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Tianyi Jiang: Thank you, Jamie, and thank you to everyone joining us on the call today. Q1 was a strong start to the year. Our leadership at a critical intersection of data protection and security, combined with the growing demand for AI-ready solutions, allowed us to again exceed our guidance on both the top and bottom line. Q1 also marks our 12th straight quarter of double-digit growth in organic net new ARR, which we delivered while driving more than 730 basis points of GAAP operating margin expansion. Importantly, we're delivering strong results during a rapid shift in the market. It wasn't long ago that AI discussions with customers focused entirely on models and productivity gains.
As AI is becoming deployed more widely and evolves from assistance to autonomous agents, data access increases exponentially and data governance becomes top of mind. Today, when I meet with customers and partners globally, the question is no longer what can AI do for my organization, but rather, can I trust, govern and operate AI safely and at scale. In short, the conversation has pivoted away from productivity and towards something far more important, enterprise trust in this new enormously powerful technology. This is where I would like to focus my time today, how organizations can achieve this level of confidence and why AvePoint is uniquely positioned to deliver on this demand.
To answer this question, it's first important to understand the AI stack today, which starts with infrastructure, energy, chips, physical compute hardware and so on. These components are important, but it's also fair to say that they are table stakes today and are quickly becoming commoditized. The real center of gravity, not surprisingly, has shifted to data, the knowledge that powers AI and fuels the next 2 layers, AI models and agentic AI. For every organization, it's here where value is created, but it's also where risk multiplies because every AI system inherits and leverages what sits underneath it and weak data governance and poor data controls lead to bad decisions and security risks, in turn destroying trust.
Ultimately, once trust is lost, AI doesn't scale. This is critical because as AI agents operate more autonomously across enterprise productivity apps, companies truly need a trust layer so that they can scale AI adoption without losing control of data security, privacy and compliance. It's equally critical to understand why it's different now and what exactly has changed for enterprises seeking to govern data. At a high level, the most commonly leveraged productivity tools today like Microsoft 365, Google Workspace, Salesforce and others were originally designed for human productivity and not autonomous AI execution.
As a result, with the rapid emergence of AI tools that are processing more information at greater speeds and scale than ever before, data governance must also evolve. This is exactly where AvePoint comes in, and the customer demand for this trust is the real AI opportunity we see. It's why we're building the trust layer for AI, spanning data, governance, risk and operations so that organizations can deploy AI securely responsibly and with confidence. We believe that organizations can only trust AI when they prioritize 3 things: first, precisely control what AI can access; second, govern and audit every action AI takes and finally, recover instantly when something goes wrong.
This trust layer must do all of these continuously, all while maintaining data lineage across both unstructured and structured data sources. The resulting contextual data is an enormous competitive advantage for AvePoint and truly distinguishes us from legacy point solutions and backup first vendors. This differentiation was also recently validated by Gartner, who specifically cited AvePoint's comprehensive set of capabilities and platform strategy as superior to native offerings like Microsoft's Agent 365. Let me bring this to life by discussing our integrated approach, along with some specific capabilities and recent enhancements to our platform. First, see. We offer unified real-time visibility across the entire data estate, including what AI agents touch and how access patterns change.
New this quarter, organizations can now see across their entire agent stack, including Copilot Studio, Microsoft Foundry, SharePoint Agents and Gemini Enterprise, all within one screen in Agent Plus. Second, Govern. Our platform provides automated policy enforcement, compliance standards and access controls across every environment and workload, including AI agents acting as virtual employees. This quarter, we launched a new risk definition for AI agents, so organizations can better access more information about agent security and correct problems automatically. This is especially critical because unmanaged agents can lead to runaway costs and expose sensitive data without proper oversight. Lastly, recover. We ensure granular, automated recovery from any failure, whether caused by ransomware, human error or autonomous AI activity.
The speed with which we can do this is unmatched as we can often recover several petabytes of data per hour. Lastly, we made significant investments into Google Cloud Protection this quarter and recently added multi-SaaS backup sources like Okta, Confluence, Jira, DocuSign, monday.com, GitHub and Smartsheet, adding to our growing library of protected data. This integrated approach, see, govern and recover is powerful because it transforms AI risk into a manageable variable and ensures that the trust layer is a foundation for AI-driven growth, and it is resonating across the market, firmly cementing AvePoint as a foundational infrastructure that enables safe AI deployment at scale.
