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

All right. Hello, everyone. I'm Shilpi Saran, and I'm a senior banker in our software investment banking team based out of Menlo Park here. I'm so excited to have on the stage with me Dr. TJ Jiang, Co-Founder and CEO of AvePoint; and Jim Caci, the CFO. And TJ, Jim, Mario and Jamie just flew in from New York after their second Investor Day yesterday. And so we're thrilled to have you here. Welcome.

Thank you. Thank you for having us.

Great to be here.

So TJ, maybe start with you for -- I think most of us know AvePoint, but for those who don't, just a quick view of -- overview of what you -- what AvePoint does and the pain points we solve for our customers.

Yes. AvePoint, we're a software company focused around helping businesses around the world manage, secure and optimize their critical business data. Very much focused on the Microsoft Cloud ecosystem, but we have expanded meaningfully into Google, Salesforce and AWS as well. So we have been historically focused on regulated industry where they have a very much emphasis around compliance and auditability of how unstructured data is being accessed and managed and retired. So that's human-generated data, that's files, chats, contracts, et cetera, which is 80% of all data out there. So fast forward to today, of course, with everyone trying to experiment and deploy Gen AI capabilities, they realize that your data estate, it's paramount because otherwise, it's trash in, trash out problem. More importantly, as you continue to deploy AI, 10% of all unstructured data now are generated by AI. So a lot of that generated data go back to the input. So how do you properly govern, ensure quality and ensure access control and life cycle management of that data. It's a problem that everyone now are demanding. So we are that picks and shovel of that momentum, and that's what we have been doing globally with 25,000 customers around the world.

And so the plumbing you put in place over the last several years really seems to be like finding its moment.

That's right.

With Gen AI and what -- the data management capabilities that we need now. That's great. I think maybe if can you go more into sort of the platform, the various products you offer, at least the key product areas?

Yes, so it's a SaaS platform we call the Confidence Platform. It has major functional areas. It's actually 30-plus products. Major functional areas, what we call it business resiliency. So data backup, data archiving, storage optimization, also control, which is governance, access control and then modernization. We talk about modernizing the workforce. What that means is data analytics, data integration, data migration between systems, on-prem, cloud, cloud to cloud. So it's a large SaaS platform, and we host them in Azure. We also have instances running now in GCP, Google Cloud as well as AWS. On a daily basis, we touch about over 500 petabyte of data. So yes, it's -- and we also have instances in U.S. government data centers, such as FedRAMP certified data centers.

Got it. I mean all the categories that you mentioned, there are both public and private companies that cover in each of those categories. Can you talk about the competitive landscape? And what makes your approach so differentiated? Like why can't they get -- why can't customers get what they need from the existing solutions?

Yes. So we actually had an Investor Day yesterday where we really went into detail and showcased the platform. We talk about Beyond Secure. We talked about our approach is very different from the traditional data security approach or traditional data backup approach. The matter -- the fact of the matter is the momentum to go to cloud is there. And once in cloud, companies also need a very much of a holistic way to manage data. You cannot think of them as data management silos. So pre-cloud days, you will have easily, for example, your company will have a storage group, right? That only care about just storage. That's all they think about. And then you have a security group, that's all they think about, security. And then you have an infra group, they think about network and access. But today, increasingly, those tasks got merged together because you have data aggregation that's happening. And also with especially AI is that you do want to have exposure to the entirety of your data estate so that your AI deployed is much better than an intern, becoming more of an industry and domain-specific expert. So what this means is that all these functions is coming together. And as data aggregating cloud at an accelerated pace, we actually have to look at problems not in isolation, but holistic. I'll give you example. So obviously, we have backup as a service, and we do a ton of that on a daily basis. But as customers accumulate data in a very rapid rate, right? Now even 10% of all unstructured data is generated by AI, you also have to control the cost. And from a cost perspective, you need to reduce the footprint. And also from a quality perspective, you also need to reduce the redundancy trivial and out-of-date data so that your data estate is at a better capacity for AI deployment. So what this means is that the backup conversation is actually now tied to archiving conversation, life cycle management conversation, storage optimization conversation and even governance conversation. So we are really the only platform that does all of it end-to-end. We can then go into account with a specific use case, whether it's governance or backup or migration, modernization, but then expand very nicely. So yesterday, I gave a very good customer example of one of our global customers now of well over $2 million ARR with us and their journey since 2021 to incrementally deploy more and more of our Confidence Platform. So now we actually say the platform is the product. It's really no longer sufficient to talk about data security and data backup recovery in isolation.

