Appian Corporation

Welcome to the Appian First Quarter 2025 Earnings Conference Call. All participants will be in the listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today's presentation, there will be an opportunity to ask questions. To ask a question, you may press star, then one on your telephone keypad. To withdraw your question, please press star, then two. Please note, this event is being recorded. I would now like to turn the conference over to Jack Andrews, Vice President of Investor Relations. Please go ahead.

Good morning and thank you for joining us. Today we'll review Appian's First Quarter 2025 financial results. With me are Matt Calkins, Chairman and Chief Executive Officer, and Mark Lynch, Interim Chief Financial Officer. After prepared remarks, we'll open the call for questions. During this call, we may make statements related to our business that are considered forward-looking. These include comments related to our financial results, trends and guidance for the second quarter and full year 2025, benefits of our platform, industry, and market trends, our -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. These statements reflect our views only as of today and don't represent our views as of any subsequent date. We won't update these statements as a result of new information and less required by law. Actual results may differ materially from expectations due to the risks and uncertainties described in our SEC filings. Additionally, non-GAAP financial measures will be discussed on this conference call. Reconciliation of GAAP to non-GAAP financial measures are provided in our earnings release. With that, I'd like to turn the call over to our CEO, Matt Calkins. Matt?

Thanks, Jack. Thanks, everyone, for joining us today. In the first quarter of 2025, Appian's cloud subscription revenue grew 15% -over-year to 99.8 million. Subscriptions revenue grew 14% to 134.4 million. Total revenue grew 11% -over-year to 166.4 million. Our cloud subscription revenue retention rate was 112% as of March 31. Adjusted EBITDA was 16.8 million. A strong follow-up to the prior quarter's adjusted EBITDA of 21.2 million and a continued demonstration of our inherent earnings potential. We held our annual conference last week, Appian World. Our focus was squarely on AI and AI agents and how AI can be deployed inside a process to deliver practical value. I appreciate the many customers who spoke about their experiences with Appian, the value they created using Appian AI and the success they achieved. Speakers from Aon, NASA, and MagMutual shared stories of how their organizations optimized processes with Appian. Newberger Berman revealed it onboard tens of billions of dollars in funds faster with Appian. Hitachi reported reducing operating expenses by 20% using Appian. A claim autism uses Appian to ingest medical documents, accelerating its patient intake process by 83%. My keynote was about bringing AI to work. By that I mean finding the place in your enterprise where work is heaviest and most important and deploying AI there. We focus on AI the worker, not AI the helper. In order to make AI a worker, you must integrate AI into a business process

