AvePoint, Inc. (AVPT) Earnings Call Transcript & Summary

Welcome to day 2 of Morgan Stanley TMT Conference. My name is Da Wei, morgan Stanley's Southeast Asia TMT analyst based in Singapore. And today, we are very honored to have here with us Jim Caci and Mario Carvajal. Before we begin, let me just read out the disclosure. For important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative.

And with that out of the way, I think we're just like set the stage and starting with you, Mario, who is the Chief Strategy and Marketing Officer for AvePoint. How about you give us a brief overview of the company and talk about what are the main problems that you're actually solving for your customers? And then perhaps subsequent to that also talk about what do you see AvePoint's key competitive advantages?

Yes, sure. Hi, everyone. Thank you for having us. Thank you to the Morgan Stanley team and yourself, Da Wei for sitting down and chatting with us. So we're a global provider in modern data protection. We help organizations secure, govern and operationalize their data estates. We primarily focus our efforts on unstructured data, which if you think about unstructured data, it makes up about 80% of an organization's data today. The unstructured data that's coming in through your different applications, whether it's productivity applications, applications that you're using to communicate with your supply chain partners, all of that information needs to be controlled and properly secured. So our platform, which is the Confidence Platform really helps organizations address 4 key problem areas. One is there's fragmented data that sits in different silos. And oftentimes, it's difficult to see the data, to apply policies. The second challenge is sprawl of information, it could be that you have a lot of access, different accounts accessing information or you have different data repositories. And over time, the digital environment really gets heavy in terms of managing it because you have too much sprawl. The third problem is that organizations really are struggling to address the loss of data problem, where sometimes you may have corruption to data or you have information that can be encrypted by a ransomware attack and so when you think about the different sources where data is coming from, it's hard to understand where your attack is coming from. And then, of course, there's also the opportunity to help organizations address over sharing of data. If you over share data, you can inadvertently expose sensitive information. This could happen in a conversation you may be having on a chat communications tool. It could also happen where you might be inadvertently sending a file to a supply chain partner. They share with someone else or it can even happen within your own organization as you're trying to share across departments. So these are data challenges that really affect all kinds of businesses, whether they be enterprise, mid-market or SMB. And so what we do is we provide a security layer of controls and this helps organizations implement policies that help them understand where changes in the information are happening, where overexposure may be happening. And it also helps the organization address data resiliency issues think about an outage that may happen at the data center. Last year, we saw 2 big outages. One was in AWS, the other was in Azure. And so when you see these outages and you want to recover your data is really important. If you can't recover the data because it's either too large and you can't recover it in time or you certainly need to recover certain elements of that data, the metadata, how do you do it effectively? We provide all of the capability in the Confidence Platform. And then the last thing I'll leave you with is we also have been helping organizations think about this next step into agentic AI systems where now in order to really advance your efforts in AI tools, you want to make sure your data state is robust, pristine. So we are helping organizations also implement governance for agents and agents are really working across different data sources. They have different identities, and they're creating more and more activity and all of that information and activity needs to be tracked. And so in the platform, you're also able to understand how agents are communicating across the different data sources, but also you could do things like inventory all your agents and you could also do a lot of roll back, especially if agents go rogue, which is really important now in a phase where organizations are looking to operationalize agentic AI systems.

Thanks, Mario. And if I can just follow up on the discussion on AI, and that's probably the, I think, single most repeated question in this entire conference, probably repeated as much as the disclosure statement at this point. So I think it was also alluded by CEO, TJ who talk about AvePoint positioning as an enabler for AI and you guys actually act as the foundational layer and probably talk about -- a little bit more about these agents, agentic AI and the implications for your business model?

Yes. If we think about data becoming the fuel for AI, the first thing you need to understand is that if you have advanced AI tools and you can't trust the data because it's either not properly classified or the data that the model may be using is incorrectly provisioned or accessed then it's really hard to build trust. So what we begin to do with organizations is think about how to improve the quality of the data, build a robust data foundation so that you can start to implement AI capabilities. The reason we help organizations get ready for AI is we started shipping probably over 2 years ago, the ability for us to do an AI assessment where we would say, run the tool, let us take a look at where you have vulnerabilities and let us remediate those vulnerabilities on your data estate. We soon after that started working with companies that were starting to build agents, specifically organizations that really wanted to start automating tasks. And the biggest challenge was if we don't have an inventory of where these agents are and we don't actually track how these agents are interacting across different data repositories, it's going to be really difficult for us to roll back if we have issues. So part of the work that we're doing today, to answer your question is we're helping organizations think about implementing the right controls so that as they build their agentic AI systems or they automate or start working with whether it's frontier models or proprietary models they are confident that they have visibility into how the agents are performing. And that gives organizations a really good opportunity to not only implement the right controls at the start, but also anticipate regulatory requirements that may be important, especially with companies in regulated industries.