That makes sense. Yes. See, Jim, turning to you for a second. I think you've successfully steered the organization through a SaaS transition. And it's never easy, even if it appears that way on paper. It's now a vast majority of your revenue. And so can you maybe talk about what the numbers look like today? And what are the most important financial KPIs that you track the business with?

Yes. I mean I think it's a great point. Those transitions are never easy. Fortunately, we did it maybe the hard way. I mean, TJ talks often about us doing the hard things first. We actually did that whole SaaS conversion. First of all, we were very early in the process and did it with really no debt, only $60 million of primary capital really over the history of the company. So going through that transition, I think, speaks to the discipline that the company has had over the past 20-plus years of actually being focused and really focused on the goals we set and then delivering against those goals. So when we think about KPIs, we kind of think about it in the same way, which is we're trying to set targets and goals that we feel very good that our discipline is going to help us achieve. And so for us, ARR is really the primary one. That's our kind of high watermark in terms of that's the first KPI, it's like what are we setting the standard at in terms of delivering ARR. Obviously, revenue is important, but that's kind of a cascading effect of what we're doing in ARR. So we're really pleased with next year's growth of 25% in ARR and guiding to that. And then if that's our North Star in terms of KPI, then closely behind that is really our retention rates because I think that really speaks to the heart of customers embracing the platform, number one, new customers, right? And then existing customers expanding. So GRR representing that ability for our customers to continue to want to work with us. So that's a great metric. We're really pleased that, that one has improved over the past several years. And then NRR, obviously, those existing customers, how much more are they going to spend with us. And so that speaks to what TJ just referred to is the product really is the platform, and we're seeing more and more of our customers consume more of the platform. Since most of our licensing is done on a seat based, it's not -- we're not seeing tremendous upselling to a customer of them buying more of the same product. What we really see is them buying multiple products and which is really the expansion of the platform. So for us, I think those 3 are probably the top metrics that we're focused on, on a daily basis.

Got it. No, I think I saw some metrics, 225 customers more than $250,000 ARR, what -- 81 customers more than $500,000, and I have 26 customers more than $1 million. So it just speaks to the breadth of adoption.

Yes. And we've been reporting every quarter, we report the first one, which is the 100,000 customers, which has been growing really nicely. But the ones you just pointed out, the $250,000, $500,000 and now $1 million, it was only 4 years ago, we had 6 customers that were over $1 million. And so now that number has expanded tremendously where we actually may start to report that more frequently just because of the acceleration in that group. So we're kind of tackling both ends of the spectrum. We have our largest customers growing, and we're adding more large customers. And then we have this SMB group that is expanding and growing probably faster than the rest of the segments we support. So we're kind of servicing all 3 segments of the market in terms of customer base, and we're really excited about continuing to do that.

So on that is that's a really unique aspect of this company, while we're just $327 million ARR last year, we truly cover all segments. So enterprise, so we sell to Fortune 50s, and we also sell to a company with just 10 employees. So that's very rare for a software company at our size. And we also do this globally, right? We have 45% recurring in North America and then 30% EMEA and then the rest in APAC. APAC has a more heavier service component. So about 13% of our total revenue is services, much of that is APAC. It's really focused on IP generation.

That's incredible diversification for a company of your scale -- of your size, yes.

Right.

We talk about that often that for a company our size, and that's why I love that one slide, you probably -- I know we've talked about it. There's a great slide in our deck that shows our ARR and kind of this diversification. So if you get a chance to -- well, I think TJ alluded to it, the Investor Day we had yesterday, it's been recorded. It's available. So everybody should go watch that. I think it was a lot of information. And one of the slides in there is this ARR diversification slide. Everything from -- we don't have any concentration in any one industry, any geographic segment. We're spread across the globe, good diversification there. So again, it speaks to, I think, what you just said, which is for a company our size, which we still know we have tremendous opportunity to grow. But we've done those hard things first in terms of global expansion. We already have the infrastructure to continue to grow. We're in 3 different segments. So I think we're well positioned to really continue to accelerate and get to the goals that TJ alluded to yesterday.

