Docebo Inc. ($DCBO)

All right. Good afternoon, everybody, and thanks for joining us here at Docebo Inspire in Miami. Great kick off this morning with a nice release. I trust you've all seen the information by now. A couple of notes are out there circulating. I've got an awesome presentation for you here today. Our speakers include Alessio Artuffo, our CEO; Scott Peacock, our VP of Product and Brandon Farber, our CFO. So before we dig in, let me remind you that during the course of the presentation, we will be making some forward-looking statements. Please refer to the safe harbor statement here on the slide deck in any of the other materials that you might go to as part of your research for notes that follow. Quick agenda. Unless you will kick it off, we'll do some product demo work with Scott, hit a financial review with Brandon, and then we'll go into the Q&A. As part of the Q&A, my colleague, Jason and I will come to you as you get pointed by Alessio and Brandon for a question. We ask that you hold it to a single question. Let it work around the loop and then we'll take second round questions. We will be available afterwards for additional questions once the session officially ramps. If you have something further you'd like to check out. So with that, I'd like to bring Alessio up to the front, and we can kick off. Alessio?

Right. Hello, everyone, and thank you for being here. Thank you to those that flew in from far away. I know some of you were on the red eye, so I appreciate you guys making it here. For those of you that have been in the keynote, there will be some concepts or info that will overlap, but the material is slightly different. And for those who haven't been, I think, particularly during this session with Scott, you'll get to see some of the concepts that we're going to be talking applied in real live demo, but let's get us started. First of all, a little bit of background as far as where we stand in the state. Every 15 years or so, enterprise -- and every time, the same companies win. In the phase of the on-prem era, early 2000s. Many of you remember those days. It was all about Oracle. It was all about SAP. They owned the workflow. That SaaS. Salesforce owned CRM and the sales and marketing workflow. Workday owned HR and the payroll workflows. ServiceNow owns the IT business. Those companies that just freed up an interface really never broke out. thing. All right. Now we are in the agentic era. The narrative is that we were hearing is that SaaS is dead. I think that's lazy. What's affected is SaaS that's built on shallow data and commoditized workflows. What's thriving are companies like Docebo that own the system of record and run the work on it. Docebo this point sits on two decades of learning data, compliance records, learning histories, customers' certification history. What's important to underscore is that none of this data can be fabricated. So just to recap, we own the data, we run the workflow, and now we're shipping the agents of it all. Now let's dive deeper into what we're building, what we've built, what we're shipping. What I said earlier is that today, Docebo is shrink at an unprecedented pace relative to its most recent history. I did bring up a stat relative to our growth in usage of Docebo AI, which we've seen go up 300x over the past few months. And that's just the beginning because the future that we are headed towards and the things that we've announced today make us ecstatic about where we're going. So let me talk to you about AgentHub, MCP in the context of Docebo. -- and enterprise knowledge. I'm going to start with Agent Hub. These are proprietary agents that reason, decide and act on our skills graph, on evaluation signals and that use our enterprise knowledge, which captures the wide net of company knowledge that exists in an organization. These agents build courses. The triage compliance. They nudge learners. They run the work that the L&D teams used to do manually. They may do that independently or they may do that with humans in the loop. And eventually, this is my prediction and something that we're preparing ourselves to, they will work with other agents coming from other platforms. The second thing that I want to talk to you about, even though I go to the next side of the slide, is enterprise knowledge. I'm going to have more on this topic in the material later on. But for now, simply put, to give you context, we have effectively connected 20-plus enterprise-grade systems that live in most enterprises so that our customers can get to that knowledge where it lives, whether it's SharePoint, whether it's Confluence, whether it's notion, whether it's Google Driver or Slack or Microsoft Teams, whether it's different CRMs or HRIS. The point here that I need everybody to understand is Docebo is no longer just a course catalog. We make knowledge available so it can feed real capability building. And on MCP server, I had a couple of conversations with some of you earlier in the all asking about it, whether this is going to make us stronger or more commoditized. The fact that we go natively into cloud, ChatGPT, Copilot, when your employees, when the employees of our customers ask a question about training, skills or certification in one of these environments, the answer comes from Docebo. What it means is that every AI assistant, okay, becomes a distribution channel for us. And when a learner interacts with our data, that becomes an outcome. And the more the learners engage with our data, the better it is. When you think about the combination of AgentHub, MCP, enterprise knowledge in the context of the LMS combined with skills, this is a unique proposition that nobody in the market right now can replicate. Not Sara not Workday, not Cornerstone. This combination that I'm presenting is unique. The market wanted us to pick a lane. We built the lane. Look at this image. I think what I just said will become more clear for you all in this animation, there is not any more animation because it went fast. So look at the left side. The legacy LMSs leave there. Nothing wrong with it. Primarily, they check a compliance box. On the skills side, you have the skills intelligence platforms. Great to manage signals. -- but no way to act on gaps. So without a learning engine to close the loop, if you know that somebody has a gap in a given capability and you don't close that loop and you don't connect it to any knowledge or learning source, there still is a gap. And on the right side, you have the knowledge platforms, the Wikis, the Copilots. They are helpful for just-in-time knowledge retrieval, but disconnected from, number one, what people need to learn; and number two, from any recorded and auditable validation. because the fact that you do a search and find that you looked for a policy using a tool like Gan is not recorded anywhere. That's not auditable. It's not a datapoint. Docebo closes the loop by sitting in the middle of this by capturing the opportunity that exists to combine knowledge, learning and skill in one closed loop. That is the magic sauce. And we haven't made this up, by the way. This is what our customers have been asking for. It's just incredibly hard to build. AI without data is a demo. Well, let me tell you this. Docebo is not a demo. Here's what we own, and I know this is an important topic for the models and for the understanding of Docebo's position in the current AI market. Let's talk about compliance records. These are legally required and very scrutinized in pharma, in banking, in insurance, in manufacturing, in aviation. They are auditable. They are tied to a specific person and a specific date. And the thing is an LLM cannot hallucinate a record like this. It must come from a system of record. And that system of record that is us. Skills graph. Through -- thanks to the investment in 365, now we hold the canonical map of who has what skill. At what level proficiency? Across the entire workforce of the company. So every agent that touches, learning, talent or workforce planning needs this data to be valuable. If you know who is at what level, how do you provide training that is coherent with it? And we control that data. We control that data that is made available via API in the way we decide. Earnings history, 100 million learners are part of Docebo ecosystem, 100 million learners. And this is the training material that makes personalization actually work. You can't synthetize it and you simply earn it over time. And then to the external training data. This is the core business of the companies, the data about the customers, who completed which certification right? This is sitting really at the intersection of compliance, revenue, customer success. It's really invaluable data for any company. And just for reference, nearly 50% of our ARR is with companies that use Docebo for internal and external training. In agentic world, it's very clear. The companies that are being squeezed are the ones with no data or light data and a pretty UI. And we're the exact opposite of that. But we have pre-UI. One more thing before I pass the baton to Scott and the team. I get this question a lot. And I think it's going to be relevant to understand better how we think about knowledge in the context of the recent announcement that we've made today. The question is, what is the difference between knowledge retrieval and what you call workforce readiness? I think it's a very valid question, and I'd like to handle it head on. It's -- in simple terms, knowledge is not learning. Retrieval of information is not capability. There's tools like a question asking Claude or a question asking Lan, you certainly find an answer. Now that we are having access to our enterprise knowledge in Docebo, you can find the answers that come from different sources across the company. And we make sure as a learning platform that you need to come back and ask it again. That's the difference between a knowledge system and a workforce readiness system Cloud can certainly surface on the compliance side, a policy document assuming that it's connected to some system. But Docebo differently can prove that the employee Mike, [ Marty ] was trained on it. On what date for which regulation with the auditor ready record available for the regulated industries. That's the ball game. You can swap a search tool tomorrow. Nothing changes. I know it because we're doing it at Docebo now. But you cannot swap the compliance system of record. And then scope, I think this is an important part to understand as well. Scope in tenders as in audiences. A [ tool ] -- fully like Gleen or a tool like Claude used in any companies for your employees. Docebo, we designed it to address audiences that are both our employees, but our customers, our partners, our franchisees, the distributors of our customers. And that is revenue generating learning, not internal productivity only. I want to -- the other one is tied to revenue, to risk and to retention. The value is profoundly different. Hopefully, that addresses upfront some of the questions that I know you will have on this topic. But I'm looking forward to the Q&A. I hope this is helpful. And I also know that the most exciting part is yet to come because Scott is going to give a little bit of a deep dive preview of what he showed today for those that missed it and for those that didn't, by the end of today, you'll learn to the Docebo yourself. Scott, on to you. Thank you.

