All right, good afternoon to the afternoon sessions of the Morgan Stanley Day 3 at the TMT Conference. Super thrilled to have the management team from Appian. We have Chief Executive Officer Matt Calkins and Chief Financial Officer Mark Matheos. Matt, Mark, thank you again for joining us at the conference. We really appreciate you spending the time with us, and looking forward to diving into the Appian story.
Thank you. It's great to be here.
Awesome. So before we start, let's get to the disclosures. For important disclosures, please see the Morgan Stanley Research Disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley Sales Representative. With that, I wanted to, you know, set the stage for the conversation in terms of just going to the basics, Matt, in terms of what, how would you characterize the unique value proposition that Appian's automation suite offers compared to alternative solutions out there in the market?
Yeah. Okay. So we're at the top of the market, right? We do process automation for the largest organizations, for the most mission-critical processes. We were the first company to go public as a low-code firm, and we've expanded into automation technology like AI, RPA, business rules to accompany that. So we're routing the work, and we're doing the work. And edges lately are Data Fabric and AI. I would say those are our two biggest features that make a difference between us and our competition. We could go through those separately if you'd like, but those are our top differentiations.
Makes tons of sense. Before we get into, you know, the data fabric, the AI, the automation story, let's do a recap of 2023 and sort of give us the journey, in terms of your customer spending intentions. I think, Matt, you were particularly concerned about a recession going into. I remember you and I had those conversations. We kind of technically avoided a recession, but I think in the software world it was it was pretty tough in terms of a spending environment and a prolonged spending environment. So in terms of what we saw at the beginning of the year and how we ended 2023, what were the trend lines in terms of customer spending intentions?
For us, it felt almost recession-like. You're right. I predicted a recession. A year ago, I said, "We're going to have one." I was pretty confident I was wrong about that. I was not. But it still had that aspect. And especially in financial services, I found there's a lot of cautiousness, you know, between the bank failures and they so that's our top industry. There was a bit of a paralysis amongst some of our customers. So it still had that feel, even though I admit it there was not my prediction coming true. However, I think we come out of this year with more momentum. I think that we predict I predict less trauma in the markets in the coming year than there was in the past year.
Furthermore, we have this wonderful new theme, this AI. It's like a golden key to get into any conversation. We've been in AI for a decade, and it's something that everybody wants to talk about now, and we can show value. Last year, a very hyperbolic year. Everybody was just talking. This year, I think it's going to be about demonstrating, and we're going to be very good at providing concrete results from artificial intelligence. I think that's going to be one of our primary drivers for growth this year.
Yeah, well, I wanted to dive into that just a little bit more.
Yeah.
I mean, from a high-level perspective, AI in some sense, AI's been around for a while. And then we've had, you know, with ChatGPT, the generative AI movement. And I think when people think about these technologies and how to enable it in the enterprise, I think there's sort of a lot of confusion. And maybe just from the basics, how do I start, and what should I be focused on, you know, generating new services? Is it about automation? What is this all about? I think from your perspective, when we think about the categories that you play in, you know, workflow automation, case management, BPM, which are all about, you know, automating business processes.
Yeah.
Is that where people are starting the journey? Like, was there a thaw in the market at first? And, like, what's step one to get into the AI journey?
This is one of the great places to use AI. It's not the only, you know. AI can do other things too, but within a process, in order to get you to a finished work, that AI has a lot to add. It can make recommendations. It could write your emails. It could, you know, make a proposal. It could make a decision if you dare to let it. AI has a place to play in a combined work team driving toward an outcome. And furthermore, if you use AI for that, you've got an ROI. You've got a measurement. This year, everybody wants to be an AI hero. And I don't mean that derogatorily. I mean, every executive that I meet with is trying to win the AI race. They want to be the first in their company to show that they can get value out of AI.
And the way you do that is to use it in a predictable, safe way to get a real ROI. And so this is a great use case for AI within a process. And it also highlights the fact that AI shouldn't do most jobs alone. AI is part of a team. It's not a solo act. And so using AI to do just the work that it's good at and then handing it off to other entities to do the work that they'd be good at, be it robotic process automation or people or something else, AI is going to be a safer choice within the context of a team than it is as a standalone solution.
