Tianyi Jiang, who's the CEO of AvePoint, and Jamie Arestia, who's VP of Investor Relations. Before we begin, I'm required to inform you that a complete list of research disclosures or potential conflicts of interest is available on our website at williamblair.com. Tianyi Jiang is going to go through some slides, and then we'll have a little fireside chat. All right. Good. Good afternoon. Hi, everyone. I think most of you are probably familiar with the story, so I'll just go real quick. That includes our latest quarterly earnings updates. From a financial at a glance, currently we're at $435 million recurring revenue. Our forecast revenue for the remainder of the year is, by the end of the year, will exceed half billion mark. Right now, the SaaS mix is, we're pretty much completed our entire SaaS subscription. The mix is about 80% of total revenue now. The growth of SaaS revenue is 38%. In terms of the profitability, we continue to show very strong profitability. This year, our estimated free cash flow is almost $100 million on over $520 million revenue. Last trailing 12-month, total revenue is $444 million. From a rule of 40 perspective, where we define as essentially profitability and revenue growth. AR. ARR growth and profitability is 45%. Also from a GAAP profitability perspective, we're already there as well, because we did a very good control around SBC to make sure that, overall, not only are we forward cash profitable, but also GAAP profitable. Also very encouraging to continue to see our cohort 100,000 and above AR customers continue to increase at a nice clip, and this is also happening globally. In all the region we operate, which is Western Europe, Middle East, North America, and Asia. By Asia, we mean Japan, Singapore, Australia, New Zealand, South Korea, and also emerging markets in ASEAN, including India. Overall, our business is really focused around helping companies to secure their collaboration with confidence. Our core business has always been around data management, data curation, data governance. Of course, in the age of AI, this is an even more urgent issue because ultimately, for corporates to turn AI into something meaningful for their business, for their industry, they need to do refinement training to leverage their corpus of proprietary data. Because enterprise historically stored data all over the place, we all have that experience. That data consolidation, the proper data classification tagging, and then ultimately access control and lifecycle management becomes core prerequisite to AI deployment. The easiest way to visualize this is actually this. Everybody know about the layer cake of the AI infrastructure from foundation layer to intelligence layer. The easiest way to think about how we increasingly becoming relevant to enterprises large and small, is that we are forming the trust layer between data and model. Ultimately, enterprise data is their proprietary moat, and that's how they compete and distinguish themselves against other businesses. We help them organize that content. This is all unstructured data. That's your emails, your chats, your contracts, et cetera. That's 80% of all data out there. That data growth is very, very rapid thanks to, of course, a lot of AI slop as well. Ultimately, we allow organizations to better organize their data from an access control delegated governance model. That would then be fed into their AI models to have concrete AI output. The things that we cover are visibility of AI agents, what agents are running in your environments, what do they have access to, what other programs they talk to, what other interface they talk to, and then surface out the cost profile of these AI agents. Effectively allow enterprise to actually control both AI risk as well as AI cost. This whole concept of trust in AI, and the AI output is something that we fundamentally help enterprise organize. This is the benefit of what we offer. It's in one singular SaaS offering. We are in 18 different instances of data centers, whether it's a Microsoft Azure data centers or Google GCP data centers or AWS data centers, as well as U.S. government, and Singapore government data centers. It's a singular SaaS platform that offers these capabilities around data resiliency, which is backup, recovery, archiving, ransomware attack detection, recovery, AI damage detection, recovery, modernization, data integration, data analytics, data migration. Data would never stop moving. That's forever a space that's part of the story. Customer moving their data from Google to Microsoft, from Box to Google, et cetera, to on-premises to cloud, even tenant to tenant from acquisition divestiture perspective. Lastly, control. It's really access control, governance, lifecycle management. Previously, it's focused on unstructured data. Now, it's focused on applications like agents. Before, we cut our teeth on low-code, no-code application platform like Power Platform, Power