because

that's how the most critical work is done by teams taking coordinated action. We don't believe in asking AI to make staggering leaps of creativity, not in 2025 anyway. Instead AI is for doing regular work with superhuman efficiency. Things like document intake and response, which AI can do faster and better than anyone else. My favorite conference session was called saving millions with boring AI because it pretty much sums up our approach to AI. Straightforward, even boring and immensely productive. We focus on practical results over hype. But don't let our use of the word boring fool you. We're getting incredible results. 70% of our cloud customers have adopted AI. We grew year over year production AI usage last quarter by 7.9x, not 7.9%, 7.9 times. We had more AI usage in Q1 than in all 2024 put together. It's natural that the focus of the AI revolution would shift to supporting technologies like processes. The major AI models are convergent. The most important decision in AI applications may be not which AI you use, but how you deploy it. Our belief, as you know if you've heard me before, is that AI should be deployed in a process. In an Appian process, AI is easier to deploy, safer, and more powerful. Appian makes AI easy to adopt. For example, a leading Australian insurer deployed an application to ingest documents and automate underwriting processes using Appian AI. Before Appian, hundreds of underwriting specialists spent days manually processing quotes with limited accuracy. Now in minutes, our AI classifies documents and extracts data with over 96% accuracy so the insurer can quickly open and progress cases. Customer expects to run these processes 50% faster and generate millions more dollars in revenue annually. Last year, Appian launched a multi-tiered pricing model that allows us to monetize AI and other exclusive features. Since then, nearly half of our new logos have purchased the AI-inclusive upper tiers. Revenue from these AI-inclusive tiers more than doubled in Q1 relative to Q4, rising to $9 million. This is not yet a large share of our quarterly subscriptions revenue, but it demonstrates our early moves to monetize AI and our customers' willingness to pay for it. Our customers become more efficient when they use our platform. An association of US financial regulators is one example. This group is an existing Appian customer. Its state regulators process thousands of product filings annually, 50% faster when using our platform. This was even without AI. In Q1, it expanded its use with a seven-figure software deal to upgrade its existing licenses to our new pricing model and deploy Appian AI. Our AI classifies each document and extracts pertinent data from each filing. Now the group expects to eliminate manual verifications and save tens of thousands of labor hours annually. The central message of my keynote involved AI agents. I explained the three primary behaviors of an agent. It thinks, it acts, and it learns. And I explained why Appian agents have an edge in all three behaviors. I'm going to walk through them right now, briefly. First of those three behaviors is thinking. Thinking refers to exploring data with repeated queries of disparate sources to decide on the best course of action. The more data an agent can explore, the better it will think. Appian's data fabric allows the agent to roam the entire enterprise of data, not limited to a single silo or data source. Our data fabric is industry-leading functionality adopted by 97% of our incoming cloud users. Our data fabric gives agents more than universal access. It also grants them speed because our queries are automatically performance-tuned, and security because we run those queries with the appropriate user's credentials. Due to a surge in AI-related usage, data fabric queries are up 166% year over year to nearly 7 billion queries in Q1. The second part of my behavior list is acting. Acting is the second thing that these agents do, and it refers to an agent implementing its decision. Appian's agents act exclusively through processes. That's all they can do is launch processes. No surprise there, because we are a process company. Processes are a great way to take action. They are complex compound actions, potentially triggering dozens of separate work items by dozens of different workers. So they are powerful. But they are also safe. Processes are auditable and predictable. They provide guardrails. If processes are the best way for agents to take action, Appian has a distinct advantage. We run 16 billion transactions per day on our processes. Finally, there's think, there's act, and there's learn. So last one is learning. Learning means that an agent benefits from the knowledge of past results. If you want to learn from past results, you must start by remembering them, and Appian monitors everything that happens in our processes. How much time did it take? How much did it cost? Was it successful? We track all these things. Our process mining capability gives us an edge in collecting data for the benefit of our agents. The more you know, the more you can learn. For example, a large US healthcare system will use Appian to simplify operations for hundreds of medical facilities. It will start by analyzing a series of patient-focused