Is there a sequence of investments that your customers are talking about? It's like, "We have to get our processes more automated. We have to get our applications more integrated." And then what sort of step two and step three when we think about, you know, integrating, you know, with some of the large foundational models? Like, what if you think of maybe some of your interesting customer case studies, how are they thinking about the journey with Appian?
Well, they start with a mandate, generally. They start with a problem. The mandate is almost always a problem. They say, "We're spending too much money," or, "We're inefficient," or, "Our customer service is bad," or, "We're wasting most of our data because we don't know how to bring it to bear at a moment of a decision." They have a problem, and then we can help them with that problem. They don't start with the infrastructure. When we encounter a client, they've got 1,000 systems. All those systems have data, right? It's chaos, generally. They've had acquisitions. They've got regulation changes. They've bought a whole lot of assets, they do not have coherence across their enterprise. But that's okay. We expect that, and we deal with it.
We're here to help them get to their motive, their specific issue that they need to fix without rearchitecting the enterprise, right? Without forcing them to make secondary changes. We're going to take this enterprise as it is and give it some value, whether that's AI value, process value, right? Whatever it is, we'll just deliver it with a minimum of externalities.
Yeah. And I think this is something that you highlighted about delivering tangible value. Can you talk to how Appian's delivering actual value to its customers and turning that into revenue for the company?
Okay. So we do have some ways lately. I mean, that this isn't exactly what you asked, but I'm going to use this as an excuse to talk about how we've changed our pricing and how we're going to turn value into.
Great.
Into revenue.
Yeah.
All right? Which is kind of what you were getting at. Appian used to have a very complicated pricing system, far too complicated, actually, too many ways to buy our licenses. That comes out of the fact that we deal we do high-end negotiations with big buyers, big organizations. They want it their own way, and they're making a large commitment, and so we have to be compliant. We've simplified a lot. We have one primary way to sell coming into 2024. There's one pricing model. We should be doing that almost everywhere. We've simplified down to one, but now we've added two premium layers. So we may always now be pricing by application and measuring the value of an application according to how many users there's going to be, but we're going to have a premium layer and then another upper premium layer.
Each of those is going to be about a 25% uplift on our regular prices. What our goal for this year is to get as many customers as possible to upgrade to that first premium tier. That premium tier is going to include AI, case management, data fabric across multiple data sources, right? Some really essential stuff, actually. These are great features, features that our customers ought to want if they're serious. If they're going beyond one little application and branching out, they should want this stuff. And so we're going to give all this on the advanced tier and try to move them up 25%. And then next year, AI is going to break out again into another tier higher than that. At least that's the intention right now. We're bundling AI for this year into the middle tier, but we mean to separate it.
Once we have case studies, once we have implementations and customers talking about it, we want to separate that out, not just AI, but, as we say, Private AI, our with our specific spin on AI. We think that that's a distinctive enough feature that it will drive a higher price point.
Let's talk a little bit about Data Fabric, which was kind of a big theme of the last earnings call and something that you highlighted as Appian's competitive differentiator, right?
Yeah.
And so can you speak to what Data Fabric actually, actually is, and how is that going to be an unlock for your customers to drive data expansion?
Yeah. Yeah, that's right. Okay. So first of all, for those who are not familiar with the term, Data Fabric's like a virtual database. It connects all of the data silos and databases across your enterprise and makes them look to the user as if they are local, right? It gives a kind of an object language, a semantic layer that allows you to address these data artifacts, no matter how distant they are, as if they are a part of your local database. You can read to them as you can read from them. You can write to them. This is a great way to get cohesion out of a dispersed enterprise. And that's really important because most companies are wasting most of the data they have because it's hard to get, and they can't bring it at the moment they need it.
So a data fabric gives you coherence, and it gives your data immediacy, immediate value. That's really important by itself. Now, data fabric is also wonderfully synergistic with AI. And I could get to that in a second, but that's the data fabric thing. It's born out of our philosophy that we're not trying to take the customer's data. Our competitors largely are trying to take the customer's data. And so for us to be facilitating a dispersed and open data strategy makes us different and makes our investments different from theirs. So we've gone a long way down the data fabric road, and our competitors have just taken a different fork. It's not what they want. They want to own the customer's data. And so we've got an unusually large technological lead in data fabric right now, mostly because they didn't want it.
Our competitors didn't want it.
There's the element of, like, competitors trying to do the data land grab, if you will.