Apps. Now, it's agents. We actually launched our Agent PaaS product at the same time as Microsoft launched Microsoft Agent 365, that better together story. More importantly, we do this for multi-cloud, not just Microsoft. We also cover Google as well as AWS. This multi-cloud ecosystem, increasingly multi-model ecosystem, is something that also really important to our customers. The key takeaway, we win based on the platform play. We view the whole end-to-end data management story as one singular story, not separate story of backup, GRC governance, and then migration, but a singular story because we think the evolution and disruption that AI brings to the table is actually forcing this convergence of different needs into a singular, basically solution offering that vendors like us can fulfill. Also, we have customers that see us as very much as an important aspect of their AI infrastructure. We are in these AI conversations. It's not the, "Oh, we're so focused on AI, we have no time to talk to you," but "AvePoint, please come to the conversation to help us organize and reduce risk and increase exposure on how do we do cost management for AI." Thirdly is we actually do this successfully across all segments, large enterprise, which is 53% of our recurring, we define as 5,000 above employee companies, as well as small to medium businesses. That's increasingly a very fast-growing segment for us. Small business, 500 and below, and then mid-market is 500- 5,000. We actually are successful in growing all three segments and across all geos. That's also very unique for a company of our size. Effectively, while we're still relatively small, this year we'll break through the $500 million ARR mark. We have all the scaling and all the foundations laid down to be a much larger global data management vendor. Yeah. That's our story and going forward, you will see a lot more messaging coming out on this very important AI trust layer that we play, increasingly position us very well for accelerated growth. Right. Okay, great. Very compact. Yeah. The final comment that you made there does lead into my first question, which is, I think the case for why you're an AI winner sounds like it's at that trust layer. Maybe just elaborate on, at this point, what you're seeing from customers. What is holding them back in terms of AI adoption, and how do you kind of help accelerate their opportunity there? Yeah. The story of last year is human using AI. The story of this year is AI using AI, right? Agentic explosion. Otherwise, also known as shadow AI. Business users are vibe coding their own agents and running amok. Either it's their own consumer edition, they just swipe a credit card, or they're using enterprise cloud and just do their own thing, and then very quickly they recognize that before they even get a ROI, the cost is going through the roof. The hair on fire problem for most CEOs that we talk to out there, one is AI risk, the other one's AI cost. Recognizing that there's a real cost now, and of course, Anthropic now set the precedent. All the other providers are now increasing their costs in a massive way. Just take Microsoft GitHub Copilot, for example. Now, the new introduction of consumption-based licensing, GitHub cost now is basically increased by 6x, 6x. That's just GitHub. It was a flat fee before. It was a flat user seat-based fee. Yeah. Now it's consumption model. Even that is still cheaper than cloud. That's why Microsoft, two weeks ago, shut down all cloud usage across the entire Microsoft. That gives you a sense of the two side of the equation. There is risk about AI running wild and B, causing damages. On the other side, there's this real cost concern. It's no longer AI replacing employees. It's actually AI, one, could cost far more than an employee, and two, we have yet to drive to that concrete business ROI yet. Do you think, I guess the obvious question is this unsustainable for enterprises right now? Just the comments that we've seen out there from the Uber CTO saying that they've burned all of their AI budget in four months. How is this going to play out? It's not sustainable because before, approximation for AI adoption is tokenmaxxing, right? Clearly, that's not working. We all heard some enterprise last month burned through $500 million in one month. We don't know whether that's AWS or Microsoft, but it's one of the bigger guys. That's tokenmaxxing. That's not sustainable. Neither is today's paradigm of, okay, everyone was only allocated this much token usage, and after that, I cap you, and you cannot use the AI anymore. That's also not sustainable. Yeah. I think what's interesting is now more than ever, vendors like us that company go to to say, "Hey, help us take stock, discovery, everything that's out there, and then bring them under management and alert us on cost." Subsequently, of course, everyone's working towards this token optimization story, because you don't really