A great example of this is a U.S. pharmacy benefits manager that became a new AvePoint customer in Q1. They wanted to roll out Copilot but knew they faced data sprawl issues with little visibility and control over 500 terabytes of unclassified data, seeking a single vendor who could address multiple strategic use cases, they purchased our highest tier control bundle along with OPUS from our Resilience suite. Ultimately, choosing AvePoint because our automated governance, life cycle and access controls would enable them to deploy Copilot with confidence and streamline the regulatory audits they face on a regular basis.
They also plan to use our modernization suite for future data consolidation efforts aimed at reducing their tech debt and retiring their on-prem footprint. The customer need to rapidly address multiple strategic use cases is extremely common today given the number of ecosystems and applications our customers are using and the ability of our platform to protect and govern data regardless of where it resides is a unique competitive advantage. This was the driver for a large transportation and logistics conglomerate, which initially engaged AvePoint during the pandemic to decommission an on-premises data center and migrate roughly 50 terabytes of file share data to Microsoft 365. This effort went beyond the basic migration.
The customer needed to preserve permissions, retention policies and governance while modernizing their environment. AvePoint supported this transformation with capabilities spanning modernization, control and resilience, enabling a secure transition to the cloud with strong governance and operational oversight. As the customer's environment matured, the relationship expanded to include broader governance and data protection. In 2025, when the customer began planning a shift from Microsoft 365 to Google Workspace, AvePoint's multi-cloud capabilities became increasingly strategic. The platform helped prepare data for transition through classification, policy management, insights and cleanup, ultimately leading to a Q4 2025 award for data transformation services supporting the move. Rather than being displaced, AvePoint's role strengthened providing consistent governance and resilience across cloud environments.
This foundation also supports the customers' AI readiness as they adopt Google Workspace and Gemini, ensuring data is trusted, controlled and recoverable. Lastly, the foundation enables real-time situation awareness for the customer, where our platform's advanced reasoning can identify and surface urgent logistics action items, such as a delayed shipment or an unread threat about critical rate change before it is too late. Looking ahead to a planned 2027 migration into the parent company's Google tenant, the engagement exemplifies AvePoint's land and expand strategy, evolving from monetization to a strategic platform for multi-cloud governance, resilience and AI-enabled collaboration.
This need for integrated platform solutions that deliver rapid automated value against multiple strategic use cases is only growing, especially in the highly regulated industry that represents the majority of our business. For example, effective data governance in the healthcare industry is more than better visibility and oversight. It's about patient safety, regulatory compliance and operational resilience. One of our largest customer recently shared that bundling Agent POS within the broader governance capabilities of our control suite has provided them visibility into thousands of agents without having to make a separate business case related to their MC65 deployment. We're hearing similar feedback from partners.
Our latest report conducted in partnership with Omdia, the leading global channel technology market research firm, revealed that nearly half of MSPs want a complete platform integrated with other core tools and 91% say that integrating data backup and disaster recovery delivers stronger data governance than offering them separately. We saw this many times in Q1 with existing customers who added to their AvePoint deployments, and we continue to believe that our nearly 30,000 customers still represent an enormous growth opportunity for us. For example, an Austrian luxury goods conglomerate that already own OPUS needed to ensure business continuity as well as tailored lengthier retention policies for their data in M365.
With native capabilities not allowing for this level of customization, they purchased cloud backup from our Resilience suite in Q1, and we're now discussing the many strategic use cases that can be addressed with our control suite. Despite the noise across the software space for the last few quarters, our strategic priorities have not changed and our growing conviction in our 2029 goal of $1 billion in ARR remains as strong as ever. The relentless growth of data and the growing demand for platform solutions that enable AI deployment at scale will ensure that AvePoint remains a top priority for enterprises around the world, and we're excited for a strong 2026. Thank you again for joining us today.
James Caci: Thanks, TJ, and good afternoon, everyone. Thanks for joining us today. Our first quarter results were an excellent start to the year and a continuation of the healthy momentum and market demand with which we closed 2025. As I discussed last quarter, very few software companies have AvePoint's organic growth profile, scaling operating margins and GAAP profitability, material cash flow generation and healthy SaaS KPIs. Our Q1 results once again highlight these strengths and demonstrate our ability to consistently execute on our commitments to shareholders. Let's turn to the quarter. Total revenues in Q1 were $117.2 million, representing 26% growth year-over-year and above the high end of our guidance. On a constant currency basis, total revenues grew 20% year-over-year.
