in the very near term at all, some world of agents in one corner from one company, from a different corner in a different company, and then needing for all those agents to communicate with one another. We have a lot of wood to chop before we get to that world. When we get to that world, the benefit that we will bring to the table is the same benefit as when you deploy your first agent on our platform, which is guardrails and data access. So ability to operate in a framework and ability to access data across the enterprise without having to move it in ETL anywhere, which is our Appian Data Fabric offering.
We have an Appian Dev MCP offering, which will allow other people's agents to access data and processes that exist on the Appian platform. We expect to monetize that over time. It is very early. Customers are trying it, but as I said, it will take a while. But in a world in which ultimately what AI, ours or anybody else's needs is framework and data, we provide both and we expect to benefit.
When AI comes into the RFP, is the competitive set that you are going up against, is it any different?
Nope.
Okay.
No. It is the large traditional competitors, your ServiceNow, Salesforce, Microsoft of the world, and its automation players, most notably Pega.
Okay. That makes sense. I do want to ask about some of the use cases that you drive. I know we have talked in the past about ServiceNow had this great use case in ITSM.
They started as a platform and then found this and started stamping that across the customer base. When you think about what Appian could do to find a repeatable use case, are there areas where you feel are better suited for Appian to do that and drive a similar level of success? Or just how do you view that ability moving forward?
For better or worse, we are exceptionally versatile.
Yeah.
That makes it very broad in terms of what we can implement. But it does make the sales cycle longer and you need to find the use case that is complex enough and sophisticated enough that it warrants an Appian platform. The way that that plays out for us is that, we have exceptional growth of our customers for many years after they get on our platform because we keep finding new use cases that we can deploy once we land in an enterprise. But again, every one of them needs to require flexibility and versatility as opposed to a point solution that you can apply off the shelf.
That does mean that our sales cycles are long, but it also means that our gross retention rate is exceptionally high because customers love our product, and frankly, it becomes very sticky, and it builds this stable place over which we can grow over time. The acceleration for us has not been that we figured out a way to run the flywheel faster. It's that we just focused on larger and larger deals, so the payback at the end of the sales cycle becomes bigger, and we think we can continue doing that, and that's going to continue being driver of the growth. As opposed to productizing or focusing on specific features, that kind of opens a different angle.
That may come over time, but we think there's great benefits in selling the platform, even if it does mean that sometimes you have a more complicated sales to begin with.
Okay. Last question here. As you think about model adoption moving forward and you think about what are the right use cases for embedding a frontier model within Appian or utilizing open source models, how do you think about what that mix looks like and how do you optimize for some of the cost versus benefit dynamics there?
First, we provide a tremendous amount of flexibility to our customers, where you can choose your model and not just for the entirety of the use case, but for the individual components of it. Historically, so far, because it's early days, we haven't found customers really availing themselves of that capability very much, but they go with whatever standard setting we give them for the most part. However, and you know this, the topic of AI expenses has definitely moved into the forefront for my colleagues across the board.
Sure.
CFO cares what you spend your money on, and after a while, it's no longer just a side pocket of money, it becomes significant. As we see that happen, and as we see customers having incentives to be more thoughtful, where do I really need a frontier model? Where can I go with an open source model or an earlier generation model? That will be another way for them to tweak value that they get from their use case, and we benefit either way. We're happy to be the agnostic layer that gets them picked the underlying LLM, and we benefit from the competition and innovation at that layer.
Okay. No, that's great to hear. I know we're at time. Serge, I want to thank you so much for joining us today and great to hear from Appian.
Excellent. Thank you for having me again.
Thank you.