need expensive cloud to summarize your email for you, for example. You see also Microsoft now releasing small models, MAI, they call it, six small models with open weights. This week, right? Yeah, this week. They released that, specific for coding, for translation, for graphic generation. open weights models that any enterprise can take and run and tweak to it, for their own needs. There's going to be that more bifurcation of, hey, is this good enough, small models, frontier models, versus truly heavy-duty, research-orientated, expensive model consumption. I think that maturity will take time to settle. In the meantime, first order of business is to take stock and try to discover all the shadow AI that's running out there. Then don't forget all the little OpenClaw agents that's running on your desktops. Right. That endpoints that enterprise now need to go discover and bring them under management. Is there a bear case for these frontier models because of what you just said, that there are going to be more optimization? Is this the hyperscalers in 2022 when everyone started optimizing their cost, or you think we're just so early that it's just going to be such a massive pie that everyone wins for the time being? Well, it remains to be seen what play out. There's six major vendors that's all racing towards building the next largest language model: Microsoft, AWS, Meta, OpenAI, Anthropic, and of course, xAI. Google. Google. Yeah. Right. Yeah. The differentiation between these large language models, effectively, yes, today, Anthropic is the best one, but they're what, three months or two months ahead or one month ahead. That side is getting commoditized, for sure. The ability to command premium dollars for workloads will have to, over time, change. It was actually interesting. I was at the Microsoft CEO Summit where they invite their top 200 CEOs every year. They had the chairman of BlackRock on stage, and he said even at BlackRock, they don't have enough cash to run Mythos against BlackRock's entire tech stack. That's how expensive things are. If BlackRock can't afford to use AI, who can? That's not sustainable. It remains to be seen how this whole thing's going to play out. Obviously, now we have shortage of everything. We have shortage of even memory chips, let alone GPUs. Never mind power. I think at the same time, though, there is real maturity settling in in terms of enterprise usage of AI. I think this is actually very healthy. It will force enterprises to be laser-focused on actual outcome-based, ROI-based AI deployments. That the question, give everyone AI and just go crazy with it, those days are gone. Hopefully, with this focus, we will actually see real business outcome-driven AI deployments in the field. I guess that's where you guys come in to help them figure that stuff out. Where are you in the AI journey for AvePoint with customers? When you paint this picture of a trust layer, is this still like slide wear? Are customers actually deploying AvePoint for this stuff yet? Customers are deploying. One large customer, even Temasek, Head of Security, was telling us this is a priority of priorities. They're now trialing our AvePoint AgentPulse solution. Where we differentiate is we do cut multi-cloud because hyperscalers only care about themselves. The customers have everything. They have multimodal deployment approach and also shadow AI also introduces all kinds of flavors. It's important to go out and discover everything that's running in your corporate environment, whether it's cloud or on-prem, and bring them under control. That's very topical and so much so that we did say, all of a sudden, 40% of our pipeline is in control versus before 26% of our business is in that governance side. Now 40% of the entire pipeline is that. Also when you're introducing these agentic governance flavors, which we just released the same time as Microsoft released Agent 360, mid Q1. It's already 50% of our total control sell, in term of pipeline building and also elevating our deal sizes in a very significant way. Yeah, we're very confident directionally this is going the right way. I think the next couple quarters will play out. Okay For sure. It's moving the needle on pipeline right now. Deal size. Will be moving the needle on revenue within whatever. We think so. A few quarters. Yeah. Jim actually mentioned, because my CFO mentioned it, I can say it, because he's a conservative guy. He thinks the demand is so high that we probably just also skew it as a standalone product. Currently, our customer only gets it if they actually have the control bundle. Okay. Yeah. What's the name of the product again? It's called AvePoint AgentPulse. AvePoint AgentPulse. Yeah. Right. Okay, okay, great. Let's talk about Microsoft for a minute. I feel like when we sit down with investors and talk about AvePoint, that's always the number one question. I don't know if you would agree with that, Jamie, but