Well, let's hope I don't need both of these mics, so I'll turn this off for now. And I guess before I dive into my kind of core of the presentation, I think it's worth highlighting how we structure this and how we think about the different components of the solution that Alessio was just talking about is, when we think about the workforce readiness platform and how we've structured it right now, I want to highlight that learn obviously remains at the core. It is the majority of our SKUs and of course, the majority of the revenue, but we're building around it as well, and everything is going to be integrated, right? So although 365 was months ago, a separate platform, we already have organizations that are using both systems integrated and passing data back and forth. So I can show you a little bit more about what that looks like in practice. And yes, so we'll get right into my kind of first component. Before we do that, for those of you who attended the keynote session earlier today, you noticed that it's not just the story of agents, it's a story of us deepening our platform and improving the core experience that all of our customers experience on a daily basis. And for those of us who were in the room, I thought it was pretty telling that some of the most simple or basic [ concepts ] net [ entertainer ] in a than at 1 point I said you could now cancel a certain type of ILT session, and I literally got a standing ovation. So I think it's important to keep our eyes on the future and on what we're building and all the innovation that we're bringing to the table. But we must remember the people that we're really serving and the challenges they face every day and the hours and hours and hours that we can save and how happy we can make them with some of these core improvements. One of which is Docebo Companion. The reason I call this a core improvement is not because it's not innovative, but it's because we want to get it in the hands of every single one of our customers. This is an answer to the customers who didn't have the ability to leverage a massive IT team to build a complete headless experience. It's something we're hearing a lot more about this idea of embedding all of the information and doing direct API integration. So you don't have to touch an interface. For our customers who wanted companion, all for them was to say, "Hey, I'm in Salesforce and my folks need training in Salesforce. My folks need training in our intranet. My folks need training wherever they happen to be. And I don't have a 30-person IT team to build an integration." So we'll turn on companion. And companion is Docebo's capability of servicing the right training for the right person no matter where they are on the web and no matter how they access their work. So this knows who I am, it knows what I'm trying to accomplish and it knows where I am. And Alassio rightly pointed out that data is at the core of everything we're doing. The more we rely on AI, to answer our questions, the more we use AI in a day today basis, the more important it is that data is relevant to me. Companion has another reason that we're putting it in the hands of all of our customers. It allows us to understand how those learners are now [ getting ] the web, interacting with their systems, and it allows us to build signals we can say, "Hey, 40% of your workforce watched a YouTube video on MCP servers recently. You should probably create some training on that. And in fact, we have an agent who saw that and has already made a draft for you. This is the kind of stuff we're doing by giving more access to more of our customers for things like companion. Another really core system of the improvements that we're making recently is our enrollments rules engine. And again, this is one of those standards parts of the platform that people are so excited to see coming out. And this allows our enterprise organizations to scale massive, massive executions of enrollment in the hundreds of millions. When you have a system like ours that is so connected to all of the infrastructure, all of the data, all of the compliance records. Making a single change can cause a cascade that affects 100 million different components of [ the ] we needed a way to do that for the largest organizations in the world. And so now we have. And I wanted to highlight another core component that we're building upon. For those of you who are tracking AI virtual coach is how we've historically referenced this, but as we've expanded our capabilities, AI role play, we've changed the NIM to reflect what you're really doing. And fundamentally, it allows people to create [ custom ] rubrics where they can define exactly what good looks like and execute against it. So content marketplace, last one before actual [ into ] more physical demos. I know we want to see the products. But I wanted to highlight that the content marketplace is getting upgraded, which allows us to add tons of new partners into that marketplace and give access to our customers very, very soon. So we talked a lot about the future of workforce readiness. We were sitting on a stage about this. And the agentic system that we're trying to -- that we're building here, I want to know some of the components that flow into this and 365 is a good place to start. So I'll jump over to my 365 environment. It's embedded [ in ] Docebo. I'm going to start from the learner's perspective. So we're going to start from the learner's perspective. And Ashley Anderson here, who is in the system, we are already hooked up to all of the sources of truth that feed the information into the platform. So you can imagine pulling in her LinkedIn information. She's uploaded her CV. We're hooked up to the talent management system that the company used to hire her in the first place, and of course, we're hooking up to SAP, Oracle and Workday wherever her performance records exist. This is step one of gathering all of the information for all of the learners in our system. Based on all of this, we can understand the type of job she has, the skills that she's building and fundamentally how her job description lines up with the skills that she actually has. So she's able to say, "Hey, look, I'm a software development engineer. What's the capacity that my career could take from here? And ultimately, where are my skills in Java or T++ compared to where they need to be. And this is powerful for an individual because they can build their career and plan what they're going to do next. But more importantly, it's powerful for the administrators of our system because an admin doesn't necessarily care about that individual [ learning ] or the individual who's kind of building their career. It's important. Don't get me wrong. But fundamentally, we are building a huge database of all of the roles that exist across this organization, how they relate to each other, the skills that exist within each of these roles, the expected skill level of each of the people that hold these roles in systems engineering, digital business analysis, software engineering. And we can [ take ] -- all right. So we can take a look based on all of the inflation we know about this entire audience to understand globally across all of my software development engineers. There are their skills compared to they need to be. C++ is right on the mark. The team is a little bit lacking in the debugging skill that might explain some of the regressions and Java is another core skill that we need to grow on. I also want to highlight the ability for us to now do benchmarking across this kind of job. And so we can do this from an internal perspective and see who's declaring the skills at what ratio according to the role. But importantly, we can take a look at benchmarks from outside the system. So we can take a look at all the different organizations that are hiring software engineers right now and how that has changed over time and how people are being found and brought into the system. So these are some of the smaller components that overall drive all of the data that we now have access to as we get into what we are calling the evidence engine. And the evidence engine is our ability to say, we understand the distinction between a signal, saying this person is interested in this topic, we should build courses, we should have an agent take an action, versus, as Alessio was saying, evidence and validation, our true understanding that someone has done the actions that we classify as that person being an expert in that particular skill. And of course, all of our customers are different. We serve a huge range of industries, organization sizes and complexities of organization. And so what one company says is the prime example of a manager validation, my boss says, I'm an expert at presenting, maybe so. But if I did a proctored certification for an AWS practitioner exam, that's the gold standard, and I'm considered an expert. We gather all that information, and we can allow our customers to set up campaigns to close the gaps where we know that they exist. So people are getting used to vibe coding with Claude. We need to expand that. We need our team to be better and faster with it. So we can launch a skills campaign and see who is actually successful. So in this case, Maria Chen, [ James ] Pia, the individuals benefit because they build a body of evidence that proves their capacity that prove their skill and we are able to say, okay, let's feed all of this information into the agents that this person has access to. When I first got ChatGPT, the reason that I moved from Gemini to ChatGPT was because they introduced memory. They introduced an understanding of who I was, and I said, refer to me is Captain Kirk and here's all the information of me. Most people in configuring their AI that they use on a daily basis. You're using an MD filing Claude or a couple of paragraphs to explain who you are. We have thousands of data points to understand who someone is. We have every time they watch the YouTube video with companion on. We have every course they have completed in every score they've achieved. And so we can use all of that to make sure that when our AI answers their questions, it does so with them in mind and their best delivery system in mind as well. Okay. So let's go back to our slides here for a second. And I want to also talk about AgentHub because I think it's obviously deeply relevant to the way that we're moving forward here, connecting to this tech stack and knowing the people a slide all the way over just for a single slide. But I wanted to highlight again that the way that we're being able to build these agents and the way that our system is going to connect to other organizations, it's really dependent on the company that we're working with, but we are going to be creating agents that understand exactly how our system works. And you've heard about the MCP server from our perspective, where we expose certain information that we want the web to have access to. But AgentHub also allows us to act as an MCP client, where we're reaching into other MCP servers gathering information and taking all of that data that we have access to and making forces delivering training and setting up learning plans for people at scale. Our customers are some of the only ones in the world that can get 20,000 learners for each of their own individual learning plan that respects the way they like to learn, the kind of job they have and exactly where they are in their career. Okay. And I have one last piece. That was the last piece. I want to hand it over to Mr. Farber. Thanks for coming up. You might want to hold on to this just in case.

