Thank you for standing by and welcome to Appian Fourth Quarter 2023 Earnings Conference Call. [Operator Instructions] As a reminder, today's program is being recorded. And now I'd like to introduce your host for today's program, Sri Anantha, Vice President, Finance and Investor Relations. Please go ahead.

Thank you, operator. Good morning and thank you for joining us to review Appian's fourth quarter and full year 2023 financial results. With me today are Matt Calkins, Chairman and Chief Executive Officer; and Mark Matheos, Chief Financial Officer. After prepared remarks, we will open the call for questions. You can follow along with our earnings presentation by downloading it from the main page of our investor site at investors.appian.com. During this call, we may make statements related to our business that are forward-looking under federal securities laws and are made pursuant to the Safe Harbor provisions of the Private Securities Litigation Reform Act of 1995. These include comments related to our financial results, trends and guidance for the first quarter and full year 2024, the benefits of our platform, industry and market trends, our go-to-market and growth strategy, our market opportunity and ability to expand our leadership position, our ability to maintain and upsell existing customers and our ability to acquire new customers. The words anticipate, continue, estimate, expect, intend, will and similar expressions are intended to identify forward-looking statements or similar indications of future expectations. These statements reflect our views only as of today. They do not represent our views as of any subsequent date. They are subjected to a variety of risks and uncertainties that could cause actual results to differ materially from expectations. For a discussion of the material risks and other important factors that could affect our actual results, please refer to our most recent annual report on Form 10-K, quarterly reports on Form 10-Q and other filings with the SEC. These documents are also available on our Investors section of our website. Additionally, non-GAAP financial measures will be discussed on this conference call. Refer to the tables in our earnings release and the Investors section of our website for a reconciliation of these measures to their most directly comparable GAAP financial measures. With that, I would like to turn the call over to Matt.

Thanks, Sri and thanks, everyone, for joining us today. In the fourth quarter of 2023, Appian's cloud subscription revenue grew 26% to $81.3 million. Subscriptions revenue grew by 24% to $115.8 million. Total revenue grew 16% to $145.3 million. Our cloud subscriptions revenue retention rate was 119%. And our adjusted EBITDA was a gain of $1.0 million. For the full year, Appian's cloud subscription revenue grew 29% to $304.5 million. Subscriptions revenue grew 21% to $412.3 million. Total revenue grew 17% to $545.4 million. Our adjusted EBITDA was a loss of $44.8 million. I want to mention 2 milestones at the top of this call. Last year, for the first time, our revenue exceeded $0.5 billion. Second and an interesting complement to the first observation, we achieved the highest non-GAAP gross margin in our public history last quarter at 78%. In our presentation deck, we've included one last time the special bonus metrics, we tracked quarterly in 2023. We didn't get the recession I expected but there were some macro complications and you can see it all starting on Page 5. Last year was the year of AI talk. Now the conversation will shift to more tangible things, shift features, successful deployments, practical value. That change will be good for Appian. We have a distinctive approach to the AI market based on years of leadership and existing technology. We are focused specifically on the application of AI to data. We're leaders in data fabric which is like a virtual database, uniting the customer's enterprise. And we are leaders in AI and now we will be leaders in the combination of these 2 things. I think everyone understands by now that AI is only as good as the data behind it. More data, better AI. Appian has an open data strategy…

Thanks, Matt. I'll review the financial highlights for the quarter and then we'll provide guidance for Q1 and the full year 2024. We closed 2023 on a strong note with revenue and adjusted EBITDA coming in above the high end of our guidance range. We saw continued healthy contribution from existing customers and strong growth from key industry verticals. Let's go into the details. Cloud subscription revenue was $83.1 million, an increase of 26% year-over-year and above guidance. On a constant currency basis, cloud subscription revenue grew 23% year-over-year. Total subscriptions revenue was $115.8 million, an increase of 24% year-over-year. On a constant currency basis, total subscriptions revenue grew 21% year-over-year. Professional services revenue was $29.5 million, down 9% year-over-year. As previously noted, services revenue can be volatile from quarter-to-quarter and a few large projects can influence performance. Our professional services will continue to be a strategic offering, focused on enabling partners and driving customer success. Long term, we expect professional services revenue to continue to decline as a percentage of total revenue. Subscriptions revenue was 80% of total revenue, compared to 74% in the year ago period and 76% in the prior quarter. Total revenue was $145.3 million, an increase of 16% year-over-year and above our guidance range. On a constant currency basis, total revenue grew 13% year-over-year. Cloud subscription revenue retention rate was 119% as of December 31, 2023, up from 115% a year ago and 117% in the prior quarter. As a reminder, we continue to target a cloud subscription revenue retention rate of 110% to 120% on a quarterly basis. Our international operations contributed 36% of total revenue, compared to 34% in the year ago period. Our cloud software net new ACV bookings were approximately 80% of the total net new software bookings in 2023, consistent…

[Operator Instructions] And our first question comes from the line of Sanjit Singh from Morgan Stanley.