SaaS revenues were $93.4 million, growing 35% year-over-year and representing 80% of total Q1 revenues, surpassing last quarter's record and exceeding our mix expectations. On a constant currency basis, SaaS revenues grew 29% year-over-year. Term license and support revenues declined 29% year-over-year and represented 8% of Q1 revenues compared to 12% a year ago. I would also point out that beginning this quarter, we are now including our legacy maintenance revenues in the term license and support revenue line item for all periods presented, given that maintenance is immaterial now to our total revenues. Lastly, services revenues grew 33% year-over-year to $14.5 million, representing 12% of Q1 revenues.
As a result, 88% of our Q1 revenues were recurring, and on a constant currency basis, services revenues grew 27% year-over-year. Our healthy momentum is also evident when we look at revenue performance by regions. In North America, total revenue growth was 21% year-over-year, driven by SaaS revenue growth of 32%. In EMEA, total revenue growth was 30% year-over-year, driven by SaaS revenue growth of 39%. In APAC, total revenues grew 28% year-over-year, driven by SaaS revenue growth of 37% and services revenue growth of 46%. On a constant currency basis, EMEA SaaS revenues increased 26%, while total revenues increased 18%. For APAC, SaaS revenues increased 32% on a constant currency basis, while total revenues increased 22%.
The same top line strength by region is evident when looking at ARR. In Q1, North America ARR grew 21%, EMEA ARR grew 32% and APAC ARR grew 27% as we ended the quarter with total ARR of $435.2 million. This represents year-over-year growth of 26% or 23% after adjusting for FX. As a result, net new ARR in Q1 was $18.4 million, representing growth of 17% year-over-year after excluding the $2.8 million of the ARR that was acquired in Q1 of last year. As TJ mentioned, this was our 12th straight quarter of double-digit growth in net new ARR.
Lastly, as of the end of Q1, 58% of total ARR came through the channel compared to 55% a year ago. Last quarter, we called out our consistent success at the enterprise level, and this momentum continued in Q1. We ended the quarter with 863 customers with ARR of over $100,000, a year-over-year increase of 25%, an acceleration from last quarter's record. We are pleased that the growth rates for our larger customer cohorts were all higher than the 25% growth from our $100,000 cohort, demonstrating that we continue to meet the demands of the highly complex organizations looking for single platform vendors that can address multiple strategic use cases. Turning now to our customer retention rates.
Adjusted for the impact of FX, our Q1 gross retention rate was 89%, a 1-point improvement from Q4, while our Q1 net retention rate of 110% was in line with Q4. Similar to prior quarters, our migration products again served as a 2-point headwind to GRR given their naturally lower retention rates. We would not be surprised to see this dynamic continue, especially given the recent elevated demand for migrations we called out last quarter. On a reported basis, Q1 GRR was 89% and NRR was 111%. Turning back to the income statement. Gross profit for Q1 was $86.1 million, representing a gross margin of 73.4% compared to 75% a year ago.
The year-over-year gross margin decline is primarily the result of lower gross margins on our services revenue this year versus a year ago. Moving down the income statement. Operating expenses in Q1 totaled $65.6 million or 56% of revenues compared to $56.5 million or 61% of revenues a year ago. As a result, Q1 non-GAAP operating income was $20.5 million, representing a 17.5% operating margin as well as year-over-year expansion of 310 basis points. Importantly, our ongoing management of stock-based compensation, which was 6% of Q1 revenues, has driven an even stronger expansion of our GAAP operating margins, which were just under 11% in the quarter and expanded more than 730 basis points year-over-year.
Taken together, these results demonstrate that our investment year is not a retreat from profitability and proves that we can fund our AI road map while simultaneously delivering meaningful leverage across the business. On a Rule of 40 basis, which for AvePoint is the sum of ARR growth and non-GAAP operating margin, we finished Q1 at the Rule of 43. Using the more traditional Rule of 40 components of revenue growth and free cash flow margin, we finished Q1 at the Rule of 51. Turning to the balance sheet and cash flow statement. We ended the quarter with $444 million in cash and cash equivalents.
For Q1, operating cash flow was $24.3 million or a 21% margin, while free cash flow was $23 million or a 20% margin. This compares to operating cash flow of $500,000 and free cash flow of a negative $1 million a year ago. Last quarter, we discussed the acceleration of our share repurchases, reflecting our belief in the underlying strength of the business and commitment to driving shareholder value. This increased pace continued in Q1 as we repurchased 5.4 million shares for approximately $60.8 million. For reference, we spent approximately $50 million on share repurchases in all of 2025. Through the close of trading on Friday, we have bought another 1.8 million shares for approximately $17.7 million.