Good job. So roughly 3.5 years ago at Inspire Nashville, we posted our first TAM over $25 billion. We're coming here today, updating that to $40 billion. And that's driven by organic growth into the government space and inorganic expansion into skills intelligence. When we look at corporate learning, it's really split into two different pies. It's the internal audience, onboarding, compliance, talent development, sales enablement, and it's the external audience. It's customer academies, whether it's monetized, unmonetized. It's franchisee workers, it's partners. It's -- it's memberships, memberships and not-for-profits is they're looking for. And from a TAM perspective, slightly less than 40% is internal audience. Slightly more than 60% is external. Let me walk you through why the external opportunity is so large. I'm going to give you four examples of real Docebo customers how they use the Docebo platform. First two are nontraditional corporate entities. First one is a large sports organization in the U.S. They use Docebo to train their internal employees, referees, parents, everyone in [ new ] hockey, they have 1,000 internal employees, whereas they train 100,000 annual users on Docebo. Their external audience of 90x the size of their internal audience. Another nontraditional an independent regulatory body that monitors all of the brokers in the U.S. They have 7,000 employees, 7,500 employees and they're training 650,000 external audiences, 85x the size. Now let's go to some more traditional corporate entities, data bricks at Inspire, long-time customer of Docebo finding out their internal audience was a little bit harder. They're a private company. I ask Claude three different times, got three widely different answers, so they have anywhere between 5,000 to 25,000 employees. I know it's large. They trained 1.5 million users annually on Docebo. That's about 65x the size of their internal audience on the upper end. They also have one of the most successful unmonetized and monetize customer Academy on Docebo. A new customer we signed in Q1 and Fortune 100 company can't name the logo. So I'm going to say a global technology infrastructure company. They're using Docebo just for a partner use case, 100,000 users. More than 50% of the revenue is [ through ] partners. If you think about a manufacturing company, you have a company handling Part A, Part B, Part C. They have partners in over 90 different countries. They're using Docebo for the certification of their partners. Three different levels as you move up through training, you get better discounts. This is just one external use case. We don't have the internal, we don't have their customer academy, large expansion opportunity. This is why we're so excited about the growth in Corporate Learning. This is why we're so excited about the growth of the external opportunity and where Docebo plays really well is when we're doing hybrid use case combining the internal plus external. From a U.S. [ gov ] perspective, we updated the TAM to $3 billion. And that's really just revised data on the updated employee and contractor count. Multiplied times the average realized sale price, very simple TAM calculation. There's three reasons why we're just really excited about the government sector. Number one, we have the right partners from Deloitte to [ Terasoft ] even niche learning partners such as skills. Number two, we're seeing the pipeline. Three quarters in a row. We talked about in Q3. We talked about in Q4, in Q1, our pipeline continues to exceed expectations. We have the right pipeline now it's on us to execute. Third, we're really just leveraging the innovation we've been bringing to the Corporate Learning segment for the past 2 decades into the government sector and the government sector continues to be the least competitive market we play in. From a skills perspective, this is the first time we're showing TAM. Post acquisition of 365, and it's third-party validated sources on three different use cases, skills, intelligence, internal mobility and talent [ place ]. The best thing about 365 is that it's already an enterprise-grade tool. There's already large enterprises such as SNCF, Credit Agricole. These are companies with hundreds of thousands of employees, multiple different geographies using Docebo -- using 365. It is an enterprise-grade tool that's ready to sell now. And I'm pleased to say that 7 days after the acquisition in Q1, we cross-sold 365 to a Docebo customer. 71 days in and our acquisition thesis has already playing out. We're not only expanding our TAM. We're also expanding our GTM. And you may look at this slide and say, "Hey, Docebo, you've been talking about the enterprise space forever. You were in there in 2021." And my answer would be, you're right, but you're also wrong. In 2021, we had 8 -- roughly 8 head count in the enterprise space. That's a combination of account executives, account managers and [ answer ] of the team. Conveniently enough, every one of those sellers was previously mid-market or commercial sellers at Docebo. We treated the enterprise space like we treated mid-market and commercial. We had no different motion. We had no partner network. Zoom forward to today, we have 25 head count combination, account executives, managers, VPs, managers. We have a completely different motion. 