Yeah.
with like data cloud platforms and those types of things. But then there's the other element of you're actually requiring the customers to build a process to get the data from their original source systems into somebody else's central repository, which is also work and cost, right?
Yeah. That's right.
Having a sort of virtual, you know, data warehousing capability seems to me make a lot of sense and could be, like, more efficient. How, if we take Data Fabric and, you know, marry it with a broader AI strategy, is Data Fabric a capability that you're going to monetize, or is that a platform capability that you're going to unlock AI capabilities on top of?
We both. We are going to monetize it, just straight up. And then we're also going to unlock greater AI value. We're going to monetize it because if you want multiple data sources to be used by the Data Fabric, then you have to upgrade to the advanced tier. And then it's also going to be an unlock for AI value because we have an offering Private AI, as I mentioned. Our approach to Private AI is that we do not want to train the AI in advance. CIOs will back us up on this. They don't want to either. They don't like the idea of shifting their data into someone else's algorithm. They don't like the cost of it. They don't like the commitment of it. They don't like the inextractability of it.
There's a lot of security and financial reasons not to do that. So they're looking for a way they can get the benefits of large language models, of AI, without committing their data to a AI vendor. And there is a way. There's absolutely a great way. And we've been pushing it for a year since I wrote that article in the Wall Street Journal about private AI. What we're pushing now is, well, I mean, it's request-augmented generation, if you're familiar with the terminology. But if you're not, let me explain how it works. Imagine that your data is like 100 decks of cards, all right? Your enterprise has 100 decks of cards of data.
The traditional AI conventional wisdom is, "You just give all that to AI, and then it learns it all, and now when you ask it a question, you'll get a smart answer." Our approach is totally different. We give the AI nothing. We leave it totally untrained. There's no training whatsoever. And instead, when you want to ask a question of the AI, we look through the card decks ourselves. We find the one or two cards that pertains to the question. We hand the AI the question and the two cards. We say, "Okay. Answer this question with those two cards, please." And in fact, it works. It's very effective. You get great answers from AI using an untrained, plain vanilla AI plus a sorted, targeted data provision. The question is, "How do you get the sorted, targeted data provision?" And that comes down to Data Fabric.
So this special capability that we have is now a prerequisite for a certain kind of AI, a private kind of AI that keeps your cards, so to speak, close to the chest, close to the vest. And so we are taking our lead in Data Fabric and turning it into a lead in AI privacy, in short.
That's great. Let's bring Mark into the conversation and talk and see how we can map this story into some of the numbers. Maybe we start with next year's outlook, right? So I think you're talking targeting sort of at the midpoint about 13% total revenue growth, targeting approximately 20% cloud growth. That does imply a little bit of a decel versus what we saw in FY 2023. What are the underlying assumptions that underpin that guidance, and what are the factors that could come online that could potentially deliver upside to that guidance next year?
Sure. Yeah. The 20% cloud guidance is what I point people towards of it. That's, like, the pulse and heartbeat of our business. The total revenue line item has services in it, which we weren't actively trying to grow that, as we are the cloud subscription and the product, obviously. But if you look at our growth rates, after a little bit of a deceleration at times in 2023, we have a little bit of a rebound. And I think the, you know, the cloud growth rate for Q1, 2024 is more impressive than the full year. And you can extrapolate from that some caution around the full year, which I think is warranted. You know, even on a normal macro year, with visibility concerns, you definitely want to be a little bit more cautious for a full year.
We still think there's some macro component. So overall, I think we're happy to see some rebound in our growth rates. But I think also, very importantly, we're continuing on our trajectory and our plan that we've put out in terms of margins, right? And our glide path to breakeven is well underway. We're doing what we said we would do, and we're reaching a breakeven point this year and then improving upon that in the future as well.
I want to talk more about that margins, but I want to go back to that point around services. Back when Matt and the team took the company public, way back in 2017, it feels like it feels like yesterday. I mean, the business was sort of around 50%, you know, software, 50% services, and we're now, you know, north of a 70% software mix. What has enabled that, and where do you think that mix between software and services heads over the next year or two?
