Appian Corporation (NASDAQ:APPN) Q2 2023 Earnings Call Transcript

Appian Corporation (NASDAQ:APPN) Q2 2023 Earnings Call Transcript August 3, 2023 Appian Corporation misses on earnings expectations. Reported EPS is $-0.39 EPS, expectations were $0.42. Operator: Good day, and thank you for standing by. Welcome to Appian Second Quarter 2023 Earnings Conference Call. At this time, all participants are in a listen-only mode. After the speakers' presentation, there will be a question-and-answer session. [Operator Instructions] Please be advised that today's conference is being recorded. I would now like to hand the conference over to your speaker today, Sri Anantha, Senior Director of Finance and Investor Relations. Please go ahead. Sri Anantha: Thank you, operator. Good afternoon and thank you for joining us to review Appian's second quarter 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. Today, you will want to follow along with the earnings presentation. You can download 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 third quarter and full year 2023, 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 subject to a variety of risks and uncertainties that could cause actual results to differ materially than expectations. For a discussion of the material risk and other important factors that could affect our actual results, refer to our 2022 10-K, our 2023 10-Q filings and other periodic 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 to our CEO, Matt Calkins. Matt?

Matt Calkins: Thanks, Sri. In the second quarter 2023, Appian's cloud subscription revenue grew 30% year-over-year to $74.4 million. Subscriptions revenue grew by 22% to $93.8 million. Total revenue grew 16% year-over-year to $127.7 million. Our cloud subscription revenue retention rate was 115% as of June 30th. Our adjusted EBITDA was a loss of $24.7 million. These results exceeded our guidance. Best thing about this year so far has been the rise of AI into public consciousness and general interest. It is a pleasure to take customer questions to speak about it in every form and to write about it in the Wall Street Journal and also, of course, to have this reason to initiate new selling conversations. Appian has been an AI leader for years. We have developed shipped and deployed AI for years. We use it throughout our product, but now it's getting the attention it deserves. Customers now recognize the potential, but they still need guidance to achieve practical value. Appian sees the AI market a little differently from other firms. I'll summarize the difference with two quick statements. First, AI is a partner and not a substitute for human labor. We need to work together. Businesses can expect to be routing tasks to and from AI as we collaborate. Appian's leadership and workflow is advantageous here. Second, data is everything. AI could make your data more valuable, but it's also a threat to data privacy. The top priority now should be to protect and defend an organization's own data. Appian facilitates a private form of AI that will keep us differentiated from the public versions offered by our competitors. Let's explore for a moment that second point. AI allows data to be real-time actionable. It is, in a sense, the natural culmination of the data warehousing movement from the '90s. AI provides a new data structure that can make a vast amounts of information instantly accessible by reducing the excess costs, it increases the value of data. Common imagination suggests that companies will be happy to send their data and their prompts to public AI firms and any lingering concerns about that can easily be fixed with a few contractual terms about not retaining the data or a promise to redact the sensitive bits before sending it across the Internet. I'm skeptical of this belief. And the conversations I've had with CIOs suggest I'm not alone. The more sensitive your data and the more regulated your industry, the more you're going to need private AI. Every firm will set their own AI privacy standards, but I know what I'd be looking for. One, no third-party access to my data. Two, my data shouldn't be kept or used by anyone else. And three, I'd want to own every AI algorithm I trained, not rented. From what I see, no vendors in our market are seriously pursuing such a customer-first pro-privacy position, no vendors other than Appian that is. Appian has 2 big advantages in the emerging AI battleground. We have a leading data fabric, which can gather data sets for training and AI algorithm. Our data fabric is like a virtual database, a great way to address and unify data that statistically separated. And we also have a great process modeler to route work to and from AI. We plan to lean on these two factors to create practical AI value for our customers. We're creating practical AI value today with prebuilt models. Our most popular models automate the extraction of data and classification of documents and e-mails, building more models now, including one we just released to summarize request for quote responses. Here's a customer story about how one of our prebuilt models is used. A US fire safety company is under executive mandate to standardize its financial processes and reduce payment errors by the end of this year. In Q2, the group selected Appian to automate its accounts payable process and