Given the increased pace of our buying, our Board of Directors has authorized the replenishment of our existing share repurchase program back to $150 million. I'd like to make 2 additional points on our repurchases, which remain a key pillar of our capital allocation framework. First, they have minimized the dilutive effects that we see from the issuance of shares to employees. Second, we are generating meaningful cash flow even after accounting for repurchases. As our cumulative free cash flow after share buybacks over the last 3 full-years is approximately $78 million. Turning now to our guidance, where I want to provide some color.
First, we are raising our full-year guidance for ARR, which reflects our momentum and healthy demand we see. Second, our updated full-year guidance for revenue and non-GAAP operating income only includes the Q1 outperformance relative to guidance as we account for the increased SaaS mix we now expect for the balance of the year and the impact it may have on reported revenues. The last point is around FX, where the global nature of our business exposes us to fluctuations in currency exchange rates and the currency headwind we saw in Q1 from the strengthening dollar has continued in Q2.
The corresponding incremental FX headwinds we expect for the rest of the year are also reflected in our updated full-year guidance and more than offset the ARR raise and the Q1 outperformance. We have included a slide in our investor presentation that outlines this progression from our original guidance to today's updated outlook. As a result, for the second quarter, we expect total revenues of $120.3 million to $122.3 million or growth of 19% at the midpoint. On a constant currency basis, we expect revenue growth of 18% at the midpoint. We expect non-GAAP operating income of $18.7 million to $19.7 million.
For the full-year, we now expect total ARR of $523.4 million to $529.4 million or growth of 26% at the midpoint. This includes a $0.5 million raise from our prior guidance, offset by an FX headwind of $2.2 million. On an FX-adjusted basis, we continue to expect total ARR growth of 26% at the midpoint. We now expect total revenues of $509.4 million to $515.4 million or growth of 22% at the midpoint. This includes the Q1 beat of $1.8 million, offset by an FX headwind of $2.9 million. On a constant currency basis, we expect revenue growth of 20% at the midpoint.
Lastly, we now expect full-year non-GAAP operating income of $91.5 million to $94.5 million, which includes the Q1 beat of $700,000, offset by an FX headwind of $2.2 million. Finally, on a Rule of 40 basis, the midpoint of our updated full-year guidance is a 44%. In summary, we are proud of the team's strong start to the year. We are excited for a strong Q2 and 2026 as we are well positioned to capitalize on the enormous market opportunity we see. Thanks for joining us today. With that, we would be happy to take your questions. Operator?
Operator: [Operator Instructions]. The first question comes from Joseph Gallo with Jefferies.
Joseph Gallo: Can you just unpack the 1Q performance a little bit? Was the 23% constant currency ARR growth in line with your expectations? I assume so given you modestly raised the full-year, which is really impressive. Then just maybe just walk us through the confidence in that acceleration from 23% to 26% constant currency throughout the year.
James Caci: Yes. Thanks, Joe. Short answer is right in line with our expectations coming off of just really providing that guidance in February at the end of February. No real surprise. Obviously, little FX impact, but pretty much right in line with what we expected. When we think about the full-year kind of accelerating from that 23% to 26%, one of the key things for us is that you may recall last year, we definitely had a lot of uncertainty, and it was a tough year for our U.S. public sector. Now obviously, our public sector is a global business, but we definitely saw some softness last year in our U.S. public sector, particularly in the federal space.
What we're seeing this year, and we're already seeing in Q2 is some traction, some pickup. Our pipeline is growing. We see some nice growth rate that's going to propel really the second half of the year, particularly in public sector. That definitely is an impact and will gives us the confidence today to sit here and see that we have a pathway to that 26% growth.
Joseph Gallo: Then just as a follow-up, TJ, you've been tremendously bullish on the potential of AI this quarter, last quarter, quarters before that. I think the last disclosure you gave was Control Suite was growing 18% year-over-year ARR in 4Q. Are we seeing a rebound in those growth rates? Or as investors, what metrics should we be monitoring that correlate with the positive AI message that you're articulating?