Yeah. In Q4, we were at 80/20. You know, it's a couple of things. One, we still think, you know, services are very important to Appian. But we have shifted a lot of our services to be more partner-friendly and kind of supplementing a partner-led delivery. And so these are services that customers are buying, perhaps in advance of the subscription agreement to get access to our really talented Appian experts, right? And so we're catering, you know, services to produce really successful customer outcomes. We have a very good track record of higher expansion when our services are engaged. And we see it as a very important thing to keep going after. That being said, we certainly are gearing our sales force towards the product growth, and that's where, obviously, the mix shift is continuing towards software. And we expect that to continue.
It's not going to stop at 80/20. We'll continue to see that, push forward even higher.
Let's talk about that margin trajectory as well. The EBITDA on margins were up, I think, 800 basis points last year. I think you're forecasting for another 500 basis points in 2024. To get to that 800 basis points, had you achieved that, and then what are some of the levers for further efficiency, to enable that 500 basis points, next year?
Yeah. I mean, in 2023, we certainly took a look at all of our OpEx, right? We said, "We're going to examine our cost structure, make sure our investments are paying off." We certainly disinvested some areas and doubled down on others. The whole notion being that we had to get a return on our spend, right? We were focused on our R&D center in Chennai, India, for example, as a way to leverage some cost benefit there. We did a lot of work around sales enablement. I think that work continues to try to get sales rep productivity up. That's helping our productivity, which I think is evident in the numbers as well, in the sales and marketing line item.
Overall, I think, a more kind of paced-out hiring process as well has helped contribute to margin expansion in and of itself. As a growth company, we're hiring, but we need to do so, responsibly and at pace with our revenue growth.
Matt, I think a lot of software companies have been focused on trying to become more efficient in this higher-rate environment. You've always been focused on, you know, yes, you know, building a sustainable model, but you've always sort of been focused on growth. As you've undergone this sort of efficiency process, and you're still obviously in the process of that, how do you feel like you've sort of sacrificed any growth opportunity, or are you just essentially getting more efficient and more productive?
Yeah. I don't think we sacrificed any growth capability at all. And I think it kind of taught us something. You'll look at how we were able to be careful and frugal and discriminating about where we spend. And in fact, there were plenty of ways that we could be more. So it was a good lesson. I think everybody's had their, you know, year of scrutiny or whatever, whatever it was, Zuckerberg said. And,
The year of efficiency, yeah.
Efficiency. Sorry. Year of efficiency. And yeah, I think we should just be in a consistent state of efficiency, actually. It's yeah.
Makes total sense. So I want to talk a bit about how you talked about how your pricing is evolving, something a little more simplified based on, like, you know, different, different tiers of pricing. Can you talk to us about how the go-to-market is evolving? And I, I think, you know, the spirit of the question comes from Q4, where the TCV of your top 10 deals, I think, was, like, up 70%, year-on-year in Q4, right? So it was a pretty impressive. So is there a move-up market? You know, how are you enabling that? How are you going? How are you how are you making that move further up market?
There is a very conscious move-up market. Yes. We are trying to target the market partly because we're seeing the greatest growth rates after the sale in our largest deals, partly because we think we have the greatest disparity of competitive advantage in those larger deals. It's where we are the most appreciated. It's also more cost-effective because our deals are long it takes a long sales cycle. So we'd rather spend that sales cycle and get a big deal than spend that sales cycle and get a small deal. So, yeah, that's very consciously done.
In terms of, also, like, sort of that time to value, which you guys have always been super focused on, can you elaborate on what the typical timeline, what that looks like from initial implementation to when customers start to see that payoff, and what those customers are like when the customer is, you know, satisfied with, you know, use case number one and wants to go to use case number two, three, and four?
We have an advantage here. We implement more quickly. We're more true low-code than our competitors are and say, "That's illustrated through the Appian Guarantee, whereby we promise that the first application can be live in eight weeks." We want to press that advantage. We're trying to accompany more of our sales with Accelerate, which is like, strategic oversight from expert consultants, right? We're going to try to, expedite our customer's time to value. Yeah. Not always does every partner want to do that, by the way. But we care about the reputation and the differentiation of the product. And, and so we want to move them rapidly through their first deployment so that they have momentum to do others. If that succeeds, I'd like to see, you know, higher NRR.
That actually reminds me of a question on sort of pricing. The old way of pricing, there was a couple, there was a, you know, per-user, seat-based element of pricing. There's also this time-based element. Hey, you get to build as many apps as you want for the first year. What were the learnings from those pricing experiments? And then how did you land on, you know, the pricing strategy that you have now, which is focused on, you know, different capabilities across different subscription tiers?