became a new customer. It will train an Appian AI model, classify unique documents, identify vendor invoices and extract payment information. Employees will review AI outputs and tune the algorithm all within a single app. They anticipate a five-fold increase in efficiency using our product. Their first project will be delivered in eight weeks under the Appian guarantee. The story is also a good example of our belief that AI and humans will work in collaboration, on most processes AI will become a more prominent member of process work, but not a substitute for the process itself. That belief matches our skill set. Appian has been a leader in process automation for decades. Our platform orchestrates work across different agents like humans, business rules, RPA and AI. Late last year with economic clouds looming, I began sharing a series of metrics to provide additional transparency on how macroeconomic factors might impact our business. You can see them starting on slide 4 of our earnings presentation. They don't say a lot this quarter. The bottom line is that there is some macro effect, but not enough to knock us off the plan we set for 2023. I'll close by sharing a few large customer examples from Q2. A global insurance provider and existing Appian customer has grown by acquisition. It needs to unify global operations. The group is running a digital transformation initiative to automate core processes like claims management. It's selected Appian as its enterprise platform standard. In Q2, it purchased a seven-figure software deal to license users in its largest geographic region. Appian's data fabric will integrate dozens of different systems into a comprehensive customer management application for tens of thousands of agents. Next, a top Canadian pension fund manages billions of dollars in investments; it's aiming to double its portfolio size. The group bought Appian two years ago to digitize its investment management processes. Its first app reduces the time it takes to assess potential investments by 90%. The customers starting at the next phase of projects and signed a seven-figure software deal in Q2, now over half the organization will use Appian. Last example is a top US health insurance provider and new logo. In Q2, it selected our platform to replace an inflexible call center system by the end of the year. It purchased a seven-figure software deal and will build a customer management tool for 1,600 call center agents. We won this deal after proving our platform's speed and flexibility with a custom proof-of-concept built in two weeks. The customer expects to save millions of dollars every year using Appian. Now, I'll hand the call to Mark for a deeper look at our financials. Mark? Mark Matheos: Thanks, Matt. I'll review the financial highlights for the quarter, and then we'll provide guidance for Q3 and the full year 2023. Total revenue, cloud subscription revenue, adjusted EBITDA and non-GAAP EPS were above guidance. We saw continued healthy contribution from existing customers and strong growth from key industry verticals, especially the US public sector and Life Sciences. Let's go into the details. Cloud subscription revenue was $74.4 million, an increase of 30% year-over-year and above guidance. On a constant currency basis, cloud subscription revenue grew 27% year-over-year. Subscriptions revenue was $93.8 million, an increase of 22% year-over-year. On a constant currency basis, subscription revenue grew 19% year-over-year. Consistent with the prior quarter, subscriptions revenue was impacted in part by some customers in cloud and from a higher mix of new cloud bookings during the quarter. Professional services revenue was $33.9 million, an increase of 2% year-over-year. On a constant currency basis, professional services revenue declined 2% year-over-year. As previously noted, our ability to predict services revenue is limited and a few large projects can influence growth in any given quarter. Long term, we believe partners will drive the majority of our implementations, our professional services will continue to be a strategic offering, focused on enabling partners and driving customer success. However, we expect professional services revenue to continue to decline as a percentage of total revenue. Total revenue was $127.7 million, an increase of 16% year-over-year and above our guidance. On a constant currency basis, total revenue grew 13% year-over-year. Subscriptions revenue was 73% of total revenue, consistent with the prior quarter and 70% in the year ago period. Our cloud subscription revenue retention rate was 115% as of June 30, 2023 consistent with the prior quarter. As a reminder, we continue to target the cloud subscription revenue retention rate of 110% to 120% on a quarterly basis. Our international operations contributed 38% of total revenue compared to 35% in the year-ago period. On a year-over-year basis, international growth was broad-based and saw healthy contributions from both APAC and EMEA regions. Our cloud software net new ACV bookings were approximately 85% of the total net new software bookings in the first half of 2023, an increase from 80% in 2022. Now, I'll turn to profitability metrics. Non-GAAP gross margin was 73% compared to 75% in the prior quarter and 71% in the year ago period. Subscriptions non-GAAP gross margin