Yes. And I wanted to -- that's a great deal point. Some big announcements yesterday in terms of your goals for 2029. Can you talk to them, $1 billion ARR?

Yes. We're very excited. We're very confident to get to $1 billion ARR by 2029. So -- and so far, you see that mostly we have done our growth via organic growth. We've done 6 small tuck-in acquisitions, really focused on IP. But we have a very strong balance sheet, GAAP profitable a year ahead of schedule. I think last year, free cash flow generation was $85 million, and this year will be more. So we are really focused around, hey, can we do even more transformational expansions beyond our organic investment. So that's exciting. So the reason why we're bullish about this $1 billion number is that, as we articulated, we really have multiple avenue of growth. There's the SMB segment that's literally in 4 years went from 0% to now 20% are recurring, and that's fast growing. And SMB for Microsoft is 40% of revenue. There is this whole Google play, that multi-cloud play we announced last week, which we get Google Global senior leadership support for them. And that we're super excited about because that's a market that's almost equal in size of user counts as Microsoft Office Cloud. And of course, we have the enterprise expansion and then, of course, IP and our continued investment into security and governance. Yesterday, I think one of the analysts said you guys have the best governance product on planet. So we're happy to hear that. So there's truly multiple avenue of growth across geo, across region, across product portfolios.

Got it. So I think it's all the plumbing that you put in place the last several years, I think that this is the inflection point.

Yes. And of course, with a strong NRR that we now set the target to 115% from 111%. We think that just builds that predictability, right? So with that kind of NRR, if we don't even acquire new customers, our revenue will grow by that amount, which is -- that allow us to have that confidence as well.

Yes. That's great. And then, Jim, I think there were a couple of -- as it relates to the $1 billion ARR target, can you summarize some -- provide some more color on that and summarize some of the other guidance points that you provided?

Yes, for sure. So yes, it's a big goal. We -- like you said, we've done some of the hard things first, I think, really preparing us and setting us up well to be able to deliver that. One of the things I mentioned yesterday that -- because somebody had asked me during the break actually before we kind of even talked about it in more detail, like, hey, that's a big goal. How do you see yourself getting there? And obviously, some of the strategic vision that TJ talked about yesterday and broke it down with different vectors for us to get there, I think, is an important component. But then even one layer deeper, we really start looking at the business now even geographically spread out. It wasn't too long ago that AvePoint was just over $100 million of ARR. And now we have 2 of our regions, both North America and EMEA, both over $100 million in ARR. So what we think about is taking that $1 billion challenge and breaking it down into components. And so part of it is, well, where is the revenue going to come from or the ARR going to come from in terms of geographies, products. And so we look at that. And when you break down the $1 billion into those segments, all of a sudden, it looks really achievable, and it's manageable, right? So we think about any problem, if you break it down to its components, each of the components is more manageable. And that's how we really talked about it with our leadership team, which is, hey, you've got a job to do in North America. How are we going to get there? How can we support you? What's the growth vectors? And that seems to be really resonating with our teams around the world. Really, it kind of was supported when we did our sales kickoffs this year. The energy and the commitment to really getting to these growth numbers was evident, and people are really energized to do that.

That's great. I have some more questions, but let me open it up for a second if there's any questions from the audience. All right. We can keep going. You talked about retention, right? The key metric that you track. Can you talk about your approach, sort of the progress you've made to-date in terms of the improving numbers that you're seeing? And what needs to be done to reach the targets?