Yeah. I think it's just a matter of alignment. You've got to align the company with the sales force, with the customer. Everybody's got to understand the model. If you come up with something complicated or you're having trouble sort of coordinating everybody around it, then you're going to create more trouble than it's worth. And so I prefer not to talk about price. In fact, one of the principles with which I made this decision was to think, "I don't want to talk about price for a minute longer than I have to. Look, we lose on price, right? So why would we want to talk about that? We're not going to be the price leader. We're not going to be your favorite pricing package.
We want to move rapidly on to talk about value, talk about differentiation of feature set, customer experience, renewals, right, success in the market. We want to move that conversation. And I would rather our salesperson come to the customer and say, "I'm sorry, but this is the only package I can give you, but let's talk about something else," right, than to say, "I hear what you want. Let me go back to management. We'll work on that." It's just prolonging a conversation that isn't, in the end, to our advantage. So short and sweet.
Awesome. Net retention, I think historically, you guys typically say, you know, expect it to be in any given quarter between 110% and 120%, right? And it's been pretty nice, even despite the more typical, difficult spending environment. When you think about trying to get maybe to the upper end of that range on a sustainable basis, or maybe there's a world where that looks even better than 120%, what are some of the initiatives that you guys are doing to maybe unlock a faster pace of expansion? Is it new products? Is it the pricing element? What's some of the factors there that could drive better expansion?
First of all, I believe our NRR could be higher. We have an elite gross revenue retention and a relatively good net revenue retention. It's always seemed out of balance to me. I think that there's things we can do, reforms we can take in order to improve our NRR until it's as elite as our GRR. The way to do that would be the things you're talking about. It's product, right? It's iteration. It's better relationships. It's more opportunism within the customer site. It's definitely all those, but it's also uplifts. It's just raw uplifts. We have to get better at having a discipline around uplifts. And we've created a new unit within the sales department that will own that, will own pricing on renewal so that there won't be a kind of a I don't know.
If you delegate this to the account representative, they're likely to overlook the uplift because they want to create goodwill for the big new sale. And if I split that, then there can't be any log rolling, so to speak. Then we've got an entity whose total bonus is on uplifts, and they've got a higher guidance. But, it's my belief that it's true across enterprise software, but especially for Appian where we deliver so much value that our customers underpay for what we offer. And so I want to find gentle ways of making them pay more. So that's, that's what we're up to. In addition to greater products, in addition to greater relationships, we're also going to we're going to raise our price on renewals.
It makes sense. On that point, I think there's a certain set of use cases that Appian's well-known that can, you know, hit the mark on each and every time. Are there capabilities and use cases maybe they're vertical capabilities even, you know, across different industries? Are there things that Appian can absolutely deliver on that customers just don't think of Appian as delivering that capability that can be a, another way to sort of, improve or accelerate the customer expansion?
Yeah. There's a lot we can do, and we haven't tapped into most of it. My favorite frontier is solutions. I want us to build more solutions. My instruction to our solutions unit right now is build solutions as fast as you can, except that they all have to be wonderful. And that's a high bar, and it's going to constrain our growth. But we're going to build more solutions than we have before. When we do that, there's a lot of great effects that we differentiate ourselves. We illustrate it. We sell to a more cautious buyer. We have more pricing power. We have a faster sales cycle. It's just a great setup for us. We need to do more solutions. And that'll illustrate the use case. We're only going to go to places, of course, that we've already deployed.
When we enter a new solutions market, we're going to be developing based on what we've learned from having already landed in that market, satisfied some obviously unsatisfied demand, and had a successful cooperation with our customer. We're going to port that knowledge into a solution. What I typically find is with the power of our platform, the scalability, the interfaces, the self-improvement, like process analytics, the hot failover, the five nines of availability, you put together the things that we have invested in this platform, and it blows away a lot of niche leaders in sort of midsize software markets. We just have to show up in a meaningful way, and we can be a top player.
Obviously, there's the, you know, the selling part as well, but we can be a top product in some meaningful markets just by focusing our platform on that market. So I, I want to move solutions as quickly as we can.