was 89%, consistent with the year ago period and 90% in the prior quarter. Professional services non-GAAP gross margin was 28% and compared to 30% in the year-ago period and 34% in the prior quarter. We expect professional services non-GAAP gross margin to decline to the mid-20% range in 2023 and low 20% range beyond 2023. And as we continue to invest in non-billable resources to help our customers maximize the value of their Appian investment. Total non-GAAP operating expenses were $119.7 million, an increase of 14% from $105.1 million in the year ago period. Adjusted EBITDA loss was $24.7 million versus our guidance of a loss between $30 million and $26 million and compared to an adjusted EBITDA loss of $25 million in the year ago period. In the second quarter, we had approximately $1.2 million of foreign exchange gains compared to foreign exchange losses of $6.5 million in the same period a year ago. We don't forecast movements in asset rates. Therefore, they are considered in our items. Non-GAAP net loss was $28.5 million or $0.39 per basic and diluted share compared to non-GAAP net loss of $33.4 million or $0.46 per basis diluted share for the quarter -- for the second quarter of 2022. This is based on 73 million basic and diluted shares outstanding for the second quarter of 2023 and 72.4 million basic and diluted shares outstanding for the second quarter of 2022. Turning to our balance sheet. As of June 30, 2023, cash and cash equivalents and investments were $237 million compared with $196 million as of December 31, 2022. For the second quarter, cash used by operations was $11.9 million, versus $29.7 million in the same period last year. Total deferred revenue was $195.4 million as of June 30, 2023, an increase of 28% from the year ago period. As we have stated on our past calls, the majority of our customers are invoiced on an annual upfront basis, but we also have some customers that are built quarterly or monthly. Due to the variability of our billing terms, changes in our deferred revenue are not -- are generally not indicative of the momentum in our business. We continue to believe cloud subscription revenue is a better indicator of our business momentum in billings or remaining performance applications. The latter metrics fluctuate based on timing of the in seasonality of on-prem license work and the duration of customer contracts. The true scale of the business is represented by subscriptions revenue, which includes support and all software subscription revenue regardless of whether the customer deploys to the Appian Cloud to their private cloud or on-prem. Now I'll turn to guidance. For the third quarter of 2023, cloud subscription revenue is expected to be between $75.5 million and $76.5 million, representing year-over-year growth of 25% and 26%. The Total revenue is expected to be between $134 million and $136 million, representing year-over-year growth of 14% to 15%. Adjusted EBITDA loss for the third quarter of 2023 is expected to be between $16 million and $12 million. Non-GAAP net loss per share is expected to be between $0.28 and $0.23. This assumes 73.3 million basic and diluted weighted average common shares outstanding. For the full year 2023, we are increasing cloud subscription revenue to between $299 million and $301 million, representing year-over-year growth of 26% and 27%. This is an increase from prior guidance of between $296 million and $298 million, representing year-over-year growth of 25% and 26%. For the full year 2023, we are increasing total revenue to between $538 million and $543 million, representing year-over-year growth of 15% to 16%. This is an increase from prior guidance of between $533 million and $538 million, representing year-over-year growth of 14% and 15%. Adjusted EBITDA loss is expected to be between $67 million and $63 million, an improvement from prior guidance of between $70 million and $65 million. Non-GAAP net loss per share is expected to be between $1.16 and $1.10. This assumes 73.2 million basic and diluted weighted average common shares outstanding. Our guidance as seems the following: first, Q3 and full year 2023 professional services revenue will grow at a mid-single-digit rate compared to the year ago period. Second, on-prem license revenue will be up on a sequential basis consistent with seasonality and year-over-year growth will continue to be impacted in part by some customers converting their contracts to cloud subscription. Third, Q3 adjusted EBITDA loss should improve both sequentially and year-over-year. We continue to expect non-GAAP adjusted EBITDA margins to come in better than 10% for the second half -- in the second half of 2023. Fourth, total other nonoperating expenses of approximately $2 million in Q3 and $5.4 million in 2023. Fifth, capital expenditures of approximately $2 million in Q3 and between $12 million and $13 million in 2020. This is primarily related to the build-out of additional office space. Finally, our guidance assumes FX rates as of August 1, 2023. In summary, we're excited about the growth opportunities ahead of us. We remain focused on investing in areas that will drive growth and generate superior returns long-term. With that, let's turn it over to questions. See also 20 Countries With Highest Cost Of Electricity and 12 Best Eastern European Countries to Meet Women.

