Good day, and welcome to Appian's Q4 2024 earnings conference call. At this time, all participants are in listen-only mode. After the speaker's presentation, there'll be a question-and-answer session. Instructions will be given at that time. As a reminder, this call may be recorded. I would like to turn the call 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 Q4 2024 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 Q1 and full year 2025, 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. 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 unless 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. Reconciliations 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, and thanks everyone for joining us today. In the Q4 of 2024, Appian's cloud subscription revenue grew 19% to $98.9 million. Subscriptions revenue grew by 18% to $136.8 million. Total revenue grew 15% to $166.7 million. Our Adjusted EBITDA was positive $21.2 million, and our cloud subscription revenue retention rate was 116%. Our non-GAAP gross margin was 80% in Q4, our best performance since the IPO. For the full year, Appian's cloud subscription revenue grew 21% to $368 million. Subscriptions revenue grew 19% to $490.6 million. Total revenue grew 13% to $617 million. Our Adjusted EBITDA was positive $20.3 million. The world of AI is very exciting, but it contains an unsustainable imbalance, and all of you know what it is. There's a monstrous amount of investments in AI. The largest American tech firm spent nearly $250 billion of CapEx last year without a proportional return. AI doesn't generate enough revenue because AI doesn't generate enough value, and this is where Appian can help. Appian creates real value with AI by putting it where it can do the most good. While other firms bring work to AI, we bring AI to work. I mean, we go where work happens, and that's where we deploy AI. We equip AI to make an impact directly in the places where the heaviest and most valuable work already occurs. Work happens inside of a process. A process is a high-volume flow of tasks handled individually and procedurally inside a corporation. These tasks are carefully orchestrated to serve an important goal. Process is how an insurer manages claims and a bank validates money with it. It's how the government operates procurement cycles and pharma companies run clinical trials. Process is how organizations spend their money, serve their customers, comply with regulation, and build their reputations. Appian is called the process company, and we do a lot of processes. Appian runs 10-20 billion transactions per day on AWS alone. A lot of those transactions will run better when we apply AI. We used to staff our processes with digital workers like RPA and business rules. Now that we have AI, I believe that the value of process automation technology has rou ghly doubled. It will take years for that value to reach our addressable market, but it's real, and the value of AI can also double when it's used in a process. That is a bold statement, but if it sounds like an exaggeration that the value of AI could double when used in a process, then hear me out as I make the case for AI process synergy. Here are six ways AI is better when deployed in an Appian process. I'm starting on slide five in the earnings deck. First, it's easy to instantiate AI within an Appian process. To launch an AI agent in any node of a process model takes only a few clicks. Customers can use AI to make suggestions, generate content, parse documents, or take action. We're agnostic about the AI model. Customers can use ours, usually Claude, or bring their own. We're making it easier to access AI. And if DeepSeek commoditizes AI or makes it cheaper, we and our customers stand only to gain. Second, on slide six, our process gives AI structure. For AI to make value in high-volume workflows, it must have a structured role. Process gives AI a job within a coordinated effort working toward an important goal. AI gets a team of coworkers, an inbox and an outbox, an escalation path, exception handling, and human oversight. I want to emphasize this human-to-AI coordination. Many processes that can benefit from AI require humans as well, as overseers, exception handlers, or final results checkers. For example, one of our customers, an international health technology company, uses AI in a process to allocate human attention to incoming work. They sell medical devices and supplies to healthcare providers, and they're working with us to automate order fulfillment. A third of their orders are submitted through email, and those emails will be processed by Appian AI Agents, whose job is to parse, appraise, and route correspondence to the right actor within the organization. Many of these requests require a human response, so the AI will frequently assign the next stage of the work to a person. The third reason why Appian process is good for AI is data. AI needs data, and different implementations require different provisioning strategies. It's not always enough to make a heap of data and train your AI model once. Sometimes you need data from disparate systems, or you need fresh data in real time from remote sources of record, or you may wish to retrain periodically on a freshly assembled data set. If you're privacy-minded, you may wish not to train at all, but instead want data provided in the