Tianyi Jiang: That's a great question. First of all, AI is a tailwind for us as we play the infrastructure layer, we talked about the trust layer in the prepared remarks, above the energy, the chips and the data and right beneath the corporate fine-tuned training model and then, of course, AI and workflows. That's the space that we operate, and we're very comfortable in that space to do the end-to-end data curation, management, governance. It's really pervasive across our entire AOS platform. Now we did announce AgentPulse, that's driving a ton of interest and also actual results. Nearly half of our pipeline now is the control suite.
It's really lifting up our overall significance around the end-to-end multi-cloud agent discovery, agent management, agent cost management as well as ultimately shutting down our rogue agents as well as recovering from damages potentially done by agents. Really, we see ourselves as the only end-to-end players in that space to help our customers gain confidence and trust into their enterprise AI deployments.
Operator: The next question comes from Shrenik Kothari with Baird.
Shrenik Kothari: TJ, you mentioned about the expanded protection into Okta, a bunch of Atlassian offerings, Cosmo CV, etc. Just how should we think about both the overall TAM expansion across the SaaS identity and developer estate as well as potential timing of how this opportunity plays out? Then I had a quick follow-up for Jim.
Tianyi Jiang: Yes, that's a great question. Firstly, the reason we supported all these multisources is because that's what we see with our customers. Our customers are multi-cloud, and they also leverage different vendors for different aspects of their data repositories and enterprise needs. We actually see the demand very strong, especially you talk about timing, right? In Q1, when the height of the conflict in the Middle East, many of our MENA as well as so Middle East, North Africa as well as European customers are very, very keenly aware on the data resiliency aspect of it. We actually see tremendous demand in those markets. More demand, not less for resiliency and also into these new data sources.
It's actually a very good positive movement for us in that regard as part of our overall platform to drive entire life cycle of resiliency.
Shrenik Kothari: Just a quick follow-up, TD and Jim, feel chime like. If AI governance and you went into great detail, it's increasingly mapping to a lot of great outcomes, right, across your offerings, including lower storage, better audit readiness, also reducing agent spend. How do you think about the value capture? I know you have mentioned about potential outcome-based approach and packaging optimization. Where should this consumption or outcome-based pricing first become material? If you can give some anecdotes.
Tianyi Jiang: Yes. We actually do more services now as well, as you saw in the Q1 pickup. That's really focused around AI modernization efforts. What our customers discover and our partners is that given our pedigree and our capabilities around day-to-day curation, management and governance, we actually help them lead to much faster, positive and confident AI deployment outcomes. The services component is part of that. It also allow us to stay very close to the customer to see where really the market is moving. Different geos have different characteristics, because we do cover the globe. We're very positive and confident in continuing that type of outcome as a service type of engagement to stay close to the customer.
In terms of licensing, we follow the market makers. In the productivity side, whether it's Office Cloud or Google Workspace, it's very much the whole market is seat-based licensing. On the compute side, whether it's GCP, whether it's Azure, whether it's AWS, that's very much consumption-based. What we look at is IaaS, Infrastructure as a Service, PaaS, Platform as a Service and of course, very much all the agentic work that's very much running on the compute side. That's the consumption side. Of course, we layer in our service -- outcome as a service capabilities to help our customers modernize AI. I will also say we see the greatest demand from regulated industry because they fundamentally understand this problem set.
Rest of the market is still taking time to reach that keen awareness of the need for proper end-to-end data management governance. The regulated industry are moving rather quickly, and we see the chunk of the larger deal engagement happening there. Yes, so that's -- we continue to see a tailwind.
Operator: The next question comes from Erik Suppiger with B. Riley Securities.
Erik Suppiger: As customers start adopting AI agents, is there a difference in the way that they prioritize securing primary data versus secondary data?
Tianyi Jiang: I think I was just with a sizable customer yesterday. I think the priority of priorities is to guard against and make sure that they enterprises have a handle on now the shadow AI. Everyone -- many people, employees within the organization are doing AI by coding, standing up AI agents with whatever commercial off-the-shelf offering that are out there. That is something that everyone really focused on. First step is to audit and discover and, of course, bring those agentic processes under control. That's what we see. Also your question around data. Fundamentally, the AI enterprise deployment does ground on good data.
Where we see these data silos that's happening and messy data, IoT data redundant as a trigger data, that does lead to inferior outcome when it comes to AI. We really focus around unstructured data. Really helping enterprises look at across their unstructured data repository, which is, again, 80% of all data out there, that's e-mails, that's chat, that's files, that's contracts. That's also the type of data that Gen AI is very good at in shifting through, ingest and be able to inference intelligence out of. It's also that corpus of data set that need to be better curated, better governed. From a risk and compliance perspective, enterprise have more confidence in that AI deployment.