processes, like medical procedure pre-authorizations and denials, to reduce overhead costs by 20%. Appian Data Fabric will consolidate data from a dozen systems, so the group can use our process mining tools to identify key bottlenecks. The group will use these insights to prioritize an IT roadmap of workflows to automate with our platform. Appian does business in the United States public sector. We have a large presence in the federal space and are thus exposed to whatever disruption DOGE may create. But we are also tightly associated with DOGE's primary virtues, efficiency and modernization. We remain cautiously optimistic about the evolving opportunity. In Q1, our federal government bookings, including both new software and services, grew 59% compared to the same period last year. Appian has a long history of delivering value within the government. The Department of Labor, for example, saves tens of millions of dollars annually using Appian. Appian applications are mission critical. The government procures $464 billion in annual budget on the Appian platform. We offer a solution called Government Acquisition Management, or GAM. GAM helps agencies automate highly regulated processes for procuring goods and services. Last year, Appian launched ProcureSight to complement the suite. ProcureSight is an AI-driven website. It applies AI to several major public data sets so government professionals can glean insights from past procurements to help generate new ones. Over 80 federal agencies and sub-agencies use the service today to make their procurements more cost-effective. We continue to sign new customers and win big expansions in our key verticals. Here's some examples. First, a U.S. civilian agency purchased a seven-figure software deal and became a new customer this quarter. It selected our platform to manage investigations for tens of thousands of mail-related crimes annually. Before Appian, the group manually consolidated case files because its legacy system was disjointed and incomplete. Now, Appian Data Fabric will seamlessly integrate data from dozens of systems so federal agents can focus on advancing investigations. We won this competitive deal because we were the only vendor to meet all the customers' requirements during our custom demo. Next, a U.S. agency supporting the Department of Defense catalogs and manages nuclear inventory using Appian. This quarter, it chose to modernize its procurement office and purchased our GAM solution. Before, contracting officers manually tracked requirements on spreadsheets and custom tools. Now, they'll process hundreds of millions of dollars of annual procurement budget on Appian. We won this deal because the customers' peer organizations recommended our solution. My final story is about a top Australian bank that became a new Appian customer this quarter. It'll use our platform to modernize customer service processes like credit card disputes and customer account updates. Appian AI will ingest nearly 75 million document pages annually, and Appian Data Fabric will consolidate data from all related systems into a single workflow tool so service agents can reduce their SLAs from hours to minutes. It's important to me that Appian's investors know Appian's intentions. So I'll share with you now two essential internal metrics which we'll report on quarterly going forward. The first is what we call weighted rule of 40. This is the most important number that we manage the company towards. It's a combination of growth and margin, like a typical rule of 40, but we weight growth twice as much as margin. In the current quarter, our weighted rule of 40 score is 27, which is the sum of four thirds cloud subscription growth plus two thirds adjusted EBITDA margin. I explained the math so you can see that the factors add up to two, just like in a regular rule of 40 metric. Some Appian executives have weighted rule of 40 targets today, and all of them will over the next few quarters. Appian's other top objective to increase sales and marketing efficiency. This became my primary objective in 2023, and after much work we're seeing some results. This Q1, our net new bookings per sales rep, rose more than 30% compared to the same period last year. We want to share our progress with you using a new metric. See slide four in the presentation called GTM productivity. That's -to-market productivity. It measures the bang for our buck in sales and marketing. The numerator is the sum of total revenue and the quarterly changes in short-term deferred revenue over trailing 12 months. The denominator is trailing 12 months non-GAAP sales and marketing expenses. As you'll see on the chart, we're showing steady progress. Appian hired Serge Tanga as our new chief financial officer starting later this month. Serge has over 20 years of financial experience, most recently as senior vice president of finance at MongoDB, where he led financial planning, strategic finance, business operations, and analytics, and then as their interim CFO. I'm excited to welcome him to Appian's executive team. I thank Mark Lynch for serving as our interim CFO during this search. He'll remain on Appian's board of directors. With that, I'll hand the call over to Mark for a deeper discussion of our financials. Mark?