it's always just like. Yeah. Yeah. It's just like, what's the relationship with Microsoft? You guys obviously have been a long time partner of theirs. You have, I think, one of their EVPs is on your board. I think there's always a little bit of discomfort- Where people are just like, "Are you too close to Microsoft? Can they cut you out of the loop at some point?" Right. Yeah. Just talk through the kind of Microsoft partnership and the overlap. Right in their product set versus your product set. Like all major hyperscalers, Microsoft has an ecosystem, we're part of that ecosystem. We don't depend on Microsoft for any of our revenue generation. Microsoft doesn't give us leads, nor resell our software. We're a part of the ecosystem. We close the last mile problem, too. Actually, it's in Microsoft favor because we actually help them light up more cloud workloads, whether it's Copilot, and before it's Purview. Of course, with their expansive licensing type, now there's an E7 license, which is $100 per user per month. Microsoft Agent 365 is $15 per user per month. Compared to before, the average cost of Microsoft 365 is $20-$30 per user per month. That creates this gap among the customers of this mixed licensing type, this is where vendors like us can come in close and help them maximize their investment. Increasingly, we see really strong uptick of Google in the enterprise. Gemini is a very strong play for Google. Interesting enough that Google historically very strong on tech, but they're weak on go-to-market on enterprise. They're changing that by hiring a bunch of very senior business commercial leaders from Microsoft. We know them very well. They're now doing the same playbook, and we are there as well. You will see that quickly we are becoming elevated as a global top-tier partner in the Google ecosystem because there is a shortage of this type of enterprise-grade ecosystem player in the Google ecosystem. Same leaders, same playbook. We know how to go-to-market there. You will see an intentionality to really go multi-cloud because that's the reality of the world. The customers more and more are using multi-cloud, are using multiple models even, to get things done. It's becoming more fractured, fragmented, from an IT deployment landscape. The more complexity, the better for us. We thrive on complexity, whether it is governance, regulations, data sovereignty, data privacy, and now, of course, agentic risk and control. That's where we actually thrive. Microsoft today is still, I think, 90% or something of your business. Maybe just talk about Google contribution, whatever you can disclose on that, and then where do you see it going over time? Yeah. Compared to Microsoft? We actually increasingly sharpen the lens around this. We actually say Microsoft 365 is where we previously make 90% of our revenue. Increasingly, all the agents are actually not running in Microsoft 365, right? Agents are running in compute cloud, which is Azure, GCP, AWS. The compute side, what we call IaaS and PaaS, is increasing at a very fast-growing segment for us. We think that outside of Microsoft cloud, we should have numbers to show this. Obviously, everyone's asking for that. As we work our way to get to that $1 billion ARR run rate as fast as we can, the mix will become at minimally 30% will be outside of the Microsoft 365. Microsoft 365. Yeah. Got you. Okay. For the Azure and the kind of non-Office stuff, what are you primarily selling to those environments, in those environments? Compute side, you have also governance. Application governance, to which actually agentic governance is just one flavor. There's also, of course, resiliency, right? Understood. Your compute environments. When AWS regional data center got taken out during the early stage of the latest Middle East conflict, we've seen a spike in demand for resilience for cloud, resilience IaaS and PaaS, in Middle East as well as in Europe. We actually call that out at our latest earnings. That's where folks realize you cannot just rely on hyperscaler themselves to provide resiliency for you. Okay. Data protection and governance for Azure, AWS workloads, basically. That's right. Got you. I was telling you earlier, we had Commvault and Varonis present also earlier today. Can you just talk about the competitive landscape? Who do you see the most? You mentioned the difference between yourselves and some of these providers that are more sort of narrow in their product capabilities. How do you describe AvePoint from a competitive standpoint versus some of the other players that are out there? I think all the vendors have their own strength, where they come from. Varonis, their strength is really file share, security, monitoring, governance, remediation. Right? Commvault is a backup player. They back up everything under the sun, including they have appliances. That's why they're suffering from the memory chip pricing spike condition. So is Rubrik, and