Great. And just as a follow-up to that, based on your conversations with some of your customers, are you seeing any changes in the customer spending behavior and are you -- I mean, there's a lot of talk about AI disruption and whether software will still be relevant. Are you, as a result of that, also seeing any form of pricing pressure. So kind of like split between what type and what actually fundamental that you're actually seeing on the ground based on your conversations with the customers?

Sure. I'll start and I'm sure Jim will add some comments. So we're not seeing major changes in spending. I think what we're seeing is a prioritization that starts with cost consolidation. Vendor consolidation is another way to think about it, where organizations are saying in order for me to have more efficiency in my operations, I probably want to operate it with less vendors. Too many point solutions create a complicated environment. So a lot of the conversations is how to really optimize the environment with single pane of glass, one type of platform that really helps them across several workloads. In that category, we are well positioned because our platform strategy is to include several workloads, whether you're thinking about recoverability or whether you're thinking about simply looking at cost consolidation. I want to get rid of storage because I want to reduce my storage cost. So we are working with the clients across different workloads, and that gives us an opportunity to access quite frankly, budgets that may not have been in the hands of the central IT program, budgets that may be sitting with the business because the goal for us is to deliver more value back to the business users through a productivity layer where the application is really operating the environment more effectively and efficiently.

Jim, do you have anything to add?

No, I think those are really good points from Mario, but maybe even just to put a finer point on it, we really haven't seen it impact our results for '25 at all or what we're seeing in pipeline for '26. So I wouldn't want to say that it's all this AI noise is hype. I think that would not be fair or true. But we're not seeing it impact right now our results, and hopefully, we'll have a chance to talk about some of the results for Q4 and the full year. But we're not seeing an impact on the results at this point, and we're still very -- see a lot of growth opportunity moving forward.

Yes. So let's talk about results. So I think you announced your results last week.

We did.

Let me just readthrough some headline numbers. I think which is a good set of numbers. $470 million ARR. SaaS revenue grew 38% for the full year, we're seeing 19% free cash flow margins, and you achieved the Rule of 40 at 46%. So overall, I think pretty solid set of results, you've been executing to your guidance, why don't you share your top takeaways from investors and you spend probably the whole day here talking to a few of them. What's been the main feedback? What do people like, what do people not like?

You're right. We've had a nice set of meetings today. So thank you to Morgan Stanley for setting all that up. And I would say a couple of key takeaways, at least for me, as I think about maybe first just setting the stage for Q4 and the full year. So for us, Q4 was a really strong quarter, which really was an end and a nice way to end a really strong year. So in -- despite all the concerns around public sector and a variety of things, we delivered for the year, 27% ARR growth, 27% revenue growth year-over-year, fourth quarter was accelerating revenue growth. Fourth quarter was also our 11th straight quarter where we had double-digit ARR growth. So net new ARR growth. So again, really solid performance, really the numbers you pointed out to make that point. One of the things that we've been talking a lot about to investors is we sat here, probably it's over 3 years ago now at our first Investor Day back in -- well, I guess it's almost 3 years. March of 2026, and we made 2 commitments as a management team at that time. We wanted to focus on profitable growth. So we set 2 targets. One was to be a Rule of 40 company, which at the time, we were essentially a Rule of 20 or 21 company. So that was a massive step forward. And the second was to be GAAP profitable. which at the time, on a trailing 12-month basis, we might have been negative $20 million or $30 million. So significant step and leap to achieve. And I'm happy to report we achieved both of those in 2025, where we were Rule of 46, as you pointed out, on the Rule of 40. So we achieved the 46. And the GAAP profitability, we actually achieved a year early in 2024 and again in '25. And in '25, we accelerated our GAAP operating margin to 7.9%. So we felt really good about this profitable growth in terms of growing, but also doing it responsibly. And that's been -- for me, that was a key takeaway over the past couple of years really trying to execute and deliver against what we committed to do. And that's some of the feedback we've been receiving after our earnings call last week, which was really very well received in terms of the growth that we put out. We also have from our guidance that we published last week, accelerating top line ARR growth year-over-year going into '26 and also accelerating GAAP profitability. So an improvement over that 7.9% that we just posted for 2025. So I think both of those were received very well, positive feedback both from our analysts and our shareholder base, lots of good feedback. And even from today's meetings, I think what we put up not only in '25, but what we're expecting to do in '26 was very well received. And again, we believe is very achievable in terms of our execution. Obviously, we have to continue to execute but we've now been executing for really 3 years and feel good about our prospects to continue.