I remember there was, like, you know, some attempts at this. I remember there was, like, a telco solution, a contact center solution, if I remember correctly, correct me if I'm wrong.
Yeah. It was a prior generation.
Prior generation.
I don't think that those solutions were fully baked, so to speak. I think they were kind of marketing vehicles, and they allowed for a lot of customization. They were, like, pieces and parts that you could put together. My intention now is to have solutions that you could turn on and run, right? It's a product. It happens to have a great deal of flexibility, but you don't need the flexibility if you don't want it.
Awesome. Let's talk a little bit about Fed. That's been a sizable vertical for the company historically.
That's right.
You've been there for a really long time. You know the space really well. Building on the recent in-process designation for FedRAMP High, for your government cloud offering, could you elaborate on the importance of achieving this certification and what potential more opportunities does that open up for the company in, in Fed?
You get a lot of the credit you need just by saying that you're in process. So the fact that we're in process now on FedRAMP High is half the battle. However, it does allow us access to new opportunities, new procurements, and those are largely, you know, DoD, high, high value, high security, obviously high barrier to entry. So I think it'll help us.
Is there, what's the reasonable timeline to achieving the high designation?
If they ask you to go back and do it again, it can be quite long. Like, I recall we got FedRAMP very quickly, but our rival Pegasystems kept hitting a wall. So hopefully, we'll sail right through, right? But I think I don't want to get out ahead of it, so just watch this space.
Awesome. In the last couple of years, when we think about, you know, point capabilities, RPA, workflow, process mining, task mining, there's been at least an attempt to go from an in you know, a siloed set of capabilities, to an integrative auto-automation suite. Where do we stand in terms of the market adoption of thinking about automation in that way and sort of an integrated set of capabilities? Or is it still sort of a best-of-breed? I buy, you know, Appian for workflow or get UiPath or Automation Anywhere for RPA. Are those markets truly converging, or is it still kind of a best-of-breed mentality out there?
I think the markets are converging, and I think they have to converge under the umbrella of process. So they can't converge on UiPath's terms. I can say that if we are in a best-of-breed world, then strangely, you know, if we're best-of-breed in process and UiPath is best-of-breed in RPA, it's weird how little we're asked to team up with UiPath. I think that UiPath brings a suite of functionality, which is bot-centric and more bottom-up in the organization, to the tasks that they do. And they do their tasks totally within their own functionality. And we bring our own top-down enterprise-grade functionality and a suite of capabilities to the jobs that we get. And we handle those entirely with our own functionality.
What I see is two different markets, maybe stratifying to the lower end and the upper end or the bottom-up and the top-down, but these are becoming separate markets. Whether you think about this convergence in a bot-centric view way or think about it in a process-centric way, that basically means you're thinking about it in one market way or another.
That makes a lot of sense. Let's stop here and see if there's any questions for the management team at Appian. If you just raise your hands, we'll get the microphone to you. Just one second. Just wait for the microphone, and then feel free to fire off.
Hi. I wanted to ask about the insurance settlement. Congrats. Great deal. One is how long do we expect this thing to play out? Like, do we can receive the $500 million cash? And who are the insurance companies who are willing to sell their put to you? What a great deal for you. What a dumb deal for them.
We, first of all, were able to pull from a broad range of top insurers in this market. And so there was great consensus around this. We didn't just do a bilateral deal here. This was we had to build a stack, a tower, they call it, right? You build a tower, and you get a major consortium participating in that tower. Now, I will say that the judgment preservation insurance market appears to have taken a sharp change in the last few months, and they will probably no longer be creating giant towers like the one that we just bought. So we've got a $500 million tower, and I love it, right? It's great to have that predictability, that cash backstop. We're really delighted to have that in place.
It takes away a lot of the variance that otherwise we would, you know, it could be $2 billion. It could be $0. It's like, now we know, right? Now we know what it is. We don't know when, but we know what. So it's a great thing that we got this under the wire. The industry has now changed, not because of us, but because I think they took a few major losses, and now the industry has become much smaller. Yeah.
Thank you.
How long do we expect?
But the timing? I have very little insight into that, actually. I don't know how long the process could play out. We might see a response from the appeals court in the upcoming quarter, but I don't know. It would just be typical, right? If we just looked at averages, it would probably be in Q2. But we don't have enough insight to say that with any confidence.