Congrats on a solid end to the year. Matt, as you think about 2024 and coming out of 2023, what are you seeing in your demand environment in your pipeline as it relates to this momentum around automation and getting practical value of AI? What are some of the use cases that customers are starting to pursue with Appian versus maybe some of the other initiatives out in the space?

Right now, AI is a fantastic door opener but it's best done with a very simple proposition. So we're equipping our team to be able to approach the customer innovate [ph] kind of an easy to understand, easy to implement way to get in on AI and show rapid benefits. I believe that keeping it simple and having a short period of investment before you get the payoff is essential to catalyzing their large interest in the topic today; so that's helpful. I also feel good about where the pipeline stands and particularly the large end of the pipeline. As you know, we're focused a little bit more on those larger opportunities now.

Yes, that makes a lot of sense. And then Matt, for you, I mean, the positive adjusted EBITDA in Q4, that was really nice to see. When we think about the balance between expense -- or managing margins versus growth, what's the potential for that to continue from what we saw in Q4? Is any -- or said another way, would the Q4 sort of bend the benefit from any sort of shifting in expenses to get to that positive adjusted EBITDA in Q4?

Do you want to take that?

Sure. Yes. No, we really didn't do anything out of the ordinary to get to a positive adjusted EBITDA in Q4. That was an artifact of our strong revenue performance. We had a really good level of linearity in -- on the top line. And we're just on our plan here on the expense side that we've discussed in the past and we're steady as she goes on that in terms of operational discipline. But the name of the game is still growth for us. We're just doing so with a lot of scrutiny on our expenses to make sure we're getting ROI we need and running a tight ship. But there was nothing out of the ordinary for Q4 in that regard.

And our next question comes from the line of Steve Enders from Citi.

Thanks for taking the questions here. I guess maybe just to start, just maybe thinking more broadly about kind of the bigger demand environment and kind of what you're assuming kind of for '24. I know that for 4Q, there's extra conservatism kind of baked in for government shutdown and some other things. But I guess, what are you seeing today in kind of the deal environment and what's kind of being assumed in the outlook here for '24?

Okay. So broadly, the deal environment. I still think that there's some macro disruption but it never rose to the level of a recession. I think that there's genuine interest across the board and what we can do for them with AI. I think that there's recognition that we're creating real value and that sparks expansion opportunities and it propels demand for our industry, not just for our organization. I think this is a workable demand environment. I think this is a demand environment that we can succeed in.

Okay, that's helpful. And then maybe just on the, I guess the kind of the net new versus customer expansion. I guess, for one, it's really good to see the net retention number pick up here. I guess maybe what drove the strength of the expansion here in the quarter? And how do you view the sustainability of that moving forward? And what's being embedded into the guidance for '24?

All right. Now we don't make any guide on NRR. I am also pleased to see it tick up. However, it hasn't ticked up that substantially. It's a couple of points. And I don't want to dwell on that. That's a blip for now. Maybe we can make it a trend but it's a blip for now. I do think that it's something we want to excel in. We want our -- we want to see more expansion. And we are focusing more on the techniques that lead to expansion, deepening the relationship that we have with our clients, having more touch points, having more exposure, emphasizing our humanity in contrast with the big tech substitute, sort of what they might conceive to be a substitute for Appian technology. I think we want to shine in the ways that we are naturally advantaged against our larger competition. And we do that by having the sort of pervasive human connection. And that's the sort of thing that will lead to more expansion if it works. So this is an important number to me but I don't want to make any implications about where it's going.

And our next question comes from the line of Jake Roberge from William Blair.

Congrats on the solid results. Matt, I know it's early but can you talk about how you see monetization shaping up for some of the new Gen AI solutions and data fabric? Could those initiatives start to drive any growth heading into 2024? Or is it still too early for that?

We have a monetization strategy for both of those features. We have a stratified pricing system whereby you pay more for data fabric if it's accessing multiple data sources and more for AI, or specifically for Private AI. So we are absolutely expecting that these features will drive a revenue differentiation. Not just volume, not just retention, not just a competitive advantage but also tagging them with revenue.

Okay, helpful. And then, you've made some changes to your go-to-market organization over the past year or so, between leadership changes, a small restructuring and then also just the deeper focus on the partner organization. How do you feel like the go-to-market motion is positioned as you head into this year?

I feel like we're a lot stronger than we were a year ago. That's how I'd read it. I think that we've been careful with the changes that we made last year but they've been changes for the better.