And I think one thing that you mentioned on the earnings call was that you're actually seeing higher demand for migration solutions in 2025. Can you just tell us a little bit more what's actually driving that? And should investors actually expect that to continue? And what would be the implications on your financials?

Yes. So it's a good point. I'm glad you brought it up because -- so migration for us is really just data movement, if you think about it in that context. So there's always going to be data movement. So we believe migration is a key component of just this evolution that we all live in whether we're talking about specifically about AI or just data governance management. There will always be data movement from on-prem to the cloud, cloud to cloud, tenant to tenant, through acquisitions, divestitures, there's always going to be data movement. So -- but I think, particularly in light of AI and as people think about how important it is to have your data properly curated and that is much easier if it's a little more consolidated in fewer repositories. So we are seeing data movement. It did take a step up really towards the second half of 2025. Which again is good. We're happy to be accommodating our customers in terms of their evolution, in terms of their AI adoption. We're happy to do that. We believe that it gives us an opportunity to not only meet their expectations and exceed them, but also introduce them to our platform in general. And so it can be a nice entry point for some new customers. And obviously, it's a nice upsell or cross-sell motion for existing customers. So we expect that to continue. We see good healthy demand in our pipeline for those products. So again, we don't see it really backing off dramatically. But again, we've seen healthy demand across our whole platform in terms of the product. So we feel good about the prospects moving into '26 from a pipeline point of view, from a platform point of view. And again, I think we're delivering that value to our customers that they appreciate.

Great. And I think the other thing that was discussed was about potentially evolving into a hybrid pricing model between seat-based and consumption. And this is probably also one of the most debated question among some of the software companies that are here today. Can you tell us more from AvePoint perspective, what the pros and cons of each of those models? And what actually you think work best in today's AI environment?

Do you want me to start that one? I'll start that one, and then Mario can chime in as well. It's interesting. Right now, we have a hybrid model within our organization and have for quite a while, where most of our licensing is still seat-based like most of the hyperscalers, but there is a consumption element to that where it may be more on the compute side. So some of our solutions are more compute-driven. And therefore in those aspects of our products, there is a consumption element. We do think as we continue to move forward with agents. Initially, the hyperscalers talk about those being governed almost like just other seats, other essentially people that are taking actions across the multiple applications. And so they would treat those to a large degree as additional seats. But eventually, I think it comes down to -- those ultimately go to the value being created by those agents and those solutions and it will become much more value-based. So we are experimenting with some of those pricing models as well. And I think what we see is this will be an evolution. It won't be a -- tomorrow, there's no more seat licenses and everything is consumption, or some other pricing model. We believe it will be an evolution over a period of time. Now we are in an accelerated time frame where things are moving very quickly, but we still think it's an evolution as the pricing starts to change. And again, our platform is designed very well to be able to monitor all those different scenarios. So we can really price various different ways. We can do seat pricing, consumption pricing, even value. So we think we're positioned well to be able to meet the demand from both our customers and other areas to be able to provide a mechanism of pricing that works in their models, but also works for us as well.

Maybe the only other thing I would add is that the platform, we're in a good position. We've designed it so that you have the right metering. We can understand activity, workloads, as Jim mentioned, if there's a high compute, we could track the activity workload, especially around agents. One thing that's interesting is the more agents that get designed into an agentic architecture, the more activity there will be, the more risk surface there will be. So part of what we want to do is give organizations an opportunity to understand how this sort of evolution, as Jim mentioned, is based on value creation so that when the time comes that we make that shift in product licensing, it just makes sense. We've been through this before. We were an organization that at one point was selling the software based on servers, right? We would count servers and we do it based on the infrastructure. And at the time, the industry was pretty anxious about a shift to user-based licensing, and we made that shift following the same sort of formula. We work with not only the hyperscalers, but we also work with a lot of organizations that really give us a good pulse on what's the right appetite and when is the right timing to do that shift. And the fact that already, we can give you workloads where we can track the way you're consuming, whether it's computer storage. I think that gives our customers the confidence that we're there to really create more value for them and ultimately measure the outcomes of the software. And that I think is where people will end up, what are the outcomes, what is that service driving that changes in this material to our business. So that's sort of how we think about it.