moment. Our process platform sends AI the right data at the right time. The fourth reason AI is better in a process is that we give agents what they need to be successful. Agents seek data, then act. First, they need to query and learn, and for that, our data fabric is ideal. Then they need to launch powerful actions. These actions should be far-reaching and coordinated and predictable and comprehensive and fail-safe. In short, they should be processes. Only a process provides the power and the guardrails agents need when taking action. Appian had agents before the term was invented. We called them skills, but we did it the right way with more structure and stronger actions. Those who let agentic AI improvise without guardrails are making a mistake. Here's an example from a top U.S. mortgage lender that became a new Appian customer earlier this year. It uses Appian to automate audit processes for over 10,000 loans annually. Our AI agents analyze hundreds of different forms and cross-validate data with the company's origination system. With 98% accuracy, the agents flag discrepancies so human auditors can review and correct the data before publishing loans to the secondary market. The company now runs this previously manual process more than four times faster using Appian. The fifth reason why AI is better inside a process platform is visibility. Everything that happens in a process platform like ours is tracked. Every node, every action, every delay, every read and write, every outcome. AI is typically a black box, but to understand it better, put it in a process. Then you can track what impact it has, what it does well or poorly, where it makes mistakes, where are its blind spots. And whatever you learn from this exercise, you can apply in the process platform, from rerouting certain jobs to gathering a new training data set. The data-rich environment of a process is great for validating your investment in AI and justifying your next project. And if you work in a highly regulated industry, this visibility might be a prerequisite to making any use of AI at all. Finally, my sixth reason, Appian makes AI scalable. A process platform isn't just a workflow. It's an application environment. Appian gives AI up-to-date security certifications, an interface usable on any mobile device, hot-hot failover, DDIL capability, and autoscale for usage spikes. That's why top global organizations run their most critical and complex processes on Appian. Our customers include over half the top life sciences, asset managers, and insurance companies, and every U.S. government cabinet-level agency. Speaking of the federal government, there's a lot of change in that market right now. We are cautiously optimistic about the opportunity these changes may create. For 25 years, Appian has been a vehicle for efficiency and modernization in the U.S. government. Our Army Knowledge Online deployment was, in its day, the world's largest intranet. We rescued a portion of the Affordable Care Act from a faulty technology implementation. We've become an acquisition management standard for civilian defense and state agencies. We advance efficiency from optimizing how money is spent to maximizing the efficacy of each action. For example, a U.S. military branch and longtime customer expanded its use of Appian into a new mission area this quarter. This group runs core operations like logistics, finances, and supply chain management on a series of legacy enterprise resource planning systems. The organization will consolidate these systems into a single Appian view for hundreds of thousands of users and expects to save tens of millions of dollars annually. Appian continues to upsell our existing customer base by launching new products and identifying new use cases. Two-thirds of our customers at the beginning of 2024 purchased more software during the year. We launched a tiered pricing structure last February to monetize advanced functionality like AI. Almost half of our new customers bought in above the base tier. Going forward, we hope to increase that share and to convert more existing customers. A leading U.S. insurance provider is one of our existing customers that upgraded its licenses in Q4. The group has been using Appian for more than a decade to manage risk and compliance and automate processes across its enterprise. The customer used Appian to expand its reinsurance business practice and generate an additional $2 billion in revenue annually. This quarter, the customer purchased a seven-figure upgrade and plans to widely deploy new capabilities like Appian AI agents. My last customer example is a medical transportation and emergency response company. I mentioned them in Q2 when they became a new Appian customer. The group has since reduced its appeal disputes processing times by 88% using Appian. Now the firm signed a seven-figure software deal in Q4 to integrate siloed systems and orchestrate its full claims lifecycle. And now I'll conclude my prepared remarks. This year, Appian's focus is on the basics, our core principles, our market identity, our financial goals, our strategic priorities, and our operational rigor. We believe we have an opportunity for growth, being a leader in a growing and changing market. Growth remains our priority. If you'd like to learn more about Appian, the best place to go is our annual conference, Appian