Operator: The next question comes from Todd Weller with Stephens.
Todd Weller: Could you elaborate on the durability demand you're seeing in the resilience segment, kind of break down how much growth is coming from new customers versus expansion? Then also tie into that the bundling strategy and how that's influencing deal sizes and growth?
Tianyi Jiang: Yes, I'll comment on the first part, and then I'll let Jim talk about the financial details. We see very robust growth in the resiliency side, especially as my earlier commentary in the EMEA territories, given the heightened awareness of resiliency when Azure -- when the hyperscaler data centers, in this case, AWS are taken offline, that increases the awareness of failover resiliency. Of course, almost every other day, we read about AI rogue agents going out there and destroying certain significant segment of enterprise infrastructure when it comes to data. That's also very top of mind for our customers. The demand for resiliency is very high. We have to caveat that it's part of our platform.
We view ourselves as really the only vendor out there that does the end-to-end, not only the resiliency to recover a bit, but also obviously, the control, life cycle management, governance, curation of data, but also importantly, governance agents and raising awareness on the cost. The agent cost is actually another very big topic across our enterprise -- all customers because if you're not monitoring the agents, it will go true up as many tokens as you allow it to consume. Agent and token consumption, token optimization is now a very large topic. It's rolled into this whole AI governance topic as well.
James Caci: Then maybe the other piece to that question about how much is coming from existing customers versus new customers. If you look in general across all our products, we're roughly 60-plus percent is coming from our existing -- or I would say, new ARR is coming from our existing customers, so about 60-plus percent with the balance coming from new customers. Obviously, that fluctuates from quarter-to-quarter. I would say in resilience, we're roughly in that same category, same range. Again, that does fluctuate from quarter-to-quarter, but I would use that as kind of like a baseline.
Operator: The next question comes from Derrick Wood with TD Cowen.
James Wood: TJ, I just wanted to touch on Microsoft starting to see some inflecting adoption of Copilot. They had 5 million seat adds last quarter. Could you give us a sense as to how you've been able to participate in this accelerated activity and if this is driving stronger pipelines? Or is demand kind of being brought more into the Azure AI studio type of environment?
Tianyi Jiang: That's a great question. I think $5 million is still a very small fraction of the total deployment seats for MCC 5. We actually see far more what you referred to than the latter, the Copilot Studio deployment of AI for specific use cases. Same thing across Google space. Google Gemini, it's a very, very robust growth, especially in enterprise as well as now in U.S. public sector. We actually see across the spectrum of AI deployments and adoption. That's very exciting. That's very much a tailwind that we actually get involved in. It's more of the overall AI adoption and evolution rather than the specific Office Copilot deployment numbers that's driving our growth.
James Wood: Jim, maybe one for you. You talked about SaaS mix shift this year versus maybe what you were originally thinking. Can you double-click on that and why it would be higher and what that means in terms of the impact to the on-prem business?
James Caci: Sure. I'm glad you brought it up, Derrick. Yes, so we noticed that in Q1, definitely of the business that was closing, more of that was showing up as SaaS in terms of just the dynamics as opposed to us having to do revenue recognition as a term license. What that means in the short term is that you're recognizing less revenue upfront. If you remember in that term license scenario, you have a larger percentage recognized immediately and then a smaller percentage recognized ratably over the rest of the contract. Obviously, in the SaaS environment, it's ratable over the whole term.
When that happens, when we see more of a shift or in our case, even from a budgeting point of view, we have to make an assumption as to what that split is going to be on new business. We were assuming a higher percentage of term, which would have resulted in more revenue in the short term. Now this is a good thing long term for us. We want to see more ratable revenue, makes it easier to predict, easier to forecast.
In the short term, and even in our guidance for not only Q2, but Q3, we've kind of assumed that this new paradigm for at least what we saw in Q1 would be fairly consistent for the rest of the year. As a result, the revenue is not going to be what we expected it to be, which is why you see me not raising guidance. I would have liked to have been in a position to raise guidance for revenue, matching what we did with ARR. Because of this mix, I'm actually going to see less of that revenue anticipated growth.
We've kind of left guidance the same because we're actually seeing, as TJ mentioned, some additional services revenue, which is nice, and it's above what we had budgeted. That's a little bit of an offset, but this mix shift definitely will result in less revenue coming from the products in the short term. Then obviously, long term, it all evens out.