Great. And now if you would just take a step back and talk about your positioning and how your relationship has evolved with Microsoft as a partner. I know you've always kind of leveraging the 365 ecosystem, you participated in co-sell programs. And I think recently, there's also this release of their agent and governance capabilities. How do you plug into that product road map? And how has the relationship with Microsoft evolve over time? And what are some of the dependency or risk the investors should be aware of?

Yes. So the relationship always starts with, what does our customer want? And a lot of our customers say, we are making investments into technologies from Microsoft or in some cases, they could also be investing in other providers, such as Google, et cetera. And most of the time, what they want is that the product functions and operates ahead of time, meaning we have a responsibility to make sure we're working with Microsoft Teams to understand where their product is going 2 years ahead of time. An example of this is our AgentPulse, which we launched in November, at the Microsoft Ignite conference was a product that had already been worked on 2 years prior when we were working with Microsoft on some of the road map that eventually would make its way into the agent control plane they launch as well that you referenced. So it's really important for us that there is a partnership that's strategic at the product level. But we also have a partnership with them on the go-to-market piece, which is deliver value and incentives. Our products, for example, are available not only on the Microsoft marketplace but they're also available on the Google marketplace, the AWS marketplace. And this is a way to give customers back because these hyperscalers give customers incentives anytime they are buying products on the marketplace. It basically gives them credits back towards the contracts they may have with the hyperscalers. And then beyond that, we are also doing some really interesting techniques in growing a market where we provide customers an opportunity to onboard sort of capabilities from the Microsoft services that gives the customer a better traction and adoption. So these are all things that I think work really well in the partnership. But I'll also say this that maybe a lot of investors sometimes misunderstand, we're providing a product line that really drives value for the Microsoft productivity cloud, but we also do this for Google. We do it for Salesforce. We do it for other third-party services like Atlassian. We just launched a number of connectors to DocuSign, Smartsheet, GitHub. Our platform is independent. It is not a platform that really depends on Microsoft capability. We connect to their APIs, and that's how we're able to drive a single pane of glass to give you a security layer on all of the data that's either coming from a Microsoft productivity service or other. And then the fact that we operate our platform on the hyperscaler data centers also creates a really nice relationship with not just Microsoft but also Google and AWS. So back again to how I started. When you work with customers and you explained this to them, they feel that we're working with a vendor that really understands the ecosystem and that the vendor will be able to help us also in cases where we might have some challenges with first-party products and solutions.

Got it. And turning back to you, Jim as CFO, capital allocation? I know AvePoint always talked about these 3 strategic initiatives, which is investing in R&D for future growth. You guys have done a series of acquisitions over the last couple of years. And as far as share repurchases. So how do you think about prioritization between these 3 initiatives? And I have a follow-up question to that. So we'll start with that first.

Yes, you're right. We think about capital allocation in those 3 pillars, right? One is investing in the business, predominantly R&D, second would be M&A activity in terms of can we supplement our own R&D efforts with inorganic growth that would help us either from a product point of view or even from a customer point of view. And then the third is share repurchases, returning and improving shareholder value by purchasing shares of stock. So those are the priorities. And arguably, you could say in terms of those -- the priority itself, like, number one, making sure the business is properly funded, two, looking at opportunities to supplement that, and then three, returning value to shareholders through share repurchases. So fortunately, we have a very strong balance sheet. So we ended the year with over $480 million of cash. So that affords us some optionality, right? So we have the ability to do not just pick one of those to actually do, but we can actually do all 3. And so that's been -- we've done 6 acquisitions to date over the past several years. So we are looking to do even larger acquisitions. I think we've built a little bit of a muscle there in terms of the small ones that we've done. So I believe we can execute and continue to execute on that. And then share repurchases. We spent about $50 million in 2025 on share repurchases. That accelerated really in Q4 and then in Q1 of '26, we already spent $33 million plus on share repurchases, which effectively is repurchasing about 80% of the amount we spent last year. So again, I think we're executing. We're taking advantage of what we believe is disintermediation in terms of our value, what we're actually executing and delivering, and we'll continue to do that moving forward. But we will do it in a measured approach. Some of you already know that, that's been our mantra probably over the past couple of years with share repurchase, is to take a very measured approach so that we can preserve that really strong balance sheet to take advantage and be opportunistic as opportunities present themselves. We want to be in a position to act accordingly and whether that's an M&A activity, or stepping up our -- like we're doing this year in '26, we're going to allocate more resources to our marketing spend. So having the ability to really make these investments and having a strong balance sheet gives us the ability to be able to do those things.