Thanks, Matt, and thank you everyone joining us today. I'll review the financial highlights for the quarter, and then we'll provide guidance for Q2 and the full year 2025. Appian exceeded the guidance ranges we provided on our key metrics of quad revenue, total revenue, and adjusted EBITDA. Quad subscriptions revenue was 99.8 million, an increase of 15% year over year. Total subscriptions revenue was $134.4 million, an increase of 14% year over year. On a constant currency basis, total subscriptions revenue grew 15% year over year. Professional services revenue was $32.1 million, flat growth compared to the first quarter of 2024. As a reminder, services revenue can be volatile quarter to quarter. We continue to expect professional services revenue to decline as a percentage of total revenue over the long term. Subscriptions revenue represented 81% of total revenue compared to 79% in the year ago period and 82% in the prior quarter. Total revenue was $166.4 million, an increase of 11% year over year. On a constant currency basis, total revenue grew 12% year over year. Our quad subscriptions revenue retention rate was 112% as of March 31, 2025, compared to 120% a year ago and 116% in the prior quarter. We continue to target a quad subscriptions revenue retention rate of 110 to 120% on a quarterly basis. Our international operations contributed 36% of total revenue compared to 37% in the year ago period. Cloud net new ACV bookings were approximately 82% of total net new software bookings in Q1 consistent with the prior year. Let's turn to profitability metrics. Nine gap gross margin was 78% compared to 76% in the year ago period and 80% in the prior quarter. Our subscriptions nine gap gross profit margin was 89% compared to 90% in both the year ago period and prior quarter. This margin remains best in class in enterprise software. Professional services nine gap gross margin was 30% compared to 25% a year ago period and 31% in the prior quarter. Total nine gap operating expenses were $114.8 million, down 2% from $117.3 million in the year ago period. Adjusted EBITDA was positive $16.8 million versus our guidance of positive $8 to $10 million compared to an adjusted EBITDA loss of $1.3 million in the year ago period. This out performance relative to our guide was largely driven by taking a measured approach to hiring, prioritizing low cost regions for hiring and by greater than expected term license and services revenue. Nine gap net income was $9.8 million or 13 cents per diluted share compared to a nine gap net income. This is based on 74.1 million diluted shares outstanding for the first quarter of 2025 and 73.3 million diluted shares outstanding for the first quarter of 2024. Turning to our balance sheet, as of March 31, 2025, cash and cash equivalents and investments were $199.7 million compared with $159.9 million at the end of the year. This is the total deferred revenue of the year ago period compared to the end of last year. For the first quarter, cash provided by operations was $45 million compared to $18.9 million for the same period last year. Total deferred revenue was $262.5 million as of March 31, 2025, an increase of 16% from the year ago period. As we stated on past calls, the majority of our customers are invoiced on an annual upfront basis. We also have large customers that are billed quarterly or monthly. Due to the variability of our billing terms, changes in our quarterly deferred revenue are generally not indicative of our business momentum. We continue to believe cloud subscriptions revenue is a better indicator of our business momentum than billings or remaining performance obligations, RPO. The latter metrics can fluctuate based on the timing of invoicing, seasonality of self-managed license revenue, and the duration of customer contracts. The true scale of the business is represented by subscriptions revenue, which includes support and all software subscriptions revenue, regardless of whether the customer deploys to the Appian cloud, their private cloud, or on-prem. Before discussing guidance, I'll share a few observations about macroeconomic and business conditions. The US dollar has weakened since we last provided guidance, which now gives Appian a currency tailwind. Appian exceeded the high end of our Q1 guidance for cloud revenue and toll revenue. And at this point in the year, we have not seen any material changes in our sales pipeline or the cadence of our business. Given the macroeconomic uncertainty, changes within the federal government, and thus a wider range of potential outcomes, we're taking a prudent approach to guidance for the remainder of 2025. For the second quarter of 2025, cloud subscriptions revenue is expected to be between 101 and 103 million dollars, representing -over-year growth between 14 and 16 percent. Total revenue is expected to be between 158 and 162 million dollars, representing -over-year growth between 8 and 11 percent. Adjusted EBITDA for the second quarter of 2025 is expected to be between negative five and negative two million dollars. Non-GAAP earnings per share is expected to be between negative 15 and negative 11 cents. This assumes 74.8 million fully diluted, weighted average shares outstanding. For the full year 2025, we are increasing the high end of our previously stated guidance range regarding cloud subscriptions revenue and total revenue while maintaining the original low end of those guidance ranges. We're also increasing our overall adjusted EBITDA range for the year. For the full year 2025, cloud subscriptions revenue is expected to be between 419 and 423 million dollars, representing -over-year growth of between 14 and 15 percent. Total revenue is expected to be between 14 and 15 percent. Adjusted EBITDA for the second quarter of 2025 is expected to be between 680 and 688 million dollars, representing -over-year growth of 10 to 12 percent. Adjusted EBITDA is not expected to range between positive 40 and 46 million dollars. Non-GAAP earnings per share is expected to be between 18 and 26 cents. This assumes 75.1 million fully diluted, weighted average shares outstanding. Our guidance assumes the following. First, we expect Q2 professional services revenue to be flat compared to a year ago. For the full year, we expect professional services revenue to be approximately flat or increased by a low single-digit range compared to a year ago. Second, we anticipate term license revenue will decrease by a low double-digit percentage on a -over-year basis as we anniversary a difficult comparison from a strong Q2 2024. Third, we expect Q2 adjusted EBITDA to be lost due to the combination of term license seasonality and the cost of running our annual user conference Appian World. Fourth, total other income and interest expense will be approximately 3.5 million in Q2 and 14 million for the full year 2025. Fifth, capital expenditures will be between 1 and 1.5 million dollars in Q2 and between 3 and 4 million dollars for the full year 2025. Finally, our guidance assumes FX rates as of May 2, 2025. Now, we'll turn the call over for questions. Operator?