Operator: The next question comes from Kirk Materne with Evercore.
Vinod Srinivasaraghavan: This is Vinod Srinivasaraghavan on for Kirk. Two questions for me. First, as you're kind of going -- undergoing that shift to a channel-first approach, can you give us a sense of how channel partner economics have evolved over time? How are you kind of balancing that with how you compensate your direct sales force?
Tianyi Jiang: That's a great question. Channel, we do embrace channel-first strategy, especially in the medium to small customer segments. That's roughly now 50% of our overall recurrent business. Even in enterprise, now we're picking up regional SIs as channel partners, and we're looking at some even bigger sized SIs as go-to-market. Within the channel, there's also the managed service providers as a massive uplift for us, highly sticky segment as intermediary to get into SMB. We do have a comp neutral philosophy. Our sales orgs are encouraged and embrace our channel as a force multiplier.
Overall, the economics of it continue to be fantastic because as we always cited, when we went public in July 2021, our cost of sales and marketing is 41% of our revenue. Latest quarter, it's just covered around 31%. All of that improvement, we credit majority of that is to our channel efficiency, and we'll continue to drive that channel efficiency because channels will allow us to scale. Importantly, we give much of the simpler service workloads the data migrations and those type of services to the channel. That would then generate service opportunities for the channel.
In the MSP segment, we have our large channel partners citing that for every dollar that they spend on our software, they generate $5 of service opportunities for them to better help their customers. That's the incentive really for the channel is to drive additional revenue growth in terms of service revenue for our channel partners. Overall, the economic model is a nice flywheel. It's growing in all regions. We now see really nice uptick in LATAM. Of course, also in India and in Middle East, we're doing super well. All of that is very much channel-first, channel-led strategy.
Vinod Srinivasaraghavan: Then just one last one for me. As you move to that hybrid seat and kind of outcome consumption-based pricing model, how do you expect that will impact NRR and kind of revenue predictability over the next like 1 to 2 years? Do you expect you have to change your guidance philosophy, maybe widen it over time as a result of that or no?
Tianyi Jiang: We don't think so. The outcome-based services, it's really to do the AI modernization, help our customers to really be able to first get their data estate housing order and then help them implement a lot of these AI modernization initiatives. That's going super well. That's our way to stay close to the customer. We always have a portion of our business now roughly about 12% that's really focused on this top-tier enterprise customers, public sector in terms of that service capabilities and delivery. That has always been our IP generation engine. Today, it's our engine to stay very close to the customer to see where the market is going. The market is highly disruptive. We all know, right?
In reality, no one really know what does the market look like 2 years, 3 years out. It's super important for product companies like us that really have a global footprint to have in every region that we operate in an advanced service capability. Now it's really outcome as a service delivery model to provide that premium service capabilities to stick close to the AI initiatives. That's how we continue to stay very agile and stay in the leading edge of the tech disruption. That doesn't actually impact -- it's only a leading edge, right? The overall 88% of the business is still very much a cloud business. It's a subscription business.
Again, as I mentioned earlier, the market makers, the hyperscalers, they determine the paradigm of licensing, whether it's seat count-based or consumption-based. We see that model to be going to be the state of things for the time to come. We don't see that being very different, at least not in the medium term.
Operator: The next question comes from Jeo Vandrick with Scotiabank.
William Vandrick: TJ, did I hear you say that nearly half the pipeline is coming from the control suite today? Just wanted to clarify that's right since I think that's about 1/4 of the business as of 4Q.
Tianyi Jiang: That is correct. Last quarter, actually, well over 1/4 of new closed deals are control. Now 50% of the pipeline are created with Control. Governance of AI, governance of data, it's very, very much top of mind for customers.
William Vandrick: Then maybe one for Jim. Can you talk a little bit about the investments you're making in 2026? Is sales and marketing the main focus for incremental investments just to capture the large market opportunity? How are you measuring ROI there?
James Caci: Joe, yes, I think you're right, you're spot on. You can even see it in Q1, the step-up in our marketing spend, definitely been a key focus, both sales and marketing. As T.J. mentioned, obviously, we're getting really good leverage from the channel, but that doesn't mean that we're not continuing to invest in our direct teams as well because we are. We're actually able to do both. We're making nice investments there, both in people, technology and really looking to scale that group. Our goal is not to execute just for 2026, but to get to this goal of 2029. We're making investments really this year that are going to propel the business well beyond '26.
