Today, I have Mark Matheos, CFO, and Sri Ananthanarayanan, head of IR. Thanks for being here. Thanks, Kevin. Thanks. So I thought maybe just to start off, I think it would be helpful for people new to the story to just give a brief overview of Appian, kind of the history and kind of the platform capabilities. Got it. Thanks, Kevin, for having us here. Appian is focused on the process automation market. By that we mean we do everything related to a process: building it, running it, automating it, executing it, diagnosing it, changing it, everything related to a process. This is a large market opportunity, and we conservatively estimate the market size approximately $60 billion. You know, the one thing that is different from others in the marketplace is we provide all the capabilities related to a process. By that we mean we include process capabilities related to workflow, robotic process automation, process mining, AI, you know, all in one fully integrated platform. I think this is extremely useful for our customers as they're dealing with one single code, but more importantly, they can deploy new applications and maintain existing applications faster. We predominantly sell to large enterprises that are building complex processes. They're making them. They want to make themselves more efficient by providing better customer experience. Largely, majority of our revenue comes from subscription-based services. When we went public in 2017, our revenue mix was 50% subscription, 50% services. Today, that revenue mix is 75% subscription and 25% services. This is largely driven by our cloud subscription revenue, which has grown at 30% or more since going public. Yeah. I wanna get back to the platform capabilities in a bit, but I thought maybe we can start, since you mentioned AI. I guess, you know, I think Appian's been pretty vocal about kind of their strategy in terms of private versus public AI. So, maybe just give us some context around, you know, what does that actually mean? You know, why approach it that way? How is that differentiated from maybe other vendors in the space? Yeah, sure. So I think it's actually pretty self-evident. Anytime you look at a corporation's assets, data is the crown jewel of the corporation. So they have really, really important controls and safeguards around data and data protection, and if you're a bank or an insurance company, it's critical that you have your data secure, but also that your proprietary business process is also secure, right? So it's not just your Social Security numbers and your customer not, you know, private information that's that has to be kept secure, but also how you do business, right? So how an insurance company files a claim through its process. So what Appian is saying, and I think what's kind of being echoed throughout industry, and there's a lot, a lot more white papers coming out about this, is that you really need to keep all of that within your own domain, behind your firewall. It's not enough to, like, redact certain parts of the information. And so when you're thinking about AI today and large language models, the notion that you're gonna send all that information out to the ether and, you know, try to get some computational advantage from that is really not well thought out, right? It has to be kind of within the confines of the corporate environment that you're in. So, I think CIOs and, people in charge of the, you know, the company's data are gonna, you know, they're not gonna react nicely to some proposal that sends the data out, right? So Private AI, I think, kind of inherently makes sense. And, you know, it's really what our CEO has spoken a lot about. He's written an editorial in The Wall Street Journal about it. And I think what we're doing is using the platform that we've already got to try to incorporate all the awesome power that large language models and AI can give us in that kind of secure environment that's within the bounds of a corporate environment or a government's environment, or whoever our customers may be. Yeah. Yeah. And what I'd just add, Kevin, to that is, you know, it's also the nature of the customers that we're dealing with. These are large multinational corporations that have very strict compliance and security needs. So in that particular context, what these customers are saying is, "Hey, we don't want to share our data with any public domain." So when we are talking about training your algorithms or LLM models, we are talking about doing that in a private setting, so that the data is held by the customer wherever it is, and whichever cloud they are hosting, they're not even sharing the data with us and training the models. In fact, I was just meeting yesterday another investor, and he was saying there was actually a letter sent out to the legal industry where they're saying is: "Hey, if you guys are going to build these private LLM models, make sure you own the model and you are training the model. Yeah. So that is what we are going to enable the customer. We will help the customer build the model, but we will give the model to the customer so that they can train that model with their own data in a private setting. Yep. And then I guess, you know, it feels like the narrative around Gen AI is, you know... The question that we get often is who gets, you know, displaced? Who are the winners and losers? It feels like the narrative is some of the more basic low-code solutions, you know, may be more pressured. And so maybe talk a little bit about, Sri, you talked about kind of the end-to-end process automation platform and kind of the mission-critical workloads that you do. So just from a positioning perspective, you know, what does that mean for a platform like Appian versus maybe some other