50% of our closed ARR in the enterprise space touched a partner in Q1. We have a completely different partner network. From a skills perspective, we inherited a stand-alone selling team as part of 365. They're going to continue to sell 365 to any organization no matter what LMS they have. If they have SAP, if they have Workday, we're going to go on there and sell 365. Now there's been investor question over the past 4 years that we just haven't had a great response to. And that question is [indiscernible] Docebo, when is ARR going to stop decelerating? We're pleased to be here today to say 2026 is that year. We show the acceleration in Q1, I understand there's acquired ARR in there. But when we look out to Q4, no matter if you look at with acquired ARR or without, we're going to be accelerating ARR. We're seeing in the business. We're seeing the levers. We're seeing the expanded TAM. Everything is in place to accelerate ARR. Another thing is that when I compare Docebo today to Docebo about 12 months ago, we're significantly derisked. In Q1 of last year, we had AWS at 2.8% of our ARR, we had Dayforce over 9%. Today, that AWS use case is at 0 and Dayforce is slightly more than 3%. Our top 10 customers, excluding Dayforce, is less than 8% of our revenue. Our customer base is significantly diverse. In 2026, we just -- we simply have a larger TAM. We have a larger GTM motion and that gives us confidence that ARR is going to accelerate. If there's one number on this slide that I want you guys to take away, we've talked about enterprise, why we're growing the enterprise. And the one number that we've never shown is when we compare our NRR for customers who pay us [ $100,000 ] or more compared to [ 50,000 ] or less, there's a 9 percentage point difference in our ARR. That's even including AWS, Thompson routers in the past 2 years. If we exclude that, that number is even better. If we look at that on a 5-year basis, it's even better, but we had small numbers, so I didn't give us credit for the full 5 years. But naturally, as our business becomes more enterprise focused, you are going to see NRR move up. We're still early days in the enterprise space. We only have 524 logos paid us over $100,000. We're only 5% penetrated in the Fortune 1000. We still have a large room to grow in the enterprise and compound growth. From an EBITDA perspective, we've gone from 8% EBITDA in 2021 to slightly over 20% forecasted for 2026. This is really just a testament to the sustainability of our business model. We've now sacrificed our growth [ or ] to get here. It's been methodical. It's been deliberate. It's been a steppy increase in EBITDA every year. And we're not only disciplined from a spend perspective, but we're disciplined from a dilution perspective. This morning, I was doing some last-minute research, changes some slides, driving my friend, Mike crazy over here. And I was looking at some research from an analyst in this room. Thank you, Josh. His firm looks at roughly 80 different SaaS companies post all these different SaaS metrics and conveniently enough, [ is ] stock-based comp as a percentage of revenue. Sort of that data from largest to smallest and Docebo was at the bottom end of the 80 names. There wasn't a single name below Docebo. When we talk about best-in-class room stock-based comp, there is just not another company you could find at our scale. It just doesn't exist. We're not only doing that or decreasing our share count. 7.2 million shares decreased over this time period, $277 million returned to shareholders for via buybacks. And we're going to continue to buy back shares at these valuations. This is all news by now, 8 hours old. I'm not going to talk too much about it. But the thing I love the most about this being raised is that it's not because Dayforce revenues were higher than we expected. It's not because we magically acquired more ARR than we expected. It's not because FX benefited us. It actually per [ our ] guide by about $1 million. It's because our core business accelerate in Q1. On the conference call, if you asked Alessio and I, what's it going to take to being raised? What's it going to take to raise expectations, and we're very consistent, enterprise, enterprise, enterprise. And in Q1, our enterprise team delivered. Here's our target operating model, 10% to 15% of subscription revenue. We talked about the growth levers. It's really clear, external use case opportunity, growth in the enterprise, government, product expansion. From an R&D perspective, it's gone down 1% since our last target operating model, and that's really efficiency from AI over a period of time. While we're not seeing that in 2026 in 2026, we're right now. We're actually seeing costs really shift from head count to compute. So while we're getting more efficient, we actually need less heads, but that cost is just moving from one bucket to another. Over a period of time, we do expect compute to come down and some realized some savings in R&D, but done in 2026. G&A is unchanged. Our track record speaks for itself in G&A. We've come down from 2021, we are 27% of revenue in G&A. In 2025, we were 14%. If you just use the midpoint, we still got 4% of leverage just through G&A EBITDA without sacrificing our growth levers. Sales and marketing is actually the biggest change since our last target operating model. We previously had 28% to 32%. We're down to 26% to 28%. What are we seeing? We're seeing improved performance from a quarter perspective. And there's certain areas within sales and market, and that will certainly benefit from AI. We're talking about more of the rev ops sales enablement, the more kind of the groups that need to scale up with the quota carriers. And I'm just going to -- I leave you guys with a hypothetical but a very realistic scenario. If you take our 2026 revenue guide, and then you use the bottom end of our subscription revenue growth, 10% for the next 2 years. So '27, '28. From an expense perspective, in '28, let's assume we get to the top end of all these ranges at 80% gross margin. I'm not telling me that's roughly 24% EBITDA margins. We're talking about a business that's generating nearly $80 million of EBITDA in 2028. Go repeat that one more time. This is a business that will be generating nearly $80 million of EBITDA with best-in-class stock-based comp and a declining share count. On to Q&A.