Q&A Session

Operator: Thank you. [Operator Instructions] Our first question comes from the line of Vinod Srinivasaraghavan from Barclays. Vinod Srinivasaraghavan: Hi. Thanks for taking my questions today. It really seemed like a very clean quarter, strong cloud, be it. So I just wanted to just generally talk about first, some of the buying trends you saw in the quarter, any differences versus last quarter? And then secondly, we're expecting that copilot announcement next week. It seems like every vendor is announcing some type of AI assistant or feature in that. So do you think this is really table stakes now? And secondly, how are you kind of differentiating your solution? What's going to be the Appian difference? Is it data fabric? Is it something else? Any color on that would be appreciated. Matt Calkins: Yes, sure. I'll speak to that. AI is a wonderful opportunity, but a lot of firms have much the same vision and are pursuing the same endpoint. And I think our advantage is that our vision is different. Ours is a very customer-centric data-centric, privacy-centric and collaboration-centric vision of AI, and that's what we'll be facilitating. So I mean, we've already made a lot of AI functional drops, right? So we're in the market today with a great deal of AI-related functionality, large language model related and otherwise. So just in terms of volume of AI functionality, I believe we're doing great. But, more importantly, we are guiding toward a sensible philosophy of AI use and where AI is going to prolong in the enterprise. And I think that because we're correct about that, we're going to be facilitating a usage model that customers are going to want to invest in. Also, you asked if buying patterns were changing, I would just say simply that they're not, that we didn't see much change in buying patterns. Vinod Srinivasaraghavan: I appreciate that. Thank you. Operator: Thank you. One moment for our next question. Our next question comes from the line of Steve Enders from Citi. Steve Enders: Okay. Great. Thanks everyone. Thanks for taking the question here. I guess I just want to ask on the deal environment currently. And I guess, how should we be thinking about the stability of budgets and willingness for customers to be investing in automation and low-code and AI initiatives at this point? Matt Calkins: Well, I think there was a tremendous amount of excitement around AI. But I also think it's a little bit early for us to appraise that because the AI boom happened less time ago than the length of our sales cycle. So I think it would just be premature to speak to the way that's open pocket books. I don't know yet. I will say that it appears that customers are applying extra scrutiny to purchases this year that their sales cycles are slightly extended by that. There's been some delays, more delays than cancellations. There's just, I think, just extra consideration around investment to be made. And the counterpoint to that is an extreme amount of excitement about the way technology could create better efficiency, specifically around AI. Steve Enders: I guess on the deal cycle point, I mean, I think you remember after the past couple of quarters that there might have been some slight impact that not a real I guess, not an overarching challenge there. I guess, has that continued or has it gotten maybe a little bit more trend in the past quarter or so? Matt Calkins: I would say that it's somewhat consistent with last quarter. We see deals taking longer, but not disappearing, just taking longer. The interest is there. And I don't deny you could see it in the numbers, right? If you were to see side-by-side of a regular year versus what we're seeing now, there would be an evident difference would be a delay. But I also don't want to make it sound like that's an enormous difference because it's not. This is a -- this is a quantifiable but a small factor. Steve Enders: Okay. All right. That's helpful. And then I want to ask on Data Fabric. And I guess maybe kind of the extent that's penetrated throughout the base at this point. And I guess, kind of secondarily, when you think about data fabric differentiation is think about the AI initiatives that you're undertaking, I guess how much is that helping those conversations and maybe pushing towards a purchase decision with the data fabric element in there?