We're doing that across the board and that some of the marketing initiatives that we're invested in as well, everything from the account-based programs that we have, all the way to some brand initiatives that we've taken on this year. Again, it's a big focus for us, again, focused on really delivering for 2029 and taking advantage of the market opportunity that you mentioned. We're doing that. In terms of ROI, obviously, some of these are more tangible than others, but we review these on a periodic basis to make sure that we're getting the expectations. Some of that translates to immediate results. Some of it is more other maybe softer metrics today that lead to those harder metrics later.
Again, we're on top of it. We're making those investments. We believe they're required today to hit those goals in the long term.
Operator: Next question comes from Stephen Bruno with Northland Capital Markets.
Stephen Bruno: Jim, I'm wondering if you could go through what you -- your expectations for free cash flow for '26 is and what the cadence and sizing of repurchases and your overall capital allocation plan for the year is?
James Caci: Yes. Thanks for the question. When we think about capital allocation, we've talked about this. We really think of it as 3 different pillars. Obviously, we want to invest in the business itself to make sure that our teams are well equipped, well staffed and can execute to the absolute maximum that they can. We want to first ensure that the business has the resources to do that. That's first and foremost. Second is we do want to look at opportunities for -- to supplement our internal growth with M&A activities. We have active discussions all year long with a number of target opportunities. M&A is a vital strategy for us. We've done small acquisitions in the past.
We've talked about potentially doing larger acquisitions. That fits into our capital allocation strategy, and we're constantly looking at those deals, and making sure that we have proper capital allocated to be able to execute. Then the third is obviously the repurchases you mentioned. We've obviously, as we talked about earlier, stepped up our buying not only in Q4, but we continued that in Q1 and the beginning of Q2. Again, we have the ability, fortunately, with our strong balance sheet to be able to execute on a variety of these capital allocation strategies, not just one. That's been really good. We'll continue to do that.
I think when we think about how much we're going to do in terms of repurchases, I get this question a lot. I think that's something we're continuously evaluating, and it's in the context of the other 2 pillars that I mentioned. If an M&A opportunity comes along or if we're looking at something, we may dial back repurchases, we may accelerate. We kind of look at it as flexible and taking advantage of the opportunities that present themselves to us.
When we think about free cash flow, you noticed we obviously generated a lot of cash in Q1, and it's really very good, but there are a couple of factors that I just want to point out for our Q1 performance. It really comes down to 3 things. If you compare our generation this quarter to a year ago, pretty significant improvement and really dramatic. I think that's 3 factors. One, if you looked at our net income in Q1 of this year compared to last year, we've generated an extra $12 million of net income. The business is performing well. That's first and foremost.
Then second, if you think of Q1 of '25, we called out that we had some special onetime payments, really tax-related payments in Q1 of '25 of about $7 million. Again, we didn't have those same payments in '26. We see some nice benefit from that. Then the third thing I would call out is that in '26, we received some customer payments in Q1 that in prior years would have been received in Q4. That was probably about $6 million. Again, taken all together, the biggest factor is the performance of the business has accelerated. We feel really good about the cash flow generation.
When we think about the full-year, I think we're going to be in line with what we've done in the past, which is we're going to exceed our operating income in terms of cash flow generation. Right now, we're guiding to the low 90s in terms of non-GAAP operating income. I would expect us to be generating free cash flow north of $100 million for the year. Again, we don't specifically guide to it, but in terms of -- just in terms of a range and if you're thinking about modeling or anything else, I would say that's the area that I would be shooting.
Operator: This does conclude the question-and-answer session. I would like to turn the conference back over to TJ Jiang for any closing comments.
Tianyi Jiang: Thank you for joining us today. We're proud of our first quarter results and raised outlook for the year, which reflects the growing demand for secure, automated and AI-ready solutions. The increasing strategic importance of our platform and its enablement of AI-driven transformation for companies of all sizes and industries around the world ensures a durable competitive moat for AvePoint and only strengthens our conviction in the enormous market opportunity we see. We're excited for continued momentum in 2026 as we progress toward our $1 billion ARR target. Thank you again for joining us today, and we look forward to speaking with you more this quarter.
Operator: Thank you. The conference has now concluded. Thank you for attending today's presentation. You may now disconnect your lines.
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AvePoint (AVPT) Q1 2026 Earnings Transcript was originally published by The Motley Fool