tools? Got it. It's a great question. Again, we constantly think about these things. The way I would think about, you know, we have been using AI for a while. We have deployed as a part of, for some of our solutions, AI. The Government Acquisition solution, Government Acquisition Management solution, which is one of the successful solutions that is largely, you know, deployed by large federal agencies, we already provide some AI capabilities as a part of the platform. The way we think about AI or Gen AI in general is, it's an additional lever or an accelerant to automation adoption, more than anything else. To your point, could there be some low-end, you know, solutions that could be displaced? Probably. You know, if you are just a code generator, that probably is more relevant. Today, when we talk about Appian Platform capabilities, we are talking about building an entire end-to-end processes. When we include AI as a part of that platform, we think it accelerates the adoption of this platform and these solutions, but more importantly, it enables customers to deploy some of the applications they're planning to build much more quickly. It's more an efficiency driver, rather than we think it's going to be a displacement. Probably some low-end, but that's not the market we are focused on. Yeah, and just to add to what Sri is saying, we operate in kind of this broad, complex, you know, mission-critical space. So companies that are faced with supply chain issues, for example, we've had a story, we said about a major manufacturing company, who had to face Brexit, and they had to all of a sudden... I mean, they were UK-based, and all of a sudden, their whole procurement and supply chain operations ground to a halt because they needed to think about customs forms for every shipping, every item that was shipped out, shipped out of the UK. So, you know, we built a solution that streamlined that entire shipping and procurement, supply chain. So when that company was sending transmissions to Germany, and to Italy, they could just type in the address. It would pull in the jurisdictional forms that were required. It would auto-populate them. It completely streamlined that procurement for that manufacturing company. They liked it so much that they're expanding into other supply chain apps. So they're running their supply chain in large part on Appian. So it's not one of these, you know, this build a low-code lightweight tool to get us to do A, point A to point B. It's a fulsome transformation that companies are doing with Appian. Yeah. And Sri, you made an interesting point on, you know, maybe implementation times, you know, getting faster, time to value, probably getting better. Does that help maybe broaden the, you know, the addressable market, you know, just by kind of having a tool that can get you up and running even quicker? We think so. You know, it not only broadens our market opportunity, but more importantly, the time to value, right? Especially in an environment like this, where customers are looking for solutions that generate quick ROI, we think that certainly helps the case from a return on investment for an investor. But also internally, when we're using the same set of capabilities, we are also improving the productivity of our developers. Yeah. Keep in mind, we've already seen some level of productivity out of our developers, but we think this is going to be accelerating, so it helps our inherent operating leverage in the business model. Yeah. And then, you know, there's a lot of buzz around, you know, Gen AI, and, and feels like there's, you know, increase in customer engagement. But like, are you starting to see it kind of in the pipeline? Like, is it impacting kind of any of the key kind of growth metrics, or is it still kind of in the early stages there? It's definitely early stages. The conversations are happening. I think the energy levels are extremely high. Companies are actually trying to figure out how to best use AI to get what they need done, right? And so they're talking to partners like Appian to try to get a feasible way. You know, they're reading about AI and the capabilities, and they're looking at their actual IT landscape and what they have to get done, and they're using Appian as a sounding board to try to get an actual feasible roadmap that will help them take advantage of all these new technologies. So, I think, yeah, it's early days right now, but the level of energy coming into it is very high. Yeah. And then I want to maybe shift gears a bit to just kind of overall demand. I think last quarter, Matt, CEO, you know, he mentioned I think things are, you know, stable or things haven't changed too much from prior quarters. But maybe just add a little bit of context around kind of what you're hearing, what's the appetite for, you know, both existing customers and new customers to maybe undergo some of these larger kind of, you know, transformations. Yeah, I think in large part, the demand is still pretty strong. It's on the user side and the business side, it's perhaps even stronger than it's been. I think the macro impact is more on the deal lengths and the approvals required to get any spend through a company right now. And so that's kind of a little bit of a, you know, a proverbial, you know, rock in the cogs or whatever. I forgot the expression, but it's kind of a little bit of a slowdown. Yeah In the actual sales cycle itself, right? So I think we've seen that for two or three quarters. In the beginning, it wasn't clear if this was just kind of normal noise, but it's been persistent enough that we think it definitely is just the overall macro backdrop that's challenging, and we certainly don't see it resolving. We're not in position to say, you know, the light