Certainly. We will now begin the question and answer session. To ask a question, you may press star then 1 on your telephone keypad. If you are using a speaker phone, please pick up your handset before pressing the keys. If at any time your question has been addressed and you would like to withdraw your question, please press star then 2. At this time, we will pause momentarily to assemble our roster. The first question comes from Sanjit Singh with Morgan Stanley. Please go ahead.

Thank you for taking the questions and congrats on the continued progress on the profitability fund. It's really nice to see. I wanted to ask about the good government performance this quarter. To what degree was there any sort of potential pull forward into Q1 ahead of some of the uncertainty around ordering patterns due to DOGE? And then as we think out into Q3, the federal government and the fiscal year spend, what sort of the baseline assumptions that you guys are making with respect to the U.N. federal budget spending periods?

All right. Thank you for the question. First of all, I don't believe pull forwards to have been a meaningful factor in Q1. I'm not aware of any pull forwards. So I hesitate to say I'm sure it was zero, but I don't believe it to be meaningful. With regards to Q3, we understand that there's a higher variance this year on the federal business than there have been in previous years. But so far we're on the good side of that variance. And I think that we're keeping possibilities open. We're cautiously optimistic about how Q3 will be.

Awesome. That's great to hear. And then Dustin has a follow-up if I look at sort of the cloud net retention rates, certainly within the range that you guys have talked about historically, 110 to 120, it did dip down more meaningfully in Q1 and doesn't sound like that's coming from the government side of the house. Any sort of spending hesitation you're seeing on the enterprise commercial side of the business that drove that net retention rate down four points quarter over quarter?

Not really. First of all, it's a reminder that this is a trailing metric. It's basically 12 months over 12 months. So it's backward looking. Basically a couple of things happened. There was some down cells in Q1 of 2024 that are working their way through the calculation now. And they're predominantly unrelated down cells. And also we had some revenue growth rates and some of the customers level off during the recent 12 month period. So those kind of conspired to lower the rate a little bit.

I appreciate

the color. Thanks, Mark. Our next question comes from Ramo Lenzchao with Barclays. Please go ahead.

Perfect. Thanks for the clarity on federal and congrats on the quarter. Matt, I wanted to ask on AI and the new agentic world. How do you like, and I appreciate you as a founder. You always think more of a bigger picture than a lot of other guys. How do you think this new world is going to play out? You clearly have a lot of success, but there's obviously a lot of noise of marketing noise in the market of people. Everyone is doing agents now and agentic, etc. How do you think, like what's ultimately the big thing for a customer and how you fit in there? Then I have a follow up for Mark.