Okay, if you would please just give your name and firm.

Matt VanVliet from Cantor. I guess when you talk about not only the growth in head count going into the enterprise, but maybe walk through some of the mechanics from an operational perspective that are changing. What things are you doing differently to attack the enterprise market, but that can still leverage down to the mid-market and commercial for more of a shared services approach?

So Brandon mentioned this in his talk track. I would say, operationally speaking, the changes that we've made to the enterprise engine are across a few dimensions. By the way, we also have here Mark also, our CRO, that is implementing a lot of the things I'm talking about. And Mark, feel free to jump in and take the mic if you want to add anything. Let's see if I know enough about the enterprise business, okay? Don't be shy. First, to me, it starts with the people. Brandon mentioned it earlier, we were running the enterprise playbook with folks that used to do commercial and mid-market sales. The first thing we did, we were intentional about upgrading our skills profile at all levels. Sellers managers, directors all the way up to VPs. The entire organization of enterprise sales has been [ read ] in order to get to where we are today. We brought on board people that were experienced enterprise leaders and sellers in the industry already. The majority of people that we brought on board had sold very large deals with the Cornerstone Workdays of the world, and they knew the enterprise game called. The second thing we did, and this is not a -- I would say, a short-term initiative, it's the work of being very intentional over the past couple of years. We built a very strong partner network to really be involved and be ahead in these accounts. When you want to entering Google and similar companies. It is undeniable the [ accentures ] of the world and the [ outs ] of the world had a head start because they live inside those companies. They run transformation projects. They run large consulting and RFPs for these companies. And so having established different degrees of partner program with these companies is something that, for sure, gave us -- is giving us a lot of return. The third thing I would mention is the way we also approach demand generation and the way we speak to the market. Our enterprise demand business has been invested in the way we go and approach the top of the funnel on the enterprise side is very different from how we did it in the past. So when you now look at these three levers alone, demand partnering. So surrounding the accounts with the right partners and the upgraded execution in people. Those are three key ingredients that come to mind. Mark, Brendan, Scott, anything sorry, actually, no, very important for [ Televera ]. We were very honest with ourselves about what we have to do in the product to be truly respected from enterprise organizations. We identified over the past 2 years, areas of the product that were not acceptable in an enterprise environment, that maybe we're not sexy, right? They were not AI forward, but it needed to be done satisfy the likes of really large banks really large insurance companies, really large health care organizations that are running businesses that are so sensitive to regulatory environments where you can't mess up and so we put a lot of work into that as well. Thank you.

I'll comment on one thing as well. It's almost like we have two directions of innovation, right? There's innovation in the direction of genic and forward-facing and in the news and all this kind of stuff. And then there's the things that the -- there's a reason that the legacy providers still exist and are still huge. And so we're kind of growing in two directions, where we're closing some of these boring gaps that are absolutely mission critical at the same time that we're growing in the other direction. So it's a good point. But I see them as both innovative just in opposite directions.