World. This year, we're meeting in Denver from April 27-April 30. You're all invited, and I hope to see you there. Now let's talk about the financials with Mark. Welcome back, Mark. Thanks, Matt. And thank you to everyone joining us today. I'll review the financial highlights for the quarter, and then we'll provide guidance for Q1 and the full year 2025. We finished 2024 on a high note with our key metrics of cloud subscription revenue and Adjusted EBITDA coming in above the high end of our guidance ranges. Strength was broad-based across our key industry verticals with contributions from both new and existing customers. Cloud subscription revenue was $98.9 million, an increase of 19% year-over-year. Total subscriptions revenue was $136.8 million, an increase of 18%. On a constant currency basis, total subscriptions revenue grew a similar 18% year-over-year. Professional services revenue was $29.9 million, an increase of 1% 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 continues to be a strategic offering focusing on driving customer success and enabling partners. Over the long term, we expect professional services revenue to continue to decline as a percentage of total revenue. Subscriptions revenue represented 82% of total revenue compared to 80% in the year ago period and also 80% in the prior quarter. Total revenue was $166.7 million, an increase of 15% year-over-year. On a constant currency basis, total revenue grew 14% year-over-year. Our cloud subscription revenue retention rate was 116% as of year-end, compared with 119% a year ago and 117% in the prior quarter. We continue to target a cloud subscription revenue retention rate of 110%-120% on a quarterly basis. Our international operations contributed 35% of total revenue compared to 36% in the year ago period. Cloud software net new ACV bookings were approximately 65% of total net new software bookings in Q4 compared to 80% in the prior year. We had a higher mix of net new on-prem ACV in Q4 than prior periods, predominantly in the public sector. Let's turn to our profitability metrics. Non-GAAP gross margin was 80% compared to 78% in the year ago period and 77% in the prior quarter. Our subscriptions non-GAAP gross profit margin was 90% compared to 91% in the year ago period and 89% in the prior quarter. This margin remains best in class in enterprise software. Professional services non-GAAP gross margin was 31% compared to 26% in the year ago period and 30% in the prior quarter. Total non-GAAP operating expenses were $113.8 million, down 1% from $114 million in the year ago period. Adjusted EBITDA was positive $21.2 million versus our guidance of positive $6-$8 million and compared to a positive $1 million in the year ago period. Reasons for outperformance relative to our guide included greater than expected high margin on-prem revenue offset by lower than expected low margin professional services revenue. In addition, some of our forecasted Q4 cloud investments and employee-related costs were shifted into Q1, and our marketing spend was more efficient than previously expected. In the Q4, we had approximately $14.3 million of foreign exchange losses compared to $11.1 million in foreign exchange gains in the same period a year ago. We don't forecast movements in FX rates. Therefore, they aren't considered in our guidance. Non-GAAP net loss was $2.2 million or break-even $0.00 per share compared to non-GAAP net income of $4.9 million or $0.06 per diluted share for the Q4 of 2023. This is based on 74 million diluted shares outstanding for Q4 of 2024 and 73.3 million diluted shares outstanding for Q4 of 2023. Turning to our balance sheet, as of December 31, 2024, cash and cash equivalents and investments were $159.9 million compared with $159 million as of the close of the prior year. For Q4, cash provided by operations was $13.9 million compared to usage of $8.2 million for the same period last year. Total deferred revenue was $287.2 million as of December 31, 2024, an increase of 19% from the year ago period. As we have 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 even monthly. Due to the variability of our billing terms, changes in our deferred revenue are generally not indicative of our business momentum. Let me briefly recap our full year 2024 results. Cloud subscription revenue was $368 million, representing 21% growth year-over-year. On a constant currency basis, cloud subscription revenue grew 20%. Total subscriptions revenue for the year was $490.6 million, an increase of 19% compared to 2023. On a constant currency basis, total subscriptions revenue grew 18%. Professional services revenue was $126.5 million, a decrease of 5% compared to 2023. Total revenue was $617 million, up 13% compared to last year. Adjusted EBITDA was positive $20.3 million compared to a loss of $44.8 million in 2023. Non-GAAP net loss was $25.6 million in 2024, or a loss of $0.35 per diluted share compared to non-GAAP net loss of $59.2 million in 2023, or a loss of $0.81 per share. These figures are based on 73 million and 73.1 million diluted shares outstanding for 2024 and 2023, respectively. For the full year 2024, cash provided by operating activities was $6.9 million versus a cash usage of $110.4 million in the prior year. As a reminder, included in last year's cash usage was the one-time $57.3 million premium payment for the Judgement