Yeah, this agent's topic it's both the most important application of AI and as such an exceptionally worthy topic for conversation and development. And at the same time it's overstated and the market is still dominated by more hype than results. And so we're at pains to differentiate ourselves from that. And the fact that we rely mostly on customer stories to make our point and that we use words like boring. This is all an intentional sort of disassociation that we're trying to make between our approach which is result centric and customer focused and using AI to practical effect versus the sky high hyperbole that we're hearing from some vendors. I keep figuring that now is the moment when the hyperbole is going to melt away and people are going to care about actual results. And I think that we stand to benefit when that change happens. When people start allocating, sorry, people start paying attention to agents for their impact. Agents are actors, they're the actors of the AI world. AI should be taking action. We believe in AI the worker. This is exactly what we're here for is to use AI to do work. But that work has to be regulated and audited and guard railed and provisioned with information and tracked. And so you need all that structure. You need all the structure around AI. You can't just make an AI agent and let it loose in the enterprise. And therefore I view the process infrastructure that we provide as a prerequisite for productive application of AI agents. Simply a prerequisite. And to the degree that anyone else is going to make value with their agents, it's going to be because they approximate the functionality even if they don't achieve the functionality that we're providing with our process infrastructure.

Okay, perfect. And then one quick one for Mark. We can't even think on the, you know, like I know Billings is not really a measure that you focus on but like some of the investors are still kind of paying attention to. Was there anything in Q1 that kind of impacted Billings in terms of timing, etc.? Thank you.

Nothing really to call out.

That's clear. Thank you.

The next question comes from Steve Enders with Citi. Please go ahead.

Okay, great. Thanks for taking the questions this morning. I guess to start, I mean good to hear on the AI side, good to hear the solid usage, expansion year over year and it was pretty clear coming from the conference what that was looking like. But I guess I just want to ask on how you're feeling about incremental kind of monetization. I think you called out 9 million or so in the quarter coming from the AI tiers that you have available. But just how do you feel about that usage that you're seeing driving incremental revenue opportunities and adoption of those plans moving forward?

Yeah, I am pleased with the willingness of customers to spend on AI. I think there's a recognition that this is creating great value. And so that's moving along nicely. Partly you could make a case for not even trying to monetize at this point in the life cycle of a feature as powerful as AI. I think we're moving toward monetization a little sooner than I might otherwise planned just to try to create a demonstration of the tangibility of the results we're creating. Because I feel like we need that contrast with the market. We want to show that this is real and that our customers appreciate it. So while I could understand not trying to monetize it, I also think that it's a good idea for us to demonstrate that in order to just make a statement. And yeah, the value is there for sure. It's a wonderful value. As I estimated last quarter, I feel like our cam has doubled in the wake of AI, which is the best thing that's ever happened to the process automation industry.

Right, no, that's very clear. Great to hear. And then just on new with SIRS coming on board and new CFO starting later this month, I guess what's kind of the mandate or the key area of focus for him as he starts to get ramped up in the role? I guess it's kind of a piece of that. How are you kind of viewing the ability to drive margin or kind of the levers to drive margin moving forward here?

Yeah, let me say that I'm really excited to have SIRS coming on board. He's an exceptional addition to our team. I don't want to preempt our strategy by talking about it right now. I think there's a lot of great opportunities where we're going to make substantial progress and I see him as a contributor across the board. Yeah, let me just stop at that.

Okay, perfect. Thanks for taking the questions here.

Our next question comes from Jake Rubash with William Blair. Please go ahead.

Yeah, thanks for taking the questions. Great to hear that those AI SKUs hit 9 million in the quarter.

Can you

talk about the use cases or areas of the platform that are driving the most demand on that front? And then is there any sense of how large of a pricing uplift you can see for those solutions on just a per customer basis?

Yeah, that's right. Well, we've got it priced at 25% uplift and that may fluctuate, but right now that's our easy we're just asking 25% to add AI. As for the primary use cases, well, they're, as I said in the comments, they're regular work. They're regular work that otherwise could be done in a rote manner, but AI is just so terrifically good at it. It's processing documents and gathering information and making simple decisions that you might have otherwise tried to delegate to a person or a business rule set. Intake is just terrific at document intake. It can read anything at this point. It can read ripped receipts or handwritten notes or emails or faxes or whatever you've got coming into your organization. It can respond, it can sort, it can extract data. These are, the theme here is that these are rote jobs. These are straightforward, simple jobs done at high volumes with exceptional efficiency. As opposed to a lot of the stories you hear about how AI is supposedly supposed to be used without thinking people. I couldn't disagree more with that right now. AI is a fantastic worker to place in the middle of the heaviest work and the most important work that your organization does. That's where we want to put it.