Ken Wong from Oppenheimer. I don't want to steal your thunder from earnings, but I think one of the big headlines today, you guys preannounced more positively than expected. In fact, you guys raised kind of above the beat. And Brandon, you touched on this a little bit, but would love Alessio, you and Brandon, maybe the tag team. Kind of what else under the covers in the quarter were better beyond enterprise? Was it new? Was it the NRR side finally picking up. And then with the macro backdrop kind of the way it is, again, surprised that you guys were able to kind of raise by more than the beat. What are you seeing in the business that gives you the confidence to go ahead and lift those numbers?

That's a great question. Certainly, when we looked at our guide for 2026, we already embedded assumptions that mid-market was going to continue to improve. And they already had three quarters of great quarters in a row, and we just -- we took that. So in Q1, mid-market had a good quarter, but it wasn't the reason we raised our guidance. It was really the enterprise motion and within enterprise, we actually had $2 million plus expansions. One was with what I mentioned, the regulatory body for brokers. We initially had the internal use case, one in Q4. We did such a great job during the presell motion and during the implementation that we sell [ the ] external use case opportunity. And at that point in time, when we're working the internal use case, we're actually working two different use cases with two different departments at the same time. The second expansion was in the health care space, where we owned a smaller subsidiary of that company, and we ended up getting the top dog, the top entity. So obviously, when we talk about our guidance, we initially put out, we assumed no $1 million plus new wins or expansions we had two this quarter. And we not only saw a great Q1. We saw a great Q1 pipeline performance in the enterprises. So we're not only taking Q1 and raising guide just for the Q1 beat or raising guidance throughout the year due to improved visibility in the enterprise space.

And as far as the latter part of the question, Ken. I'd say there are a few things that make us realistically optimistic. The first one is the realization that we have matured a leadership team across the organization that is ready ramped up understands the market and has brought in the right leaders below them and it's creating the osmotic conditions for performance to persist. The second one is more backed in the numbers. Brandon stole my thunder a bit, but I will be more emphatic. We continue to see sustained pipeline performance, not only in the enterprise space, but also in -- the segments where we've historically been present, like mid-market, our bread and butter where we continue to perform at very strong levels. But we've been working to improve the performance of our international business as well, that in the past couple of years, has been choppy, to say the least. And we are seeing very strong momentum even there, connects back to the comment I made about our leadership. And finally, I think the momentum on top of the signals of pipeline, that exists in product, our ability to ship at a very accelerated pace. Our ability to be here announcing something like 20-plus meaningful evolutions of our product between core and highly innovative AI forward. There is a lot of material to go back to our existing customers and build these account plans and expand upon them. Fifth, impeditive landscape. We are seeing a significant influx in here had to add wins with the usual suspects that have a large market share. You know the companies that I'm referring to. And we, at Docebo, have had always very clear ideas about how we plan to grow the business, doing things that benefit our customers. One of those things is not getting distracted by, for example, acquiring competing assets. We could have done that a number of times. We have chosen not to do it. Why? Because we believe that creating that magic closed loop that I showed earlier where the convergence of learning, knowledge and skills, get together in a unique solution, that's what is going to make us win the long game. We're seeing that link out right now. The companies that we compete with are either in the Learning segment that we saw or in the skill segment we saw and we win on share capability. And I'm referring even to the more modern ones that have been acquired by larger assets like Workday. We're very excited. Across all fronts, the signals are green and so we're bullish.

Ryan MacDonald with Needham. As we think about the 10% to 15% sort of target model growth rate over the next few years here, how should we think about what the products are that are driving those growth rates? Because it was interesting to see in the keynote today of it feels like the market is sort of in two different spots. Customers are very excited about blocking and tackling core improvements and maybe more skeptical or inquisitive about brand-new agent workflows and ways to use the platform. And so where do you think that growth is driven from core versus some of the new? And how do you bridge the base of customers to go from core to some of the new function?

When we go into an enterprise, Ryan, everyone, we -- like Brandon described this very well earlier, we have a number of use cases that we address, whether they are one of the few internal use cases or one of the few external use cases. And all these use cases relate to different capabilities and products and pains, frankly, that the customers have. Today, the biggest contributor to our ARR without a share of doubt is our core LMS platform. the ships with roughly, if I recall correctly, there's about 20 modules or so that are attached to it. That supposedly is going to be to continue to be our major driver of growth for the time being. The acquisition of -- but the acquisition of the Skills intelligence platform gives us an opportunity to differentiate ourselves and compete in deals where despite having such a rich platform feature, we would have not been able to play. There is a very large organization today at Inspire. It is a prospect, and it's a big embedment group, which I will not name for privacy purposes. And when we start talking to them, everybody in this room would know their brand name. They were very interested in our capabilities. But when they identified the fact that we were light on the skills element, I would say, we were about to lose that race. We were about to being dismissed. And we're talking about the potential of very significant deal, certainly top 20 ARR in the company. And so more than top contributors to growth, the way we think about it is how do we create the right product mix to serve these organizations that are going to have multiple use cases and needs that are very articulated. And so if the LMS is saying a $2 million deal, $1.6 million, but there's $200,000 of skills, not having the possibility to position skills would make you lose the possibility to win the $1.6 million of LMS. So that's more how we think about it. It's less about having a product that wins the race and more about adding a platform that gets together and really positions as uniquely against anybody in the competition in the target market because it's also a matter of choices. While choosing to do all of the above, we're also choosing and telling ourselves that organizations that are looking to spend $10,000, $20,000, $30,000 over time are not going to be our ideal customer profile anymore because we've designed the product, the company, the strategy, the PS, the partners around a different type of organization. And that's why we have great partners that take care of them.