Matt Calkins: Yeah. Data Fabric is going to help us make a specific form of AI argument. So let me clarify this before I address your question. Data Fabric allows you to gather information in dispersed locations across your enterprise and use it for a common purpose. It's like a common semantic layer for addressing all that data as if maybe we'd put it all into the same database, except we didn't we just came up with a common way of grouping it and addressing it even though it's really scattered across the enterprise. Well, that's super useful. If what you want to do is train or fine-tune an AI algorithm. If you bring in an AI model, you want to use it behind the firewall so that you keep the data. It's always yours. You keep the algorithm. It's always yours. It's a very private customer-centric, data-centric vision of how to use AI than Data Fabric is fantastic. Data Fabric will grab you that data set, allow you to customize, select the information you want to train your algorithm with bring it together neatly and serve it up to the AI algorithm, so you can train it. It's very good for that kind of a vision. It's also very good for that matter for our typical use, which is to inform the actions in a process. And remember that now AI is one of the primary actors process. And so the more data connectivity you have, the more you can inform, send the right questions to AI, be sure that they're better informed to give you the answer. So Data Fabric is a key supporting player in an AI future. As for how that's playing out in terms of winning deals, closing deals, it's going to be too early to say. So I can't speak to that. But I have strong belief that we are facilitating a form of AI usage that's going to appeal to large organizations in regulated industries with important data sets and mission-critical intentions. Steve Enders: Okay. Perfect. Appreciate the answer there. Operator: Thank you. One moment for our next question. Our next question comes from the line of Sanjit Singh from Morgan Stanley. Unidentified Analyst: Excellent. Thank you. This is on for Steve on for Sanjit. I just had maybe two quick questions on the go-to-market. The first one, last quarter, you spoke a lot about public sector strength. I would be curious to hear kind of where the strength was this quarter? And then maybe contrast that with where you also see the most excitement around AI that could materialize later on? And then the second one under the new partner program that you announced, anything that you can share in terms of what you're seeing in terms of early momentum, or when -- what we should think about in terms of timing of some of those new leads materializing. That would be very helpful. Matt Calkins: Okay. Okay. Great. With regards to the industry that did the best this quarter, I'm going to a public sector again. It's just a really strong sequence here in the US public sector specifically, which isn't to say that that's where there's the most excitement around AI. The public sector is a cautious segment. And I don't think it's going to be the AI pioneer. I think we're going to see AI pioneering in places like pharmaceutical, financial services. I think it's going to make sense, insurance, healthcare. I'd actually put a public sector as a likely AI late adopter relatively. So we're succeeding for other reasons in public sector. And then the other question was about partners. We are adopting a new methodology of working with partners I think it's dynamic, it's exciting. It's premature to cite anything, of course, totally because it's not even rolled out. So I can't say what it has done -- but I believe that we're on to something important, having learned what we have about how to motivate partners, I think that we're going to take a powerful step in the right direction. And that's all I can say about it, just a future expectation kind of a statement. Unidentified Analyst: Great. Thank you. Operator: Thank you. One moment for our next question. Our next question comes from the line of Kevin Kumar from Goldman Sachs.