Okay, that's helpful. And then data fabric queries, I think we're up 166%. I think you start monetizing that solution when customers connect it to multiple data sources. So can you talk about how that's progressing? And then there's also some other players in the market that are obviously talking about other data fabric solutions. So can you help us understand how your data fabric compares and contrasts to those?

You know, it is so important to emphasize how our data fabric is different. Because the need for a data fabric has become so important, now everyone is using the term. But what they have is not, in general, what I would have called a data fabric. But we're talking about a semantic layer similar to a virtual database that allows you to interact with data objects across the enterprise as if they were local objects. The semantic layer makes them local, effectively. They can be viewed and queried and manipulated and combined in a local manner. It's not just a layer of integration. It is far more than that. It's a semantic layer that makes everything you integrate into a local addressable object. Secondly, it's read and write. Third, it's performance tuned. Fourth, there's a security layer. So you're running queries under variable credentials, depending on who's answering the question. This is probably our best feature, along with process itself and the integration of AI with process. Let's put this in some kind of a, you know, call of fame top three features. It's an extraordinary piece of functionality and it is strictly differentiated from anything on the market today that goes by the name of data fabric that I'm aware of.

That's helpful. Thanks for taking the questions.

Our next question comes from Nick Altman with Scotiabank. Please go ahead.

Awesome. Thank you guys. I wanted to circle back to the nine million dollars of AI revenue. How are you guys thinking about contribution from AI in 2025? And can you just maybe talk about the net new ACV that's being driven by AI just to kind of help us think about where that can shake out in 2025?

Yeah, that's right. Well, we're going to continue our push to bring customers to the higher tiers, the AI-laden tiers. We've done that mostly focusing on new customers over the past year. We're broadening that into a campaign to bring existing customers to higher tiers as well. Though as you saw from my notes, a few have already made that jump. We are also going to transition, and our whole industry is going to transition away from per-seat pricing, that's my prediction, because per-seat pricing is going to move in the opposite direction with AI success. So we're going to need to price by something else. It could be nodes, it could be cases, it could be consumption of some sort, and within a solution or a highly understood context, it could be value or value correlates. So we're all going to be adopting different pricing mechanisms in order to capture AI as an upside instead of effectively having it as a downside as it removes necessary seats. So there's going to be a little bit of a pricing transition across this industry this year, and we're thinking a lot and carefully and we're on the way to making that careful transition.

Okay, great. That's helpful. And then the net new bookings per sales rep up more than 30%. That's encouraging, and we're starting to see some of those efficiencies show up in the margins. I guess my question is how durable do you think some of those productivity gains are through the rest of the year? Because on one side they're very encouraging and can help out that weighted rule of 40 target you outlined. On the flip side, you guys are relatively early and kind of running a leaner -to-market motion. Maybe some of that pipeline was generated when you had a larger sales force. So any color you can provide on kind of how durable those sales productivity gains are as you get through the rest of the year, I think that would be really interesting.

Thanks. Great. Well, I don't wish to quote any targets on the metrics that we've recently revealed, including the ones that we will be reporting on next quarter as designated. I would sooner classify them as durable than non-durable according to your terms. I don't believe that they are dependent upon a larger pipeline gathering force. I believe that they instead stem from recent innovations, superior efficiency, better account targeting, larger accounts, selling higher, conveying value first. I think that they're the new habits and the new seriousness and tension that we have brought to the sales organization, the terrific professionalism that we are bringing. These are the real factors and these are enduring factors.

Great.

Thank

you. We have our next question from Derek Wood with TD Cowan. Please go ahead.