I'll just add quickly. From an AI perspective with prospects they're coming to Docebo, and they're asking what we're doing with AI without really knowing what they want to do. They want to know we're thinking about MCP. They want to know it's coming. When we asked them, how are you planning on using Docebo through MCP, they don't actually know the answer. They just want to make sure we're thinking about it -- they want to make sure we're building agents, even though they don't really know how to use it yet. They want to be a platform that's thinking about the new generation. And we've been able to demo, we've been able to show, and that's going to result in more LMS revenues. But we're not just thinking about LMS revenues. We're thinking about the whole product suite.

I'll wrap it up because it's a broader question. Yes, I'll go ask them. The interesting thing to think about is the same way that our -- the organizations that we work with are typically mixed in between internal, external, hybrid the customers that are happy with us and stickiest are using us for the most use cases. Similarly, we want to give our customers the opportunity to grow into their own ambitions. Like it's easy to think of ourselves as we're innovating, we're growing. But like -- they want to innovate and grow too. And some of them can't innovate and grow in the direction of AI right now. So I guess what they're doing. They're becoming skills-based organizations, right? They're innovating and growing at a human level. It's almost like a dichotomy. Some of them say, "I'm going AI, some of them say, invest in our people. And like we want to be there in the situation where an organization says, no, we are really the all-in company. We're going to do all of this. And so yes, we have that offering. But it is important to note that we'll sell -- we'll happily sell our product to an organization doing compliance, to an organization that's doing skills and learning and of course, to one that's doing an AI forward agentic future. So it's a bit of -- we want to make sure that we have what's necessary on the table, but also respect our own customers' goals and ambitions because they sometimes go in skills versus AI in different directions.

Erin Kyle, CIBC. Just on the guidance. How can we think about some of the other factors that are impacting the guide this year? So if I think about 365 talents, Brandon, you talked about the fact that you cross-sold the solution about 71 days into the quarter. So maybe you can speak to is it -- if you can speak to whether the acquisition has been performing in line with your original expectations and kind of the ARR that you expected to be added when you acquired it back in January? And then maybe on the flip side of that as well for Dayforce? You noted in the press release this morning, you're expecting the ARR percentage to be around 3%, 3.2%, I think, was the exact number. And I think in past quarters, we had talked about Dayforce maybe being anywhere between 3% to 4.5% by the end of 2026. So it seems like it's now kind of below those old expectations. So maybe you can speak to where you expect it to be at the end of 2026. And if it does churn faster than expected, what the base business needs to look like to continue to offset that.

Yes. From a 365 talent, we continue to expect the revenues to be exactly as we previously announced when we acquired the acquisition. So it's roughly $9 million of revenues. We acquired this asset with the expectation to sell it right away -- [ from ] a Dayforce perspective, listen, ARR is turning slightly faster than we expected this quarter. But as I mentioned previously, the actual revenue amount we're still expected to come roughly in that range that I previously disclosed. If you think about it, the only thing that's changed is that the revenue base is higher. So the amount of revenue contribution as a percentage will be slightly lower, but the actual absolute dollar number is the exact same as we previously expected. So really, the only thing that is changing in my guide is the core business improvement.

Kevin Krishnaratne at Scotia Bank. Just as you're moving from an LMS into a broader learning management platform, learning platform, are you seeing the point of contact in the company -- customers that you're talking to changing it might have been an L&D admitted before and now it's maybe moving into the CEO role, maybe for Alessio.

The -- not just as a byproduct of our product innovation or product evolution and product growth, but also as a byproduct of our growth in the enterprise segment. Even without the most recent announced capabilities when we sell into companies with 50,000, 60,000, 70,000 employees. We don't have any more just learning as a buyer persona, the CIO office is very involved. The compliance office is very involved. And this becomes more true and they take more of a driving [ seat ], we've seen in certain industries versus others. I would say that, for instance, in highly regulated industries, take in banking, Finserve and health care as examples. The learning and development teams are effectively our functional champions. But then we have other buyers from the IT and risk teams that are really the ones where we have to do the selling and demonstrating. We have to demonstrate that we can adhere with their complex compliance requirements. Whatever those are, depending on the industry. Every industry has a different subset. We're learning a lot in that regard. And by the way, you can expect a Docebo over the next couple of years, that becomes increasingly more sophisticated it is very complex to navigate compliance-driven environments. And why is that? It's because the barrier of entrance in those industries is pretty high and it takes resources, which we have and time, which we've had. And so our win rate in things like pharma health care, life sciences, financial services is improving significantly. There is a good case to be made about us dialing down on these regulated industries, where we have increased right to win.

It's Gavin from ATB Cormark. Just given the pace of innovation in some of the stores in a intimidated by the change management. Maybe you can just talk about customer success and how that's going to evolve to help them through that journey and then also kind of uncover the upsell motion.

Look, I think my friend, Mark is getting board. He's is a chatty one, and he actually has been leading our efforts in customer success for quite a bit of time. One comment, though, before passing the microphone and getting going, I want to address the topic of customers being -- I don't want to -- I don't think you said scared, but intimidated, I think that's the word you used about all the pace of innovation. One of the things that we realize as we bring this innovation to the table, there's two things. If you were in the keynote, we spoke about the story of Mary. And Mary, this fictitious L&D leader is really actually a representation of and an analysis that we ran with AI in the company about a lot of the things that we get from gone calls, okay? We analyze patterns and the pattern is Mary is under staff. And the pattern is Mary's overwhelmed. The pattern is Mary has got to do a lot of chair to balance between strategy and getting stuff done every day. As a result, she struggles being strategic because she's brought down a lot to getting things done. Oh my gosh, this new cohort is starting. We need to build the course and need to oversee the course even if somebody is building it. So our average buyer struggles to act strategically and some of the work that we presented today takes away the annual work that they're used to doing. So they have an inkling young about our recent innovation. On one end, they're really excited about it. On the other end, like Okay. I actually spend 50% of my time creating courses and I just saw an agent creating an awesome course outline that would usually take me 30 minutes to build. So that gives them a pause and that intermediate feeling that you may have seen is also the result of that. Is the realization that the technology AI innovation is brought forward in the industry, and we're here making it available to them. And now they need to figure out what to do with it. It is a change management. It is a cultural progress in the industry that, frankly, it's unprecedented. They haven't seen anything like this before. On the customer success front, we're doing amazing things. particularly because we believe that one of the keys to success is not only becoming stronger in product and selling more and having better pipeline, but increasing stickiness. Increasing stickiness is through product strategy, but also through customer success. Mark, is that okay to pass the mic? Let's do it.