Preservation Insurance policy. We continue to believe cloud subscription revenue is a better indicator of our business momentum than billings or remaining performance obligations or RPO. The latter metrics can fluctuate based on the timing of invoicing, seasonality of on-prem license revenue, and the duration of customer contracts. The true scale of the business is represented by subscription revenue, which includes support and all software subscription revenue, regardless of whether the customer deploys to the Appian Cloud, their private cloud, or on-prem. Now I'll turn to guidance. For Q1 of 2025, cloud subscription revenue is expected to be between $97 million and $99 million, representing year-over-year growth between 12% and 14%. Total revenue is expected to be between $162 million and $164 million, representing year-over-year growth between 8% and 9%. Adjusted EBITDA for Q1 of 2025 is expected to be between positive $8 million and $10 million. Non-GAAP earnings per share is expected to be between $0.02 and $0.05. This assumes $74.7 million fully diluted weighted average shares outstanding. For the full year 2025, cloud subscription revenue is expected to be between $419 million and $421 million, representing year-over-year growth of 14%. Total revenue is expected to be between $680 million and $684 million, representing year-over-year growth of 10%. Adjusted EBITDA is expected to range between positive $38 million and $42 million. Non-GAAP earnings per share is expected to be between $0.17 and $0.22. This assumes 75.1 million fully diluted weighted average shares outstanding. Our guidance assumes the following. First, we expect that Q1 professional services revenue will be roughly flat compared to a year ago. For the full year, we expect professional services revenue will be approximately flat or will increase by a low single-digit rate compared to a year ago. Second, we anticipate that on-prem license revenue will grow by a low single-digit percentage on a year-over-year basis and will track seasonality that is consistent with prior periods. Third, we expect our Q2 Adjusted EBITDA to be a loss due to the combination of on-prem license seasonality and the cost of running our annual user conference, Appian World. Fourth, total other income and interest expense will be approximately $4 million in Q1 and $15 million for the full year 2025. Fifth, capital expenditures will be between $1 million and $1.5 million in Q1 and between $3 million and $4 million for the full year of 2025. Sixth, our guidance assumes FX rates as of February 10, 2025. Finally, we're making a change in 2025. We're removing foreign exchange gains and losses from our non-GAAP EPS calculation. And with that, we'll turn it to questions. Thank you. If you'd like to ask a question, please press star one one. If your question hasn't answered and you'd like to remove yourself from the queue, please press star one one again. Our first question comes from Sanjit Singh with Morgan Stanley. Your line is open. Yes. Thank you for taking the questions. And congrats on a strong end to 2024. On the Q4 performance, there did seem to be a lot of strength in sort of the on-premise business. You called out strength in the public sector vertical specifically, which sort of begs the question, just given all the uncertainty with DOGE and U.S. federal spending, what's sort of the underlying assumption in terms of the guidance about public sector overall, but U.S. federal going into next year? How do you feel about Appian's positioning in an uncertain U.S. federal budget environment? Well, we feel cautious about it. And that's our nature. In a state of uncertainty, we want to be careful. I cannot forecast the outcome of DOGE, the impact that those rearrangements are going to have. I love the principles of efficiency and modernization, but how those principles will translate into the buying environment, I cannot yet predict. And I think it's important, Sanjit, for modeling purposes that the 65% cloud, 35% on-prem was an anomaly. We expect that the ratio to go back to be consistently about 80% cloud and 20% on-prem for next year. We just had a couple of large deals in the public sector that skewed it. Great. And then just to follow up, Matt, on some of the case studies that you highlighted in your broader agent strategy. As we look into 2025, from a product roadmap perspective, what can we expect in terms of more skills? You announced a skills package in the last couple of years. But broadly, on the agent strategy, what can we expect the customer base to be seeing from an innovation standpoint on the agent front? Yeah. I pointed out that in the world of AI, there is an imbalance between excitement and results. And I think that as severe as that imbalance might be, it gets even stronger when you talk about agents. Our goal is to teach people that agents can be valuable when they're structured, when you've got guardrails, when their actions are far-reaching, when you narrow the chances that improvisation will occur and fail. We can make practical value. And I want to elevate that. I want to expose people to the value we're creating, the real value with agents. And so our goal is to show this practicality. Some of us like to say that our goal is to be boring with AI because real productive AI is less of a flight of fancy and instead just going to where the work