All right. Well, welcome to day two of Morgan Stanley TMT Conference. My name is Da Wei. Morgan Stanley, Southeast Asia TMT analyst based in Singapore. 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. With that out of the way, I think we'll just like set the stage, 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. Then as subsequent to that, also talk about what do you see AvePoint's key competitive advantages? Yeah, 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. 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 that you're using to communicate with your supply chain partners, all of that information needs to be controlled and properly secured. Our platform, which is the Confidence Platform, really helps organizations address four 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. Over time, the digital environment, you know, 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, you know, encrypted by a ransomware attack. When you think about the different sources where data is coming from, it's hard to understand where your attack is coming from. 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 it with someone else, or it could even happen within your own organization as you're trying to share across departments. These are data challenges that really affect all kinds of businesses, whether they be enterprise, mid-market or SMB. 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 two big outages. One was in AWS, the other was in Azure. When you see these outages and you wanna 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 this capability in the Confidence Platform. 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 wanna make sure your data state is robust, pristine. We are helping organizations also implement governance for agents. 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. In the platform, you're also able to understand how agents are communicating across the different data sources. Also you could do things like inventory all your agents, and you could also do a lot of rollback, especially if agents go rogue, which is really important now in a phase where organizations are looking to operationalize agentic AI systems. Thanks, Mario. If I can just follow up on the discussion on AI, 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. Yeah. I think it was also alluded by CEO, TJ, who talk about, you know, AvePoint positioning as an enabler for AI. You guys actually act as the foundational layer and probably talk about a little bit more about what these are agents, agent AI and implications for your business model. Yeah. 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. 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 two years ago, the ability for us to do a 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. 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 gonna be really difficult for us to roll back if we have issues. 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, you know, whether it's frontier models or proprietary models, they are confident that they have visibility into how the agents are performing. 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. Just as a follow-up to that, you know, based on your conversations with some of your customers, are you seeing any changes in the customer spending behavior? Are you, I mean, there's a lot of talk about, you know, AI disruption and, you know, whether software will still be relevant. Are you, as a result of that, also seeing any form of pricing pressure? Kind of like, you know, split between, you know, what's hype and what's actually fundamental that you're actually seeing on the ground based on your conversations with the customers. Sure. I'm sure Jim will add some comments. 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 wanna operate it with less vendors." Too many point solutions create a complicated environment. 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 wanna get rid of storage because I wanna reduce my storage cost. We're 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, you know, our results for 2025 at all or what we're seeing in pipeline for 2026. I wouldn't wanna say that it's all this AI noise is hype. I think that would not be fair or true. 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. You know, we're not seeing an impact on the results at this point. You know, we're still see a lot of growth opportunity moving forward. Yeah. Let's talk about results. Okay. Right? I think you announced your results last week. We did. Let me just read through 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. You achieved the Rule of 40 or you're at 46%. Overall, I think pretty solid set of results. You've been executing to your guidance. Why don't you share, you know, your top takeaways from investors? You spent probably the whole day here talking to a few of them. What's been the main, you know, feedback? What do people like? What do people not like? You know, you're right. We've had a nice set of meetings today, thank you to Morgan Stanley for setting all that up. I would say a couple key takeaways, at least for me, as I think about maybe first just setting the stage for Q4 and the full-year. For us, Q4 was a really strong quarter, which really was an end and a nice way to end a really strong year. 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. You know, net new ARR growth. Again, really solid performance. You know, really the numbers you pointed out, to make that point. You know, one of the things that we've been talking a lot about to investors is, you know, we sat here probably it's over three years ago now at our first Investor Day, back in, well, I guess it's almost three years, March 2026. We made two commitments as a management team at that time. We wanted to focus on profitable growth, so we set two targets. One was to be a Rule of 40 company. Which at the time we were essentially a Rule of 20 or 21 company. That was a massive step forward. The second was to be GAAP profitable, which at the time, on a trailing 12-month basis, we might have been, you know, negative $20 million or $30 million. Significant step and leap to achieve. I'm happy to report we achieved both of those in 2025, where we were Rule of 46, as you pointed out, on the, you know, Rule of 40. We achieved the 46. The GAAP profitability, we actually achieved a year early in 2024, and again in 2025. In 2025 we accelerated our GAAP operating margin to 7.9%. We felt really good about this profitable growth in terms of growing, but also doing it responsibly. That's been for me, that was a key takeaway of the past couple of years, really trying to execute and deliver against what we committed to do. 