It's a great question. So we ended this year at 89% GRR. And we've set the target at 90-plus as kind of our -- we set that really 2 years ago. We said, you know what, a company of our size and where we want to go and the respect we're looking to obviously garner, we need to be at 90-plus. Like that's almost a watermark that I think if we're above that, it really demonstrates that we're a need to have and very resilient. So we set that target. Now we started to do things a couple of years ago. We invested in our customer success teams. That's both people and technologies. Whether it's telemetry built into the product in terms of how people are utilizing the product. We also utilize third-party tools to help us evaluate how customers are engaging with the product, are they getting the value out of the product? I mean we know it all in our personal lives, right? If you're getting value from what you're spending on, you continue to spend it. It's when you don't see the value that you don't spend. So key for us is ensuring that the customers are getting full value out of the platform that they expected. And so customer success is a key component of making sure that, that happens. And dovetailing into that. So that's overall investment. And then what we've noticed is if you break down our customer groups, we had a cohort that we would refer to as our, let's call it, our core cohorts. And that we have dedicated CS. And then we had this cohort, which was considered the long tail, which would be those customers that -- and it varies by region that we would say, you know what, we don't have a dedicated CS below this certain dollar amount. But that group is also very important. And when you add them in the aggregate, they make up a large portion of ARR, just not individually. So we decided to really focus on this concept of pooled CS. And so the idea there is you don't have a dedicated CS team. But with all our digital technologies as well as a pooled CS team, we're focused on ensuring that, that group is properly enabled and that they're getting the full value out of the platform. And then if there are any cracks in their value creation that they're seeing, we're able to step in and then address that and mitigate or remediate any issues that they might be having. So with that, we really focused on that in '24, at the beginning of '24, that was a key focus. And we saw improvements in that cohort, really leading to the 88% that we achieved in Q3 and then the 89% we achieved in Q4 were really coming from that cohort as a meaningful improvement over where they had been. So we think there's still more to be done there as well as with the rest of our group. So we think that we still have a lot of work to do. We're pleased with the 89%, but we know the job is not done. And we think we can even get to that 90-plus percent here in the near term, so.

Got it. And while maintaining some nice gross margins, standard SaaS gross margin...

Yes, exactly, yes.

So let's turn to Microsoft for a little bit, right? 90% of your business today is kind of tied to Microsoft's sort of rich set of enterprise apps, data that they generate, that they consume, et cetera. So you clearly first proved out the value proposition there. How do you think about sort of expanding beyond that? And how has that evolved over time? What's next?

Yes, so 89% of the enterprise today are multi-cloud. So multi-cloud is reality. So one of the artifact of that CrowdStrike incident last year is that we hear this common refrain from our enterprise customers that this is why we're multi-cloud, right? So because of that, we want to become -- expand our footprint and become more strategic partner to our customers. And they are multi-cloud, and this is why we're investing aggressively into the Google ecosystem as well as the Salesforce ecosystem. Fundamentally, customers need a holistic way to manage and govern and secure data across all their data estates, mostly the hyperscaler platforms. And so we are able to then take what you mentioned, like proven out enterprise needs across large enterprise, even small businesses now to another ecosystem, which, quite frankly, you probably already know that the Google enterprise ecosystem is not as mature, right? So of course, the pricing ceiling is keep on going up, thanks to AI as well. So that also creates opportunity for third parties to come in and help customers maximize the ROI and make better use of that extra $2 per month charge of Gemini. So there lies the opportunity. I think we're pretty excited about it at yesterday's Investor presentation, we actually upped our split, percentage split in the future to say, hey, today, while that non-Microsoft cloud ecosystem is just 10% of our revenue, we actually firmly believe that we can bring that up to 25% to 30% of our revenue as our total revenue continue to grow 25%.

Yes. No, I talked to so many clients, my husband works at a firm where we have -- they're all using Google docs, et cetera, for their work. And you said they're not -- it's not as mature, but it's getting there.

Even big companies, right? Capital One are now all on Google.

Yes. I think can you wait just a second for the mic?

[indiscernible] Microsoft Copilot adoption because you guys definitely have a front row seat in terms of to see how that's going. So can you comment on the traction? Are people finding use cases real valuing it?