Kevin Kumar: Thanks for taking my question. Now Appian has an expanded set of AI-related features and capabilities that is going to be released, I think, later this year. Are these features being released across all on-premise and cloud customers? And do you think AI could potentially catalyze more customers to migrate towards cloud over time? Matt Calkins: I think AI will catalyze more customers to move to cloud. We are focusing on cloud as the primary AI environment. We will deliver more AI functionality faster in the cloud. And yes, I do believe that, that will be an incentive for customers to choose it. I want to be careful not to say that it will be an incentive for customers to migrate to it, because I'm not convinced that the customers who aren't -- who have not yet migrated by cloud will be motivated by any new feature set. Kevin Kumar: Okay. That's helpful. And then maybe one on margins. Operating expenses, I think, excluding certain one-time items has been relatively flat the last three quarters. Obviously, I know there's a focus on expanding margins, particularly in the second half of the year. So just curious, Mark, how you're thinking about resource allocation and how much is maybe new headcount in international regions, such as India helping with some of that operating leverage? Thanks. Mark Matheos: Yeah, sure. Thanks for that question. I mean there's definitely a focus on extracting operating leverage from our R&D center in India. But it's also just making sure we're investing in growth or accounts, right? And so -- we're not looking to make any operating expense reductions in areas that might impact our growth rate or our expansion. And it's really just some OpEx initiatives around scrutiny items that have led to some tightening of the ship, if you will and then some operating expense moderation in all areas across the board. But we definitely have a as all in mind that we shared in the past and that I've spoken to in my prepared remarks with operating expenses, and I think we're continuing to see through that plan. Kevin Kumar: Thank you, both. Operator: Thank you. One moment for our next question. Our next question comes from the line of Terry Tillman from Truist Securities. Joe Meares: This is Joe Meares on for Terry. I'm just curious, Cloud stub NRR is remaining steady at 115%. I'm just curious, are there any moving pieces under the hood as far as better than it charge results from up-sells or low base? Matt Calkins: I mean this -- it's pretty consistent, to be honest. If anything, expansion is slightly healthier. I mean, our GRR is so strong that it's hard for it to be any stronger -- and -- but overall, I would say it's been more the same than different. Joe Meares: Well, that's helpful. Just on the margin question. I understand that, you're investing where accounts and maybe doing some moderation in other areas. But I think you had said that you expect to be EBITDA breakeven next year. Are there going to have to be like larger cuts to operating expenses in order to get there in the medium term, or is it just going to be a factor of revenue leverage? Thank you very much. Mark Matheos: Yeah, I'll take it. You can add in, Matt, if you want. It's the latter. It's really -- we're not going to cut our way to an EBITDA breakeven point -- and just to clarify, we're saying we're going to reach a breakeven point next year. It's not at least the full breakeven. But yeah, that is going to come through the growth and the natural growth of our revenue streams and not through some concerted effort to cut out costs. Operator: Thank you. One moment for our next question. Our next question comes from the line of Derek Wood from TD Cowen. Andrew Sherman: Great. Thanks. It's Andrew on for Derek. Matt, I just wanted to come back to the federal business. How did federal bookings compared to less software bookings compared to last quarter and heading into the big September quarter. Can you give us a sense for how pipelines are tracking how they compare versus last year this time? And can that new GAM solution are you expecting pretty good upsell this year? Matt Calkins: All right. First of all, let me just second what Mark said a moment ago about growing our way to breakeven. That's the plan for next year. We're not going to cut our way there. We're going to grow our way there. Secondly, with regards to the performance of public sector and the pipeline, specifically heading into the big Q3, we feel good about the pipeline, the -- it shows real strength. I'm pleased with public sector's progress so far this year. And I think we have momentum and reason to believe that we can do well in quarters ahead. Andrew Sherman: Great. And I think last quarter, you talked about Appian World prospects or leads being up 2x year-over-year. Maybe just talk about how those leads are moving through the pipeline and your ability to convert and close some of those deals in the second half?