And our next question comes from the line of Derrick Wood from TD Cowen.

This is Cole [ph] on for Derrick. You flagged good strength in the TCV for top 10 net new customers. Could you just unpack that a little bit and talk about what drove that strength?

Yes, all right. Well, first of all, I think part of it is driven by our strategic focus. We believe we belong in the big organizations doing mission-critical things at relatively higher price points. And that strategy, I think, has something to do with the fact that we're seeing higher TCVs on our top 10 deals and for that matter, higher on our median deal, right? We're just trying to raise the target sites a little bit and we're seeing that that's happening. So yes, I'll just say it's strategically aligned, right? It's not unintended. And I don't want to make any promises about where it's going, just to say that it was gratifying to see it come in where it did because that's what we intended.

And our next question comes from the line of Kevin Kumar from Goldman Sachs.

I wanted to ask about the international public sector and the traction you're seeing there. Maybe talk a little bit about the go-to-market investments you're making there. And higher level, I guess, how early are these public sector organizations in terms of thinking about AI and kind of implementing more intelligence into their workflows?

As you know, we're a Washington company and I'm looking at the beltway out my window right now as I take this call and we've done a lot of business here in Washington, D.C. with the federal -- U.S. federal government. And the international public sector has always represented a big opportunity for us. And for that matter, so has state government in the U.S. and it is a largely untapped opportunity. We -- I did mention in the prepared remarks one substantial organization in the state government level that works with us and does hundreds of millions of dollars of procurement every year on the Appian Platform. That's great but that's the beginning. This is tip of the iceberg stuff. And even though we have notable wins in other -- the international or non-federal public sector opportunities, I still feel like the penetration is so minimal. We've done just enough to prove we can do it and not enough to show what we can do, like how much we can do. So that's an opportunity. We look forward to moving into. We're making an effort to move into it. And it's largely unsaturated right now.

[Operator Instructions] Our next question comes from the line of Frederick Havemeyer from Macquarie Capital.

I wanted to ask about data fabric in a little bit more depth here about, generally speaking, it seems like being in the enterprise data space and data integration space right now is a fantastic bit of positioning considering what enterprises are trying to do with their data and trying to make it useful. And of course, everyone is trying to have a Gen AI strategy. So I'm curious with data fabric, when you're helping customers implement this, what have been the most significant challenges that you're helping them to address? And also around that, what are the most significant challenges that you or your partners face when implementing an onboarding customers to data fabric?

Yes, all right. First of all, you have to open up their imaginations. The typical organization does not imagine that it will be possible to merge data silos and to have synthesis or combined benefit from them. We're so used to an enterprise software landscape that is dominated by the walls, right? That is cut into silos. You have to -- you first just tell them that it's possible. And then secondly, the integration. Sometimes it's easy. Sometimes it works with APIs and it's very intuitive. And in some cases, the entities could have been custom-built or very out of date and then integration is a bit more of a challenge. But once -- it's not so difficult to overcome once you convey the benefit, we can easily stitch these data silos together. It's simpler than one might imagine. And it's very fully featured. You can read and write, you can filter by individual permission access. It's actually a really powerful layer. By the way, the strength of the data fabric is such that I expect that this year, more organizations will start saying these words, data fabric. They'll claim that they've got something like it. And I suspect that what they have is not going to be fully featured the way what we've built and have had for years is. It's an artifact of our divergent data strategy. Many of our competitors have a data strategy whereby they seek to claim to unify and to own the data in an enterprise. And they are big enough in some cases to pull that off, to use their size, their leverage against their customer and to force a kind of an aggregation under their own flag. We do not attempt that. Instead, we have always had a, call it, pro customer, if you like, an open data strategy that respects and empowers and enables the customer's existing data architecture. And that's why we got into this data fabric concept in the first place, is because we wanted to be the vendor that would enable the customer to have the data the way they wanted to have it, instead of trying to force it all into our database. So we have taken this -- we've built this technology because we first took this decision to be the sort of company that would enable to disperse data strategy. And because our rivals have largely not taken that decision, they have also not developed that technology. I think that because this is the result of different beliefs about how the market works, it might be a more persistent technology division than it might initially appear.

Matt. I wanted to ask also, on both renewal rates and net retention rates, understanding also, like you said earlier, that a couple of data points does not yet a trends make. But I wanted to ask, it looks like your total gross renewal rate ticked down slightly in 2023 by quarters, while your cloud subscription revenue retention rate ticked up. So I wanted to ask, is there anything happening between the total company business and cloud that would be worth calling out at this point that could be attributable to that?