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, you know, last week, accelerating top-line ARR growth year-over-year going into 2026, and also accelerating GAAP profitability, so an improvement over that 7.9% that we just posted for 2025. I think both of those were received very well, positive feedback both from our analysts and our shareholder base. Lots of good feedback. Even from today's meetings, I think, you know, what we put up not only in 2025 but what we're expecting to do in 2026, 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 three years and feel good about our prospects to continue. I think one thing that you mentioned on the earnings call was that you're actually seeing higher demand for migration solutions. Mm-hmm. -in 2025. can you just tell us a bit more what's actually driving that? should investors actually expect that to continue, and what would be the implications on your financials? Yeah. It's a good point, and I'm glad you brought it up because migration for us is really just data movement, if you think about it in that context. There's always gonna be data movement. 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 to cloud, tenant to tenant, through acquisitions, divestitures. There's always gonna be data movement. 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. We are seeing data movement. It did take a step up, really toward 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. It can be a nice entry point for some new customers. Obviously, it's a nice upsell or cross-sell motion for existing customers. We expect that to continue. We see good, healthy demand in our pipeline for those products. Again, we don't see it really backing off dramatically. Again, we've seen healthy demand across our whole platform in terms of the products. You know, we feel good about the prospects moving into 2026, from a pipeline point of view, from a platform point of view. again, I think we're delivering that value to our customers that they appreciate. Great. I think the other thing that was discussed was about potentially evolving into a hybrid pricing model, you know, between seat-based and consumption. This is probably also one of the, you know, most debated question among some of the software companies that they're here today. Can you tell us more, you know, from an AvePoint perspective, what the pros and cons of each of those models and what actually you think work best in today's AI environment? You want me to start that one? Yeah, you can start it. I'll start that one, and then Mario can chime in as well. You know, 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. There is a consumption element to that, where it may be more on the compute side. 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. They would treat those to a large degree as additional seats. Eventually I think it comes down to those will ultimately go to the value being created by those agents and those solutions, and it'll become much more value-based. We are experimenting with some of those pricing models as well. I think what we see is this will be an evolution. It won't be a, you know, tomorrow there's no more seat licenses and everything is consumption or some other pricing model. We believe it'll be an evolution over a period of time. Now we are in an accelerated timeframe where things are moving very quickly, but we still think it's an evolution as the pricing starts to change. Again, our platform is designed very well to be able to monitor all those different scenarios. We can really price various different ways. We can do seat pricing, consumption, pricing, even value. 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. Yeah. Maybe 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. You know, 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. Part of what we wanna 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, you know, an organization that at one point was selling the software based on servers, right? We would count servers, and we'd do it based on the infrastructure. At the time, the industry was pretty anxious about a shift to user-based licensing. 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 what's the right timing to do that shift. The fact that already we can give you workloads where we could track the way you're consuming, whether it's compute or 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. 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? That's sort of how we think about it. Great. Now if we would just take a step back and talk about your positioning and how your relationship has evolved with Microsoft as a partner. I know historically you've always kind of like leveraging the 365 ecosystem. You participated in co-sale programs. I think recently there's also, you know, this release of their agent governance capabilities. How do you know, plug into their product roadmap, and how has the relationship with Microsoft evolved over time? What are some of the dependency or risk that investors should be aware of? Yeah. you know, the relationship always starts with what does our customer want? 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. 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's going two 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 two years prior when we were working with Microsoft on some of the roadmap that eventually would make its way into the agent, you know, control plane they launched as well that you referenced. It's really important for us that there is a partnership that's strategic at the product level. 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 Cloud Marketplace, the AWS Marketplace. 