is shining at the end of the tunnel and we're turning the corner on that front. But again, the product demand and the use cases that are out there that need to be done are still very much present. Yeah. You know, what I would just add to that is just, you know, we have been seeing this for the past two quarters, but we have appropriately baked that into our guidance. So, you know, we have been dealing with this. This is not like a new phenomenon. The only thing is, it's not getting incrementally worse. So, but the guidance appropriately bakes that into this. And I think, Mark, you had mentioned maybe healthier contributions from Europe and APAC last quarter. Is that just kind of a one-off, or like maybe catch up after maybe softness in prior quarters? Maybe talk about some of the regional markets and any changes you're seeing there. You know, those, those markets are doing well for us. I think it speaks to the use cases that are emerging in financial services and insurance, among other areas. There's definitely, you know, some law of numbers here. There, those are smaller markets for us. Our total international spend, revenue is about 30% or so. So we definitely have, you know, smaller numbers. The growth rates are better, but it's a consistent and durable growth, and I think we're gonna potentially see that same stay the course for at least the near term. Maybe the midterm, we'll see strength in Europe. There's a lot, a lot of institutions that could really benefit from, from Appian. I think I'll note, maybe a common thread is the regulatory environment there is a little bit more likely to need systems and structure for business processes. You know, Europe takes... There's a lot of regulations that come out of Europe all the time, right? And the companies are faced with, "Oh, crap, we've got about 18 months to deal with this regulation. How do we do it?" And I think that's a little bit more of a catalyst than you might find in the U.S. Yeah. Around kind of, you know, sales cycles, but budget scrutiny, is there are you seeing, you know, customers consolidate vendors? You know, especially just given the breadth of the, the Appian Platform, you know, is there an opportunity there to kind of capture more of the share and consolidate? I think we are seeing that to an extent. It's along the lines of just spend management, but really, it takes multiple forms. They try to reduce vendors they're not using, they try to consolidate vendors where they can, and it's sometimes the fight between the back office procurement folks and the business folks who really want to use something. But we're actually, you know, on the good side of that fight, because what we build is really not something that's easily replaceable. It's our GRR, gross renewal rates, are 98%-99% in the past few quarters. They've been that way since IPO. We definitely have a sticky set of software. Yeah. I think we prevail when we, you know, stay the fight. If there's a fight around consolidation, and we say, "Let's have it. Let's go through it," we usually end up doing pretty well. So I wanted to ask about just cloud revenue growth. Sri, you mentioned, you know, you're factoring in some macro dynamics into the guidance. I think the full-year guide is around kind of high 20s growth. So maybe just around kind of how you think about kind of the durability of cloud revenue growth. I think, Mark, you've talked about, you know, 30% being a key target for the company. So maybe just to put some takes there in terms of how you're thinking about, you know, how you're investing and what you think is the right level of growth, you know, at this stage of maturity. Yes. Yeah. Yeah. You know, when we look at the guidance for the year, the midpoint, it's 30%. And clearly, in a normal macro environment, we said, you know, we should be able to sustain that 30% cloud subscription growth rate. You know, when you look at the key drivers, right? The existing growth coming from existing customers and new customers. Today, roughly two-thirds of the growth comes from existing customers, and about a third come... the rest comes from new customers. Within the existing customers, we clearly think there's a lot of room for expansion with them. We think our penetration within our existing customers today is probably less than 10% of the available spend that's there. And with our platform capabilities broadening, we think there's a lot of upsell opportunities within our existing customer base. That is certainly something we are seeing, even in this kind of environment. I know you talked about Europe. When we look at some of the strong growth coming from Europe, it's also coming from our existing customer base. You know, what we have seen historically is, once a customer builds that first application with us, they certainly understand the capabilities, how easy it is used to... they can use the application. The second sale or the third sale comes within a relatively short period of time. With the new customers, right, we are certainly baking in some macro impacts in the current macro environment. Clearly, that's where we are seeing the sales cycle impact. But clearly, given the market size and the broad capabilities of platform, we think there is substantial room for growth, and in a normal macro environment, we should be able to sustain that 30% cloud subscription growth. Yeah. I mean, you bring up an interesting point. It seems like the larger customers or the 1 million plus, I mean, the growth rates there are very strong. It seems like the bigger a customer gets, you know, the faster the growth. Is that just a function of, you know, they know how to use the platform, that, you know, it's end-to-end, you have all these capabilities? And, you know, maybe talk