Rubrik came from the AWS world. If you look at all these vendors, and we come from the Microsoft Microsoft 365 world, right? Just as proxy, our Azure consumption, I know this because we negotiate with Microsoft, right? We have a bigger economic relationship with Microsoft than all of these guys. That shows you how much we actually consume and burn, and then also gain revenue opportunity out of the Microsoft 365. That's our core strength. If for the enterprise, Microsoft 365 is your mission-critical platform, we are the go-to partner. We do many instances of coexistence with the players you mentioned. You also have Veeam, who target SMB. Commvault is more enterprise, so is Rubrik. Varonis is more enterprise. We cover enterprise and SMB. We're growing very well. Our public statement is that we'll continue at 26% ARR growth for the next few years while maintaining high profitability. We can do that because our core strength in that space. Of course, we are now expanding or investing aggressively into multi-cloud. We think that will allow us to have an even stronger story when it comes to that single pane of glass to be able to help you manage all your workloads, including AI, across multiple vendors. Got you. Okay. The fact that you guys are playing in various segments of the market, enterprise, mid-market, SMB, you're strong in a lot of different regions, especially outside the U.S. You don't have one vertical that's more than like, what, 15% of revenue or something, right? No single customer more than 2%. No single. Yeah. I guess that in some ways that's great. In some ways, somebody might say, "Well, you're not focused." How do you respond to somebody that, where's the focus of the company from a go-to-market standpoint? We do have dedicated divisions that focus on SMB, mid-market, enterprise, and then obviously dedicated regional coverage. We even, for public sector specifically, we have a vertical practice that's only focused on public sector housing, Arlington, Virginia, in a security cleared facility. Within the business, we have domain focus, for sure. I think maybe to our own detriment is that we historically have been very fiscally conservative. We built this business without acquiring any, and then so far, we've done six small acquisitions since we've gone public. Now we have appetite to leverage our strong balance sheet, not only to do stock buyback, which we have done plenty, like last year did $50. Far as of earning that we went out, we did $70 already, and we topped up to another $150. We're doing strong stock buyback because we think we're undervalued. At the same time, we still have a very strong balance sheet. Like I mentioned, we generate $100 million free cash flow this year, to do some meaningful inorganic expansion on extending our platform. That will then accelerate our timeline and growth because all the guidance we've given out is all 100% organic. Yeah. I think we built to counter to what you mentioned. We feel that, yes, we're very fiscally disciplined and conservative, but we took the time to really build solid foundations around the world, around the segmentation coverage. Now that we have the capital, and potentially we can even use some leverage, we can really take advantage of this golden window we have in front of us and go faster. Yeah. That's the number one ask, to show us how you're taking advantage of the AI tailwind and show faster. Acceleration. acceleration. Acceleration. Trust me, we take that to heart, and that's our number one priority. Okay. In the minute we have left, I want to bring Jamie in here. Just from an investor relations perspective, what do you think the most underappreciated when you talk to investors, like what do people not get about the story? Like you said, it feels like you're not getting the respect that you would deserve from the type of growth, the consistent growth that you've shown. I think the balance that Tianyi Jiang just talked about with however you look at the business, the demand has been very strong and consistent, is something you just don't see in a lot of companies, particularly of our size. I think our desire, I think, to get to the point that Tianyi Jiang was talking about, of having this meaningful scale is real, and I think is going to be seen this year and in the years to come, just given how much demand there is and how, I think, focused our leadership team is on sort of delivering that. That will help solve kind of that problem. I think so. When you get to that type of scale. Yeah. Where it's like nobody can really deny that. Yeah. Have arrived, so to speak. I think we did 12 consecutive quarters of outperformance. Now it's really size, right? Size does matter. We need to gain critical size as fast as we can. Awesome. Thank you everybody for joining. Thank you guys for being here. We're going to go up to the breakout room for anyone interested, and have a great rest of the day. Thank you. Thank you.