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. Beyond that, we are also, you know, doing some really interesting techniques in go-to-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. These are all things that I think work really well in the partnership. 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. 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. Back again to how I started. When you work with customers and you explain 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, you know, some challenges with first-party products and solutions. Got it. Thanks. Turning back to you, Jim, as CFO, capital allocation. Mm. I know AvePoint always talk about, you know, these three strategic initiatives, which is, you know, investing R&D for future growth. You guys have done a series of acquisitions over the last couple of years, and as well as, like, share repurchases. How do you think about prioritization between these three initiatives? I have a follow-up question to that, we'll start with that first. Yeah, you're right. We think about capital allocation in those three 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, you know, from a product point of view or even from a customer point of view. The third is share repurchases, returning and improving shareholder value by purchasing shares of stock. You know, 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. Three, returning value to shareholders through share repurchases. Fortunately, we have a very strong balance sheet. We ended the year with over $480 million of cash. That affords us some optionality, right? We have the ability to do not just pick one of those to actually do, but we can actually do all three. That's been You know, we've done six acquisitions to date over the past several years. You know, 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. I believe we can execute and continue to execute on that. Then share repurchases. We spent about $50 million in 2025 on share repurchases. That accelerated really in Q4. In Q1 of 2026, we already spent $33 million+ on share repurchases, which effectively is repurchasing about 80% of the amount we spent last year. I think we're executing, we're taking advantage of what we believe is, you know, a disintermediation in terms of our value, what we're actually executing and delivering. We'll continue to do that moving forward. 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 repurchases, 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. Whether that's an M&A activity or stepping up, like we're doing this year in 2026, we're going to allocate more resources to our marketing spend. Having the ability to really make these investments and having a strong balance sheet gives us the ability to, you know, be able to do those things. Yeah. AvePoint just turned profitable, and at least based on your guidance, it seems like you're gonna be a lot more profitable in the coming years. You have a strong balance sheet. You're you know, generating nice free cash flow. At what point does dividend actually comes into the equation? You know, it's a, it's a good point in terms of profitability. Like I mentioned, our GAAP profitability, operating profitability, 2024 was the first year where we had crossed that threshold, and actually we're generating GAAP operating margins. Which is great. We continued that and accelerated that in 2025, and we're projecting and guiding to accelerate that even further in 2026. We feel good about that. Our free cash flow margins are also very strong. 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. 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 lifecycle of where we are, where we're still accelerating growth, we're still looking to continue to be an accelerant. 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. You know, I would say in the near term, we don't have any plan to be actually issuing a actual dividend, but continuing our share repurchases approach. Right. We're just gonna take a pause here. We're just under five minutes. I'd like to ask the audience if there are any questions. Copilot might be the first of what we get with enterprise AI. Can you talk a little bit about what Copilot? Sure. Maybe to set the stage, Copilot is a brand of capabilities. 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, you know, enable not only agent development, but workflow automation. If we think about those two categories, for us, the opportunity really started when organizations really started saying automation of workflows could really be, you know, 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. 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 two years ago. Copilot inside of 365, you know, 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, you know, information. Is that information curated? Is the information accurate?" Organizations immediately came back to us and said, "Look, we wanna make sure we're looking at our data state, and we're putting the right controls in place. Can you help us?" 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 the data state ready for what's coming." Fast-forward two years later, we're 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, you know, advanced AI tools that are homegrown or some that are commercial off the shelf, right? 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 an experience layer. We're working more at the trust layer of the stack. For us, it's a, it's an opportunity to keep doing the work we've been doing with these organizations and partners. For us, on the innovation side, it gives us, you know, enough room to continue bringing, not just the governance controls that we're shipping now in AgentPulse, but also think of what comes next. That's how we think about it. Again, we're still in the early stages, and we believe that, you know, 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, you know, tech stack that gives you an opportunity to build also advanced agents, I think is also gonna be part of the conversation. 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, you know, antiquated or that are not giving the organization the efficiency that they're looking for. With that, I think we are at time. Thank you all for joining. Jim, Mario, it's been a great pleasure. Thank you. Yeah. Thanks for having us. Thank you. Thank you. Thank you all. I appreciate it.