a little bit about that, that, how some of the larger customers are really doing. You know, that cohort is doing really nicely right now. Yeah. The, the most prolific customers, the ones that are our bigger customers, are actually expanding in general, high, at a faster rate than, than our smaller customers. There's definitely a, a component of familiarity that builds, and then the power that we've been talking about through that sales process is actually made evident. And so they're getting an ROI from the first 3 apps or 2 apps that they've built, and the roadmap that we initially talked about, maybe we had 10 apps on it. And so they, they look at that ROI and they say, "Well, why not build the rest?" There's definitely, you know, that's where kind of macro and things like that just get pushed aside, right? You've got, you've got your ROI, you, you've got things you need to do. It's working, keep building. The, the new customer doesn't have that confidence. It's got nothing to do with the product or our capabilities, it's just a new thing, right? So they need to figure out, you know, kind of dab their toe in it first, and then, and then, and then go in the water completely, right? So I think it takes time to get that confidence. I think we do see success once that confidence is attained, and that happens through just the building of apps. Some of our larger customers have 30, 40, 50 applications that they've built, and they're actually continuing to build. It's almost endless, because if you think about a top five commercial bank, the amount of hair in the IT department and in the business is off the charts, right? It's not... It's not just 40 or 50 that they can build; there's a lot more. And, we're just out there to try to get that use case in front of the customers so they can keep buying. I wanted to shift a little bit, maybe back to, to product. You know, I think, Sri, you mentioned it, but, you know, end-to-end platform, now you have Process Mining, you have RPA, workflow automation. Maybe just to level set, like, how is, how is the platform being used differently now? Or just maybe compare and contrast the way the platform is being utilized today versus maybe three years ago. Today, when we look at the usage of our customer base, right? Today, they're still predominantly using to build, you know, workflows, applications. We're definitely seeing incremental adoption of RPA and process mining, but we still think it's in early stages today. The key value add that customers get from our platform is building that workflows and applications in a relatively quicker time period. More importantly, deploying those in an efficient fashion. You know, when we look at the usage levels from our, you know, different cohort of customers, to a point, like some of the larger customers, the usage is still growing at a pretty healthy rate. The early customers are gradually ramping, but once they deploy that first application, we see the adoption of that growing much more broadly. The other things that we're seeing is, like, you know, Data Fabric. We talked about recently, that's a new capability that we added to platform. That is the number one feature that's been widely adopted. Since introducing, 90% of all of our new customers have signed up for Data Fabric capability. So as we are broadening those capabilities, I think we are seeing wider adoption, but more importantly, we are focused on that long-term... long-tail growth opportunity. So, you know, we are taking our time, but we are definitely feeling good about where the usage levels are trending with our customers. Yeah. I did wanna talk about Data Fabric, because that stat is pretty impressive. And maybe just talk about why is that resonating so well. You know, what does that enable? And are you also seeing that, 'cause I think that metric is for new customers, but you know, what about existing customers as well? Yeah. So Data Fabric is a phenomenal feature of Appian, and it is a differentiator for us. When we show it to customers, they love it, they want it. It's, it's usually a game changer. And I think it's actually... You know, it, it's been enhanced further by AI. And, and, and I think what it allows us to do in that space is build these large language models, a lot faster, a lot more securely, a lot more, in line with compliance regulations. So but, but let me step back. I think the biggest part of data fabric is that it's kind of solving all of your data integration issues, and it creates this virtual database in a very easy-to-use environment, and allows you to pull information from all sorts of data sources at your company's IT environment. So whatever systems need to be involved, it can pull the data, and actually can write back to the source system as well. So a lot of that depends on, you know, how is the user experience, right? Is it easy to use? Is it fast? Is there latency? And that's where it shines. It's extremely easy to use, it's very fast, it's low code, and so you're actually able to solve a lot of these data integration pain points that companies have. And further than that, when you're actually thinking about building large language models, what better way to do that than to use Appian's Data Fabric? And again, one of the things about Appian that is a differentiator is that we don't really care about where the data sits. We're not big tech. We don't say you've got to bring all your data within, you know, our system, within our cloud. You can actually just pipe into it. And I think our traditional use case is around an orchestration layer, where we've come in and say we're in at a call center and at an insurance company that's acquired, you know, dozens of insurance companies in the past 20 years. And all those