already is and improving how we handle it with AI. It's kind of boring, right? It doesn't really change the way your business runs. It just makes it run a lot stronger. So our intention is to be practical and even boring in the way we solve real problems with these new technologies. Okay. Those thoughts, Matt. Thank you. Thank you. Our next question comes from Steve Enders with Citi. Your line is open. Okay. Great. Thanks for taking the questions this morning, and Mark, good to hear you back on the call here. I guess I want to start on the AI point and, I guess, follow up on the prior question. But I guess, how do you kind of see this dynamic playing out of customers, I guess, kind of understanding the Appian approach to AI and understanding kind of embedding the agent experience into the process pipeline versus, I guess, other approaches that are out there in the market? Yeah. I think we've got first of all, everybody thinks about AI in a different way. Some people are thinking Copilot. Some people are thinking chatbots. Some people are talking about Agentforce. We're thinking about AI in a distinctive way. And I believe that the way we approach it stacks up very well, value-wise, results-wise, against any other vision around the way AI should be used. Ours allows you to deploy AI to where work is happening and therefore to put it right in the midst of things. AI shouldn't stand to the side and be your butler and help out when something anomalous happens or it deserves to be in the absolute center of work. If, as an economy, we're going to spend as much money as we're spending on AI, this should be an absolute centerpiece to the way we address big flows of work, and so I think our approach is intuitive and even obvious when you think about it. Where does AI belong? Of course, it belongs exactly where the greatest amount of work is done and value is created, so that's our philosophy, and we're going to make our case through demonstrations. We're going to make our case through publicized success stories and word of mouth. That's how we'll win this argument. Okay. I guess maybe that dovetails into the next question, just on the changes in the go-to-market that have taken place over the past year or so and the new CRO coming in. I guess, how are you kind of feeling about productivity rates from the changes that have been made? And how are you kind of thinking about further evolution of the go-to-market moving forward? Yeah. Well, first of all, I feel great about the progress we're making. And we're getting back to first principles, right? We're bringing focus and discipline and leadership, and we're getting the right people doing the right things. And I'm very encouraged by the movements that we've made. And I think that higher productivity can only result from building good foundations. That's great. Thanks for taking the questions. Thank you. Our next question comes from Derrick Wood with TD Cowen. Your line is open. Great. Thank you. Matt, I guess my first question, when it comes to data fabric and tapping into various data sources to bring more intelligence into the Appian platform, can you talk about what the common data sources customers are looking to get access to and what vendors or systems you're working closely with when it comes to building connectors and APIs and trying to bring more different data sources into the Appian platform? Yeah. First of all, we see this as a major advantage for our technology over other firms. Our ability to access the distributed data that exists in every major enterprise differentiates us from our competitors who typically wish to assemble the data to aggregate it in one place or under their control before they can properly learn from it or interact with it. So, we're reaching across the enterprise, relational databases, systems, important software, textual repositories, especially with AI. Text has become a really important source of information. We're a universal connector, and we're broadly integrated with all these systems. And I think that that tolerance for data diversity gives us an edge. Got it. Thank you. Maybe one for Mark. Just hoping to get a little more color on demand trends across core verticals, financial services, government, life sciences, how the quarter went, how you're feeling about pipelines, and even underneath some of those verticals, areas like insurance and pharma, I think, are newer focuses. Just checking in on traction there as well. Well, I'd say that the four key verticals, financial services, public sector, insurance, and life sciences. I'd say that the performance for Q4 and the pipeline were equally distributed among those top four. We also have success in other verticals like energy or manufacturing and education, etc. But those are the top four. So pipeline looks pretty good, and the performance speaks for itself. Okay. Thank you. Thank you. Our next question comes from Raimo Lenschow with Barclays. Your line is open. Hey, thank you. Congrats from Barclays. Great Q4. Two questions, one for Matt, one for Mark. Matt, if you think about the AI and your offering, I saw your presentation was really kind of thorough and gave us a good idea. But the question I ask, how do you think about pricing your agents and how is pricing evolving around AI with these agents? Is it kind of outcome-based? Or per seat, etc. Could you talk about