Yes. First of all, I want to address that downtick. Our gross revenue retention rate did indeed downtick from 99% to 98%, bottoming at 97% and it's now risen back to 98%. And I just want to clarify that though that may have been a downtick, is still best in class. It's still remarkable numbers. And then secondly, I want to say there has been, I would say, just a little bit of migration, just a very small amount, from on-premise to cloud, at a point when I thought there wouldn't be any more but there was just a little bit. And so that may be impacting the numbers a small amount.

Our next question comes from the line of Thomas Blakey from KeyBanc Capital Markets.

I have a couple here. Maybe first on the heels of Fred's great question on the data fabric, I think he also asked about the actual use cases, if you could maybe double click on that, Matt. And then after answering that, if the company -- as we're hearing an uptick from our calls on Gen AI, especially in the enterprise, if these customers don't use your data fabric, what are these organizations going to do architecturally in terms of breaking down silos/bringing all their data together? Is it something akin to Appian solutions or compared to a cloud-based data warehouse like Snowflake, or -- I just want to understand like the pros -- if they don't use you, what are they going to have to use in terms of launching these Gen AI enterprise applications given the examples? That would be great.

No, that's a great question. Like what are they going to do without data fabric? Well, Snowflake is one obvious example. Snowflake is asking, give us all your data. It's like a modern data warehouse. Just pile everything you can into this one data source. And when you do, we've already got a partnership lined up for Gen AI on top of it. That's fine, if you can move all your data there, if you can move all of it. But, boy, I talk to a lot of CIOs and I can't remember any of them saying that they could move all of their data or even all of their pertinent data into a central repository, Snowflake or anyone else's. So typically, today, AI either runs on one giant silo, like Snowflake, or all you can train which I'll address in a moment, or a data fabric. If it's all you can train, then essentially you're saying that AI isn't going to run on a source. It's just everything you can upload, right? So you can upload one source after another if you want but you've got data loading costs, you've got data freshness issues, you've got variable levels of personal security access to that data issues. There's a lot of flaws with that strategy. And I think also just the idea of training at great length an algorithm that the CIO does not own is problematic for a lot of tech decision-makers. So I think that even though there is the data lake with Snowflake strategy and there is the train an external algorithm on everything pertinent strategy, these are not plausible strategies. And what I see happening, in the absence of data fabric, most of the time, is AI is too limited on the data it knows. AI runs on one silo and just one. And I think that is, unfortunately, the typical fallback in the absence of data fabric.

That's interesting. Any use cases that you've seen maybe sprout out early in the evolution or planning to in '24?

Well, you mean use cases for data fabric? Yes, most of our customers actually use data fabric. We've got a terrific usage rate, somewhere 80%, 90% which is good for a participation in a feature. Because it's so beneficial. It makes it easy to connect to data sources; like even if you're using just one, it makes it intuitive and simple. But if you're using multiple, it's a huge step forward over what was possible in the past. And it also makes it far easier for a user to develop new applications because we objectize all of the data that's been touched by the data fabric so that a creator of a new report or process can just grab and drag and drop that object. All of these objects of data across the enterprise are now sort of draggable objects within the development environment. It just makes creation of new artifacts really intuitive. And as for use cases, it really the challenge is more thinking of cases where you don't need more than one data source. I mean I mentioned one in my prepared remarks about the hypothetical students in need of rescue, right? And how it would be great to be able to know whether they've attended their classes or missed a tuition payment or had friends who have dropped out or had bad grades, or any of that, like all of those things are going to exist in different systems. So even a simple application like how can we help the student to do well is something that's a natural use case for data fabric.

Excellent. And just a follow-up to that, my final question would be, at last year's Appian World, you expanded your partner programs and reach there pretty significantly from what my understanding was. Where is Appian's infrastructure in your mind today in terms of reaching out to enterprises along these lines in terms of the sales motion? Do you have the right point of go-to-market infrastructure that touch -- had these touch points in large enterprises to sell this kind of Gen AI solution in terms of the data fabric? It would be my last question.

No. Well, we definitely did a strategic pivot on partners last year. We had 700 registered partners coming into the year. And we still do have a ton of partners. But we decided that we wanted to focus, really focus down and make big investments in partners that were willing to make big investments in us. And that beneficial reciprocity is the pattern that we have set going into 2024. I think it will be more motivational and it will allow for a level of commitment in our partner that leads to greater expansion, because it will be greater implementation quality as well.

This does conclude the question-and-answer session of today's program. I'd like to hand the program back to Sri Anantha for any further remarks.

Great. Thank you, Jonathan and thank you all for joining us today. We look forward to seeing you -- many of you at upcoming investor events and on our next earnings call. Thank you and talk to you soon.

Thank you ladies and gentlemen for your participation in today's conference, this does conclude the program. You may now disconnect. Good day.