systems that they acquire, they all work, but they're just kind of clunky, and the call center reps have to put you on hold when you file a claim to look you up and what system you're in. You know, that's a perfect use case for Appian, we've done it before, where you just build an Appian orchestration layer, all those systems feed into Appian, and the call center reps are just using Appian. And if they need to update the core record, they can do it with Appian. They don't have to ever use the other systems. And so that's much more effective and really much more cost-effective as well than a rip and replace scenario, obviously, which can be a complete nightmare. But that's like chapter one of Data Fabric, right? Nowadays, Data Fabric can do a lot more, a lot faster. And again, this AI revolution allows us to bring in data within any system or with even any, like, if you're talking about papers, right? If you're talking about paper invoices, we can use Appian's Intelligent Document Processing to pull in that data. And then that's how you, you know, harness the power of a large language model in a Private AI space. It's getting all the right data in the right spot. And when you're a highly regulated bank or insurance company, you really can't mess around with how you do that. You need a highly secure environment like Appian. You know, what's different about that is, you know, it's our... By the way, it's our own patented analytical, you know, framework. More importantly, today there are other tools that are available where they offer open APIs, right? But they force customers to migrate the data onto their platform. With a Data Fabric, you don't have to do that. So what is the advantage of, to customers? Instead of customers building that new API tools or maintaining existing API tools, they don't have to do any of that. It's like a virtual database layer. More importantly, it helps customers to keep the data wherever it is, and it helps customers to integrate the data onto this, into the Appian Platform and get real-time updates on what exactly happening with that particular processes. So the advantage is, customers don't have to build new APIs or maintain existing APIs. Yeah. That's great. And given some of these newer capabilities that are coming out, I think it will be helpful to just talk a little bit about the overall kind of pricing strategy. You know, how are you monetizing some of these newer features? Just maybe talk about, you know, seat-based versus kind of, you know, usage-based pricing and kind of how you think that's evolving. Sure. So, you know, the... Historically, we've priced, you know, this is going years back, but we still have a lot of our revenue base and our renewals this way, just on a per user, per month model, and so we've got a published kind of price list. We've recently, I shouldn't say recently, it's really been over the past 4 years or so, kind of pivoted new business to an application-specific model, where we evaluate the use case, and it actually creates a less friction environment because the customer isn't locked into some per user dollar amount for the long term. Whenever we see anxiety or friction develop around that, and we start getting negotiations that are, you know, hammering down our per user price, we just say, "How about we just price you on the app you wanna build?" And that cuts out the friction. So they'll. You know, maybe if it's a bank, we'll build a know your customer application, you know, for $200,000, and that's palatable. They'll build it in 8-10 weeks under the Appian Guarantee. It'll go live, they'll love it, and then they'll say, "Okay, we need a mortgage origination app. That was the next thing we wanted to build." And we say, "Okay, great. Now you know about Appian, you know how it works, and we have a little bit of a bigger stance at the negotiating table with them on that. It's better than kind of locking a lower price. But the usage component... You know, we don't have usage-based pricing. It's kind of incorporated in how we evaluate the pricing on an application-specific app sale. So, you know, will we ever switch to usage? Maybe. I think subscription seems to be the name of the game at the moment. Okay. Yeah. Any questions from the audience? Can you talk about how you compare the environment? AI in particular seems like what is it? So the question was just on competitive dynamics and kind of, you know, how AI is kind of impacting that. Yeah. Yeah. So I think historically, you know, we, we've entered into a greenfield opportunity where the, you know, the incumbent competitor, if you will, is high-code, and or some development in-house that's custom. If it's not that, it's usually Pegasystems that is at the bake-off because they can build powerful applications as well, although they have an older technology that takes a lot longer to do that. The other emerging competitor has been ServiceNow. I think in the past two or three years, they've kind of gone right at us with a low-code platform. I think a lot of their marketing shows that they mirror a lot of what we're saying. But at the time of a proof of concept, I think it becomes really clear that our power is much, much greater, and that their use cases are really orchestrated around their ITSM environment and neighboring environments that they can do some things in low-code with. But it's not... You know, whenever there's a complex use case, like the ones I've talked about, it's really not in ServiceNow's wheelhouse at the moment. I think they are investing and certainly formidable. We don't see much of Microsoft, but occasionally we do. Anything else you want to add, Sri? No, I would say the competitive environment, if you just look at for the past few years, it's largely