Yes. Yes, we definitely do have front row seat. We have enough data points around the world. It's like how ADP is cutting Paychex, right? They have enough data so they can actually tell whether we're in a recession or not. So we actually have very good data points around global adoption of all of the different Microsoft SKUs. The Copilot active use, so this is interesting. Majority of the customers are -- have some Copilot for experimentation, 70% to 80%. But the total, if you actually just count the active user seats is still in the low single percentages, despite Copilot being out for 1.5 years now. I think the real challenge ultimately, it comes back to a data problem. So if you just use Copilot as in its raw form, whether it's in Teams or in e-mail or Office, your experience is not optimal, right? Because it's just not tailored and tuned to your need. So this go back to that, again, that data problem we talk about. Where we see success is enterprise using Copilot Studio or Azure Cognitive Services, which is API gateway to OpenAI to specifically build an AI instance that's fine-tuned with and trained with their own corpus of documents for specific purpose. So for example, we actually roll out what we call ChatAVPT internally. It's trained with -- have an HR persona, have a tech support persona, have a partner support persona. So then when you actually talk to this chatbot, then you actually have very meaningful output from that. So it is that intentionality that's happening across enterprise that say, "Hey, I cannot just blankly roll out AI and hope that it's going to work." There is work to be done to actually make that much more purposeful and reduce the hallucination, right? So I think having said that, Copilot is getting better so there's been a lot of changes. I recently talked to the President of Microsoft APAC. She actually said, Miki-san, she actually said half of all the new Copilot feature requests come from Japanese customers. And we all know how demanding the Japanese customers are and how detailed they are. And Japan is our second largest market outside the U.S., right? So I think we will see incremental improvements. Now does that justify the $30 per user per month charge? Probably not yet. And you already see Microsoft doing some modifications to their pricing bundle, so did Google. So there are various components that they're increasingly making it for free. So it's an evolving space, but we do see incrementally more enterprise deployments. So last quarter earnings, we actually cited a global bank that roll out Copilot to all their employees after they activate our governance product set for access control because otherwise, if you don't manage it properly, Copilot is an excellent way to leak and overshare data. That's also a big, big problem for companies. So -- but yes, we do see that. That's why we always say, hey, maybe enterprise deployment will be more of a second half this year and even 2026 conversation. But having said that, there are purpose-built AI projects within enterprise that are quite successful already.

Excellent. I think to talk about sort of your move, the incredible diversification, you have successfully expanded your partnership with MSPs. And at the Investor Day, you provided an overview of the next generation of elements. It's your platform that's aimed at the MSPs. Can you tell us more about that? Like what is new in this updated version? And how do you expect it to benefit both AvePoint, of course, and MSPs' partners?

Yes. We're very excited about the Elements Platform. It's really grounded on our Confidence Platform. But the way we design Elements Platform is to unlock effectively the SMB segment for us in that we changed the interface to -- and the go-to-market. So it's really designed for IT organizations that are purpose-built and managed service providers to help small businesses handle their cloud assets. So they will then use our software as mission-critical to manage and scale to hundreds of small business tenants and be able to do backup, to do governance, to do data migration, to do monitoring and entitlement management, license management. So what we rolled out in addition to that is what we call baseline change management, risk management, allow these folks to have sophisticated enterprise capabilities so that they can do more day 2, day 3 for us, day 2, day 3 products, but to do more with their services. So we even offer example of, hey, this is how MSP charges to their customer. Their end customer doesn't see our product at all. The MSPs are basically special purpose IT organizations that are using our product to then scale and charge customers. For example, many times, when we provide the backup as a service for the MSPs, we charge them based on the seat counts, and we give them pool licensing, monthly contracts, 2-tier pool licensing. So it's very flexible. But they don't even charge their customer based on per seat. They charge them based on per restore. So there's various -- so this is very interesting, right? So it actually opens up in a very dynamic way how the software is being licensed and used. And we even had a very large customer, Crayon, which is a global company. The says for every dollar they spend on our software, they generate $5 services opportunities. So that's the massive opportunity for our partners to leverage our platform.

Yes. And for you, MSP is the customer, end customer.

That's right.

Great retention.

Great retention. And as TJ said, we're no longer a cost center to that MSP. We're actually a revenue generator because they look at our software as a way that they can increase the services they provide to their customers. So it's an interesting dynamic and a great partnership.

Fantastic. I think you've mentioned you intend to do a list in Singapore, right? Tell us the rationale behind that.