Matt Calkins : All right. Now let me just speak based on what I know of this, which is not everything. I understand us to be doing well with regards to new opportunities, Stage 1 leads and a lot of that comes from events like Appian World, but not exclusively Appian World. We're seeing strength in that broad category. And Appian World is just one of the sources. It's true that Appian World is well attended. It's true we got more prospects than we typically get. Those are great signs Appian World is like a showcase for what people can do with our software and the strength of the community and the enthusiasm around our users. I mean, 98% gross renewal rate is a number until you show up at Appian World and then it's an experience. And those people are it's contagious, right, the excitement. So I think it's great to get our prospects there. I believe that, that led to a set of quantifiable leads, but I don't have the numbers that show that that's where the leads came from. So I don't want to be too definitive about it. I just expect that, that was a great experience, and we exposed a lot of prospects to it. So good things are going to happen. Andrew Sherman: Great. Thanks guys. Operator: Thank you. One moment for our next question. Our next question comes from the line of Jake Roberge from William Blair. Jake Roberge : Hi. Thanks for taking my questions. Data Fabric vision definitely on very interesting. I'm just I'm curious, when we think about your core products within low-code RPA and process mining, do you think any of these products will see outsized benefits or headwinds from generative AI? And then how do you think AI impacts existing productized solutions within maybe your KYC or the GAM suite? And could it impact kind of the future solutions road map from here? Matt Calkins : It can definitely impact the future solutions road map. It's a terrific way to enhance the value of our application in all contexts. It enhances it in a solution, it enhances it, as a platform build. AI is one -- is like a star addition to the team. AI is more powerful than it's ever been. It's more popular than it's ever been. It's more likely to be adopted than ever. And it's part of a great suite of automation tools that can do work. So this is an efficiency boost for all of our applications and all of our clients. As soon as we can get them to make proper use of it, I -- yeah, so I see it as a lift across the board. We're the disruptor here. We use AI to create the value that we create. When customers buy Appian platform or solutions, they're counting on efficiency gains; we deliver some of that with AI. We're going to make the most effective use of AI technology toward efficiency gains. That's exactly what we're focused on. It's finding a way to get practical value out of this terrific new area of technology. We will be the vehicle, whereby, our customers achieve their AI efficiency gains. Jake Roberge: Very helpful. And then, Mark, when we think about the numbers, when do you think AI could start showing up on the revenue side of the house? Is that -- do you think that's more of a Q4 story or more of a 2024 dynamic? And then on the margin side, are there any AI investments that we should be cognizant of? Mark Matheos: Yeah. On the first part, AI, in my view, is a pretty big sea change in a long-term opportunity for us. And it's not necessarily something that will discuss in the short-term on a revenue basis. We certainly do dovetail on the second part of your question, we are making appropriate investments as part of our overall R&D strategy. We have had investments in the past for years. It's not like we're waking up and say we should look at AI, it's part of our blueprint for a long time, and we're certainly going to keep that investment in view we move forward to two, three years out, I think we'll still be talking about AI. Matt Calkins: Yes. Look, there's definitely a reallocation of resources internally. With the takeoff of large language models, we definitely want to put a lot of focus behind the proper utilization of that form of AI, and so we're shuffling investments internally. But what we're not doing is bolting on a big new investment. We already have expertise. We're just reallocating internally in order to match the explosion in customer interest and the power of these products. Like Mark, I don't want to make a prediction for when it will show up in revenue though. Jake Roberge: Great. Thanks for taking my questions. Operator: Thank you. At this time, I would now like to turn the conference back over to Sri Anantha for closing remarks. Sri Anantha: Great. Thank you very much, Gigi, and thank you all for joining us tonight. We look forward to catching up with you on our next earnings call. Talk to you soon. Operator: This concludes today's conference call. Thank you for participating. You may now disconnect.