Yes. And AvePoint just turned profitable. And at least based on your guidance, it seems like you're going to be a lot more profitable in the coming years. You have a strong balance sheet, you're growing -- you're generating nice free cash flow, at what point the dividend actually comes into the equation?

It's a good point in terms of profitability. Like I mentioned, our GAAP profitability, operating profitability, '24 was the first year where we had crossed that threshold. And actually, we're generating GAAP operating margins, so which is great. We continued that and accelerated that in '25 and we're projecting and guiding to accelerate that even further in 2026. So we feel good about that. Our free cash flow margins -- free cash flow margins are also very strong. So you're right, we are generating a significant amount of cash we generated this past year, about $80 million of free cash flow and we would expect that to accelerate next year. So again, we're producing a lot of cash. When it comes to dividends, the way we think about dividends is more in line with most software companies here in the states, which would be share repurchases as opposed to a true dividend at least at our stage of life cycle of where we are, where we're still accelerating growth. We're still looking to continue to be an accelerant. So we don't think about returning capital to shareholders in the form of dividends, but more in the reducing either dilution from our SBC or just reducing shares outstanding by share repurchases. So I would say in the near term, we don't have any plan to be actually issuing an actual dividend, but continuing our share repurchases.

We're just going to take a pause here, we're just under 5 minutes, and I'd like to ask the audience if there are any questions?

[indiscernible]

Yes, sure. So maybe to set the stage, so Copilot is a brand of capabilities. So you have Copilot in the Office suite of applications. You have Copilot Studio, which is really more focused on low-code way for you to enable not only agent development but workflow automation. So if we think about those 2 categories. For us, the opportunity really started when organizations really started saying automation of workflows could really be more driven by agents and that led to conversations on how agentic architectures could work. For us, that was an opportunity to start building our governance framework in the context of agentic architecture. So we're happy about that. I think that gave us an opportunity to work with some large organizations that were first movers. And this is probably going back 2 years ago. The Copilot inside of 365, for us, that creates another -- it's just another productivity app, where organizations that first turned that on were starting to have concerns, wait, I turned Copilot on, and I'm asking it to go find me the latest employee handbook, and it brings back a bunch of information, and is that information curated, is the information accurate? Organizations immediately came back to us and said, look, we want to make sure we're looking at our data state and we're putting the right controls in place. Can you help us? So it wasn't that the Copilot was something we were solving. It was that Copilot triggered off a thought in the organization that really said, we probably need to go get data state ready for what's coming. Fast forward 2 years later, we are now in a year where I think a lot of organizations are seeing the opportunity and the possibility to work not just with Copilot but other models. You see some of the work that Anthropic is doing, trying to come into the enterprise and say, we have an opportunity to help organizations think about proprietary data models. Well, that's good because agentic AI systems will be a combination of advanced AI tools that are homegrown or some that are commercial off the shelf, right? So for us, these are all opportunities to go back and talk to the client about what does it mean to put a set of capability to build the trust layer of your stack. See, AI has experience layer. We are working more at the trust layer of the stack and for us, it's an opportunity to keep doing the work we've been doing with these organizations and partners. And for us on the innovation side, it gives us enough room to continue bringing not just the governance controls that we're shipping now in AgentPulse, but also think of what comes next. So that's how we think about it. And again, we're still in the early stages, and we believe that the work that Google is also doing, which Google is a partner, and we're doing more to support now Google Gemini. Their Vertex AI tech stack that gives you an opportunity to build also advanced agents. I think it's also going to be part of the conversation. So we're very much looking forward to it and working with some incredible organizations that are not only experimenting with this, but actually deploying this to transform business processes that are antiquated or that are not giving the organization the efficiency that they're looking for.

And with that, I think we are at time. So thank you all for joining. Jim, Mario, it's been a great pleasure. Thank you, guys.

Thanks for having us. Thank you.

Thank you. Appreciate it.