Great. Thanks, guys. This is Cole. I'm for Derek. I just want to start off on the -to-market. It sounds like you've made some good progress in efficiencies. I'm just wondering how much of that is coming from this renewed channel focus and narrowing the scope of channel partners versus direct reps?

The narrowing of partners is an example of something that's very successful, demonstrably, measurably successful last year. We motivated a small group of our most trusted partners to seek business with us and it dramatically expanded the partner-generated pipeline in 2024. We continue that because it has worked so well. I saw more evidence of how well it was working last week at Appian World. Our partners are enthusiastic. Those that are focused partners are working hard to maintain that designation. Those that are not are working hard to gain it. We also have another category called champion partners that lead us into a new market. I see a boom of interest for partners, especially if they're not focused partners, on becoming champion partners so that they can receive our attention in at least one market. This has been a great motivational tool, a great alignment tool with our partners. We will certainly keep it up.

Great, thanks. Just to follow up on the GAM suite, could you just remind us if there's any sort of ACV uplift that comes with that in a cell, what would that be? Thanks.

The GAM suite has a price. It isn't so much an uplift, it's a separate product. The GAM suite has a price, I don't know if it's published, it might be on GSA, but it's substantial. If you want the GAM suite, it's going to be a seven-figure, for sure, a seven-figure per year proposition, no matter how small your organization. So it's a meaningful sale when we place it.

Appreciate

it, thanks.

The next question comes from Devin O. with KeyBank Capital Markets. Please go ahead.

Great, good morning Matt, good morning Mark. Thanks for taking my questions here. I want to first off start with some of the exciting product announcements that came out of Appian World this year. When I talk to the customers at the conference, it seems like intelligent document processing and extraction, that has been a really widely adopted product among the customers. Could you maybe share more on what's been driving success in adoption there? Any learnings you can kind of port over to some of the new AI agent offerings that you can maybe replicate the success you've seen at IDP?

I'm

glad

to hear you enjoyed the product announcements at Appian World. I was incredibly excited. I felt like all four of the major features that I announced could have been the headline feature at a typical annual conference. Of course, they were all AI related. Most of them were agent related. But there was also the one composer that allows you to create a new application through the use of AI, having AI be the author of the application. And that was exceptionally well received. And I can absolutely love that. That's been receiving some of the best feedback I've ever seen. With regards to IDP or intelligent document processing, this has long been our number one AI use case. Like literally for years, this has been number one. And we made it sharply better in this latest round of advancements. IDP used to be a feature that you trained per document. So if you had a format of document coming in, you would train the AI to recognize it and know where to extract different pieces of information. The new version, you don't have to train on any format of document. It just figures it out. So you can give it something in handwriting or in a novel format or an email or whatever it is. It could be in the wrong language. And AI is just going to figure it out. And the level of accuracy with which it does that is astonishing. It's both more adaptive and more accurate than anything we've been able to offer in the past. And customers really love it. I build it in the conferences, read anything. I said you can call it IDP, but you can also just call it read anything.

I appreciate the context there. Really helpful. And then just a quick follow-up, I do want to dive a little bit deeper into comments around public sector. It seems like things are still going well. And you were cautiously optimistic and you mentioned bookings growth of 59% in the quarter. I mean, how did that bookings performance compare to your internal expectations in the quarter? And any color on how that figure kind of compared last quarter, maybe last year? Anything you can share would be helpful. Thank you.

Well, it is a -over-year comparison, of course. And I would say that that exceeded my expectations. But I'm sticking with cautious optimism. That's what we said word for word last quarter. And I think it's the right position to take right now. And I'm glad that the numbers are bearing us out, but I don't want to get out ahead of them. I want to just let this story tell itself.

Another factoid out there is that the federal revenue, the federal government revenue grew -over-year 21% versus the total revenue for Appian during the quarter was 11%. So that strong revenue growth as well.

Got it. Really appreciate the call there. Thank you.

Thank

you.

We have no further questions at this time. The conference has now concluded. Thank you for attending today's presentation. You may now disconnect.