your thinking there, please? And then one for Mark. Your NRR on cloud ticked down a touch again. I know it's a lagging indicator. Where do you think that number settles down or was there anything in Q4 that might have impacted that number? Thank you. All right. I'll go first. With regards to how do you price agents? So you price them by usage. That seems to be where the industry is coming down also. It's just a request flow to agents. However, I'll add that we're going to subsidize the use of agents for the time being. So we're going to encourage customers to make more use of them so that the value can be demonstrated so that we can have a higher volume of adoption. So what our eventual price may be and what our price is right now may not be the same. And as for the NRR, it bounces around a little bit. Raimo, you know that. It's well within the range that we've stated, 110-120. And I think more importantly, the gross renewal rate's 99%, which is best in class, right? Yep. Okay. Thank you. Our next question comes from Nick Altmann with Scotiabank. Your line is open. Awesome. Thank you. Matt, you mentioned half of net new customers bought in above the base tier for the new tiered pricing structure. And so can you maybe just talk about the installed base and how those customers are resonating with the new tiered pricing structure? And is there any way to think about what percentage of the installed base is on the new tiered pricing structure today and where that could head in 2025? Yeah. Let me comment on this. We did not go after our installed base very hard with the new pricing structure. We did not disrupt the contracts and commercial relationships that we had in place in order to impose that structure. I feel like that the best opportunity to bring our installed base higher is when there's a feature they feel that they need, and if we can make a good enough case around certain AI functionality, that might be the inflection point we need to bring them willingly onto the new price structure, and then there's some other possibilities as well, but I'd love to see us do more with the installed base. We absolutely have our eye on that. I think that they've honestly got a nice consumer surplus that we'd like to split with them, and we're looking for ways to craft and share with them a pricing system that will allow us to benefit from their success. Okay. Great. And then just going back to Steve's question around the go-to-market, but can you just maybe talk about the messaging to the go-to-market function coming out of sales kickoff? Are there any new incentives or tweaks in place this year versus 2024 that you'd be willing to share? Yeah. Hey, that was the best sales kickoff we've had in five years, the one we just had. And it was the best because it was focused on the fundamentals. As I say, straightforward things, but things you've got to get right. Right people doing the right things, basics of who we are, what we stand for, what our customers benefit, how to find leverage and monetize it. It was the core things. And there was a... I came away from that very encouraged about where we can go. The funny thing is we're asserting these fundamentals in the midst of a moment when there's so much opportunity. The change, the greater value that we're creating right now, the need for clarity in a marketplace that's echoing with messages about AI. It's essential that our identity, like the process company, and our message, right, focused on putting AI in a process, be extremely intuitive and clear. That's the kind of thing that we're getting across to the team. You ask about the incentives. Yeah. The incentives have been tweaked, definitely, right? We've got more incentive for the most important is larger deals, right? We're shifting incentives in order to motivate larger transactions and more strategic adoptions. That's the most essential thing that's came out of our new incentive structure. But yeah, I feel that all of it's pointing in the right direction. Great. Thank you. Thank you. As a reminder, if you'd like to ask a question, please press star one one. And our next question comes from Devin Au with KeyBanc Capital Markets. Your line is open. Great. Thanks for taking my question. Maybe just one for me. I kind of wanted to get an update on solutions, particularly around the GAM suite. I mean, you mentioned you saw particular strength from federal in Q4. Curious how the adoption of GAM suite has been trending, but also kind of what are your expectations around contributions from that in 2025? Seems like that product would be really well positioned under increasing efficiency focus from the federal government. Thank you. I feel the same way about the potential for GAM. And I can back it up somewhat by saying that we had a substantial pipeline. We don't get into specifics about pipeline, but we had a strong and historically strong for any solution that we've ever done, pipeline in GAM coming into the year. And of course, that's before the DOGE activities and the intense focus on efficiency that we're seeing now. So I like where we stood at the top of the year. We've got a lot of adoption. We have the credibility of successful deployments, and we have a best-in-class product. Thank you. There are no further questions at this time. This concludes the program, and you may now disconnect. Everyone, have a great day.