Yes. So we have a very strong APAC story, right? 2/3 of our employee population now number 3,000 are in APAC and 50% are in ASEAN. So this is actually one of our massive competitive advantage. We also mentioned 50% of our employee population are developers, which is massive for self organization. And yet the cost of that is just 1/4 of our total cost, right? So that's a huge competitive advantage where we have massive dev capacity to continue to stay ahead of the tech curve, and that's super important. This is why when people say when Gen AI come out, people say, "Oh, developers not going to have a job anymore." I 100% disagree. I think we're going to have more developers because there's infinite amount of software to develop, right? They're just more efficient. So finally, maybe we have a chance to have software eat the world, right? Because we have so much tech devs still, especially at large banks still leveraging mainframe, for example. But anyway, so Asia has been a big IP driver for us, especially in Singapore, 90% of our business is with the government. And we actually drive a lot of this governance, data management, record management product out of the government institutions and edtech. So we have large portfolios within the university in Singapore, and they have very high requirements. So that allow us to leverage that as an IP generation center. So because of that, we are very attractive in Asia to institutional investors, long-term institutional investors in APAC who has an APAC investment mandate. So in America, we're still pre-mid-cap company. I like that term, pre-mid-cap. We like to be mid-cap soon, but we're still pre-mid-cap. And in America, mid-cap is effectively $10 billion in market cap. So until then, we're not really necessarily getting the long-term institutional investors' attention. So I think part of our job, Jim and I, is also to create shareholder value and also trying to get long-term institutional investors, blue-chip investors to come in as part of our cap table to form that long-term support. And this is really the reason behind it.

So diversification in customer base, diversification in investor base.

That's right.

That's the theme. We do live in a multiparter world.

That's exactly right. Another question, yes.

Sorry, I do want to ask maybe a follow-up to the Copilot adoption question. I think you had like a really good point where a lot of the use case needs to be very specific. The model need to be fine-tuned to the specific use case.

That's right.

I think that echoes to what I think Snowflake and Databricks are talking about yesterday. So I guess like are you guys also adding value or providing support where your customers are fine-tuning specific use cases within the Microsoft ecosystem? Just want to understand how you guys play there?

Yes. So the foundational problem to all AI deployment is data quality and data management. So whether you do specific use case deployments or across all your employees via Copilot, fundamentally, you need to have a good handle on your data because enterprise data is messy, right? So for decades, enterprise search was a terrible thing. Even Google Search appliance when you apply to enterprise is not good. Why? Because you think about the example, right? So Google was -- is great in the Internet on the public domains because every company is optimizing their own website for SEO. In the enterprise, nobody is optimizing anything for their own files, right? Your files in e-mail, you have duplicates, 70 attachments, bankers love to e-mail each other, same attachments, lawyers the same thing. So you need software to automate that reduction in version control and also in regulated industry, especially in life cycle management. So all of that at the end of the day actually matters when it comes to AI. So you're basically shrinking the corpus of quality data to be more manageable to then apply to AI for refinement model because it doesn't matter which -- I get this question yesterday a lot about DeepSeek, for example, right? It really doesn't matter which commercial off-the-shelf large language model you use, open source large language model you use. Ultimately, you want to turn AI from, again, infinite summer intern to infinite experts, you do need a refinement training with your domain-specific proprietary data that matters to your company, matters to your specific industry. So in that regard, it is a data management, governance and security problem. And so one of the big use case now is, hey, let's use Gen AI as a better search. That's what everybody does. And then very quickly, they realize that it's now telling you things, either hallucinate things when you have too much trivial out-of-date redundant data or it's telling things to you that you should not have access to, right? Because we all know segregation of knowledge within enterprise, especially in the regulated industry. So there lies the problems that we have to help customers solve.

I think we got a minute. So you touched on DeepSeek. Clearly, a mic drop moment for the industry after ChatGPT, right? The true democratization. What does that mean for your business? And what are you excited about?

No, we're super excited because it just -- it's fantastic. It just means to lower the cost of deploying AI, right? So more companies can experiment. Government can now experiment when they cannot have access to the worldwide web. So they can have local instance of public models, open source models. So Lambda is not the only option and smaller models, right? So smaller footprint and more energy efficient to actually get answers. So all of this means there's going to be more push towards adoption and experimentation. So that's actually great. And for us, again, it doesn't remove the foundational problem of data quality, data governance and data security. And that's the game we play. And we actually see more and more customers experimenting. So that's good.

No, we're super excited. I think the $1 billion ARR goal for 2029, we see the path there with the way you've clearly laid it out. So kudos to your team and congratulations and just a round of applause for TJ and Jim.

Thank you.

Yes. Thanks for having us.

Thank you for everyone for coming at 7:00 am session.

Yes, thank you.