remained the same. Even if I look at within the past 12 months, on the margin, we see ServiceNow a bit more compared to what we see in the past. But the type of use cases that we are going after, the type of customer base, I think the competitive set is much more narrower than what's tend to be believed out there. There are certainly a lot of noise at the very low end. If you're just a code generator, there's a lot of noise out there, or building some lightweight application, there's a lot of noise out there, but that's not a market that we're really focused on. I did wanna touch on go-to-market. You know, I think there were. Appian definitely added a lot more sales capacity, I think, in the back half of last year. So, maybe just touch on kind of, you know, how things are going in terms of go-to-market in this, you know, in this macro environment. How you think about some of the newer reps ramping and, you know, the impact of productivity, and maybe layer in kind of, you know... 'Cause I think you guys have set some nice kinda EBITDA targets, right? And so kinda how that plays into the, you know, bottom line guidance. Yeah. So we made a lot of investments last year. I think we're very happy we did. We've got a really strong go-to-market motion at this point. Certainly the macro is not ideal, but we're still seeing a healthy ramp. We wouldn't have expected those reps to be productive quite yet. There's a solid 12-month or so ramp-up time. So towards the end of this year, early next year, we'll start to see productivity from them. We certainly have seen pipeline generation and all of the things that are indicating success. But you know, our growth rate, I think, is still the central focus, and we're very happy we have that strong motion on the go-to-market side. You know, to your EBITDA comments, we are moderating our OpEx in general, and I think that's more catered around just what I call growth with scrutiny. Identifying areas where maybe in a 0% interest rate environment, you would've allowed sort of some spend to happen, but in this environment, we need to cut some of it back. But it's not, I think, targeted towards anything that's revenue generating or impacting our growth rate. And so, we'll actually continue to invest in those areas, you know, as we move forward, especially where we have territories that need more go-to-market muscle. But overall, that moderation in spend will result in us reaching a break-even point in adjusted EBITDA in 2024, and being adjusted EBITDA positive in 2025. Yeah, uh- Any other questions? On the go-to-market, I mean, part of the ramp, is it related to... You know, your one of your competitors, they talked about de-emphasizing the net new motion and kind of focus more on the installed base. Do you see that as an opportunity, to kind of take the other side of that? And, you know, you said that you see the most, so. Yeah, it's absolutely an opportunity. We aren't doing that in terms of what our competitor is doing and focusing on expansion. It would be easy for us to try to get a few more points of growth from expansion, but I think the strategy for us is to get more customers. We're using our partner ecosystem to help with that. We're enhancing our partner relationships with our most strategic partners so we can get more new logos. It's critical. We see this as an early innings company with a large opportunity in front of us, including a lot of new customers. And hopefully, we can get those customers up to that seven-figure ARR mark, so they can start expanding on their own and telling us what they wanna build. And that's the, that's the goal, try to get as many of those. You know, some of that improvement in EBITDA is just coming from us getting more efficient, right? We've talked about our R&D efficiency. We're improving our efficiency. We recently opened our R&D development center in Chennai, in India, so part of that R&D efficiency is coming from that particular center. Plus, we're also going to be more than $500 million in revenue this year, so some of that is just comes with scale, rather than we arbitrarily trying to take away some of the costs from somewhere. So we're still focused on the growth, but we're also trying to get more efficient. Yeah. I, I think it's nice to be in this kind of scale right now, where we can still grow and kind of naturally create Adjusted EBITDA breakeven without having to do any painful cuts. Yeah. Maybe to finish things off, just on this, Mark, you recently introduced some long-term targets. So maybe talk about kind of the key levers there. I think you've talked about 20% operating margin. I think key to that is also 80%-85% gross margin. So maybe talk about kind of, you know, what's the appropriate mix. I know you guys have talked about services declining, but maybe a little bit more on the key levers that'll get you that 20% target. Yeah. Certainly, the mix will continue to shift towards software. Our gross margins are near 90%, on the software side, so that's certainly an area for leverage. Sri talked about our Chennai, India, R&D center. It's not, you know, some small thing we're doing, it's a massive R&D tech center we're building, and that'll help. We're actually finding a really good talent there, and kind of very happy we've gone there. So, in general, we are looking at sales efficiency as well, and making sure our reps are ramping quicker, that they're all productive. Sales enablement is a focus. And then finally, we are at the size now where some of the marketing programs can have some more scale and benefit to us as well. So I think S&M we'll certainly be looking at improving that over time. Yeah. Great. I think we're out of time, but really appreciate the time. Thank you. Great. Thanks, Kevin. Thank you.