Great. Any other questions for the management team? Awesome. Let's pick on the competitive environment. And I think, you know, when I get asked about Appian and its competitive environment, I think there's, like, a lot of confusion. You know, people lead with Microsoft and the Power Apps portfolio. People worry about, like, ServiceNow. But there's also IBM and Pega. So, you know, out there on the ground, who are you seeing most, and how has the competitive dynamics between, let's just say, Appian, IBM, Pega, how has that element of competition changed or evolved over the past year?
Well, Pega specifically has pulled back from greenfield opportunities, and so we're less likely to see them in any place other than an existing Pega customer. Now, that said, we're contesting all of Pega's customers, so we see them constantly. We're both focused on financial services above all, it's our favorite market, both of us. And so we still see Pega more than anybody. However, the rise of the largest firms, the big tech firms, Microsoft, ServiceNow, Salesforce, they're a, you know, a big factor for us, especially over the last five years. And we have common advantages against them. We're real low-code, and they're mostly a scripting language. We allow for dispersed data, whereas they want to unify it and control it. We're more scalable than they are and fully featured than they are. So we've got a set of really clean differentiators.
Meanwhile, they can out-visibility us completely, right? They're so good. They've got a presence in every C-suite. They're so it's a battle of product versus go-to-market, really, in that case. And we just need to raise our profile enough to claim more business because anybody who compares us and has the budget for both is going to be well-disposed toward Appian.
So yeah. And so I'm thinking about maybe just focusing on sort of, like, let's say, the ServiceNow in the workflow automation space or even when we think about Microsoft because you are thinking about moving up market where a lot of those players play. What is the playbook that the Salesforce is going to be speaking to, you know, keep those win rates and, you know, secure those deals?
Yeah. You got to know how to climb the org chart. You have to know how to use executives to get high-level access and build partnerships. Partly, this is personal. People with these big ticket purchases, they're based on trust. You have to know our identity, the advantages that we've got as an organization, the feature advantages, which are superior. It's important feature advantages. We have to be able to set traps, like shape RFPs around features that matter to us, maybe get into a demo situation where we can show how much more quickly you can get to a product with Appian than you can with one of these scripter, you know, competitors. There is a playbook we need to learn. We're working on enablement in order to be sure that the sales force does learn it. But it's not like it's totally new to us anyway.
We do a lot of, you know, million-dollar deals. So we're going to draw on what we know from the successes we've had at the top end of this market and be sure that we're putting all of our energy there and not wasting energy on these small deals that, that take almost as long to sell, but then they come in at one-tenth the size. So I, I want to take that energy that I think was kind of wasted in the past and, and just hoist it up and focus it on big deals.
How does that influence, like, the profile of the salesperson that you hire? Are you looking for specific backgrounds who have maybe operated in these, you know, target customers?
I look for problem solvers, smart people, adaptive people, understand that you're going to have to create a solution in collaboration with the customer. You have to be a listener. You have to be a whiteboard person. You don't need to be an order taker. We're not looking to hire people from sales machines. They won't know what to do here. I do find that technical people do really well provided they also have high communication skills.
Awesome. So maybe let's end the conversation where we began, which is on the topic of AI. And, you know, there's increasingly talk about agentic architectures, right? Agents talking to agents, taking on actions on behalf of the business. I wanted to get your thoughts on, like, to what extent is that future a reality? What role will Appian play? Or do you sort of push back on the idea of, you know, an emerging, you know, agent-to-agent architecture?
First of all, I love it. In the degree to which it happens, it's going to be good for us because we can deploy AI agents as well as anybody. We can, furthermore, delegate to them specific tasks and check whether they've done it. So we have a process framework that would be ideal for using AI as a digital worker. And that's effectively what you're talking about. AI is a digital worker. We're very much in favor of that. I don't know the degree to which it will come true and whether the way that we communicate with AI will actually be a good way to communicate with an agent, right? English is loose. English is not concise, not precise, right? There's some flaws in English, and it tends to be so that AI constructed through English is best instructed to do very simple things.
Not all of our agents do simple things. So we will see how suitable that fit is, but we're ready for it, and we would benefit from it.
Awesome. Well, let's leave it there. Thank you so much, Matt and Mark, for joining us at the conference and giving us an update on the Appian story. I really appreciate it.
Thank you.
Awesome. Thanks.
Thanks, everybody.