Thank you I was very lucky in my career to work for customer success platform, whose job it was, was to help retain and expand customers and in that time, about 18 months, I was able to meet with some of the best post-sales mines on the planet on a regular basis and glean from them what I determined were, what is make post sales process, what makes great customer success? And there's three things that I found are required that we are becoming best of breed in. One of them is focus. We removed the commercial conversation from our CSM, so they can focus on creating proactive value for our customers and rather than haggling over a $10,000 difference in pricing on a renewal, which we have our commercial reps do that. We have them beat our customers over the head with how we can help create more value and solve the business problems they have. So our focus is the first. The second is data. We now have very -- through my partnership with Scott and Ricardo, we now have a slice of data that allows us to understand exactly how our customers are using the platform so that we can create those proactive warning signals of churnable behavior so that we can cut them off before they get deeply rooted. And then the last is process. This was surprising to me. But in my first 50 days at my previous company, I talked to 90 customers that were all CS professionals, and I asked them what methodology do you use for CS? Do you know what they all said? There is no CS methodology. Well, that means that with the lack of process, reps don't know what to do. So we are instituting a best-in-class process of how do you create a repeatable, predictable way to drive value for our customers so that they don't think about churning. And so that creates like a stage-based process that we can run multiple cycles on and measure how fast are we driving additional value for our customers. So those are three of the foundational changes that we're making in customer success that should really help us with retention and even maybe more importantly, expansion because by default, expansion means that they're happy enough to renew.

John Shao from TD Cowen. Alessio, you mentioned in the beginning of the presentation that there's going to be a future where your AI agent is going to be working with agents from other vendors. So maybe from a customer's perspective, could you help us understand what's going to happen to your customer given multiple agents from various vendors? Do you see a future of consolidation? And do you see Docebo consolidating?

You're right. I said that. And that's the result of what we're seeing in the market. There is a definite case for agents involved by other agents and agent interoperability platforms. With that said, I think we are early in that game. And I think, first, we need to ensure that we take step one. Step one is enabling our customers, the people across our customers, the humans to use these agents and make the best of it before we make the agents available to other agents. Now, the way we are exposing our agents and our MCP leads itself to enabling other platforms to connecting with Docebo. Ricardo demo it earlier today. If there is an agent that invokes the Docebo of the MCP, one of the things that we will be able to control because we control the data is what do we want other agents to do with our agents? That is something that we haven't established yet. But certainly, you can expect a world in which we make our data matter, right, our skills graph of our -- of the employees of our customers, the learning history, all the data primitives that are really valuable are going to be part of a value program. Not everybody can just access without some form of consumption model or outcome model in favor of Docebo. That is pretty simple to envision the technology of implication of agents to agents that were a little early.

Josh Baer with Morgan Stanley. Alessio, a couple of questions because you mentioned you brought up efficiency and content creation. I wanted to ask one on broader customer ROI. In the past, you've measured that through sales enablement, some revenue metrics or external training opportunity. Customers are always focused on engagement, of course, completion. How does AI and skilling change the way that customers are thinking about ROI? Like what are you talking to in sales processes? What metrics are you tracking along the way? And ultimately, like how do you frame Docebo's ROI today?

I think one of the biggest dilemmas in the learning in LMS industry has always been the truthful ROI calculators, particularly true on the internal use case side. Easier to calculate ROI, the closer you get to the revenue stream. So you're right in mentioning sales enablement, customer education, anything that touches pro serve or support because they are very close to an outcome and that outcome as a dollar attached in terms of revenue or in terms of cost. When it comes to internal learning that ROI is a lot more ambiguous and difficult to establish, particularly related to employee trading. Technical sales enablement is an internal use case, but it's a lot easier to quantify ROI based on the productivity that you gain with sellers, accelerating the ramp time, for instance, getting them to first deal, getting them to quota. Every enterprise seller has specific playbooks, the touch on value depending on the use case sell. And in Docebo, we have a practice which we actually call value engineering, called in the name of VE, where when you approach us, and we go through the discovery phase, i.e., we learn about your business. And we ask questions about what you want to solve. Then all that data is funneled through ROI calculator for the funding use case. And so when we go and issue a proposal to the organization, it doesn't ship with just the price. It usually aims to asking to the customer a question, why wouldn't you do it now? And what is the cost of not doing this right now? So instead of just standing in order form, we send a question, which is based on our data and based on the fact that you told us, this should be an operator. And the customers that are the most successful with it are the ones that use that to form the internal use case for purchasing it. That is when we are able to influence the way the decision is actually framed internally using our own data because not only you're saving your point of contact, a bunch of research work, you're actually influencing the way they go to talk about the problem they're going to solve. We've seen this play out pretty nicely. I don't know if Brandon and Scott have anything more to add.

Yes, I'll comment on this as well. I helped build the initial value engineering capabilities a couple of years ago when we really started doubling down on this. And what's interesting to see is that as we move into more of the skill side of things, the situations in which we can save our customers money and prevent risk and do these kind of things, has actually grown significantly. The cost of internal mobility at large organizations, which is something that we now handle natively is extreme in some cases, right? If you have 30% churn in a certain type of organization, certain type of industry, being able to actually prove that we had through the system that we now control, 10,000 people apply to and achieve a new role within the company. That's not pixie dust that we're saying, oh, yes, we were going to save money. This is real 10,000 people, if you find your cost of hiring a new person is 10% to 15% of the head count, those kind of things. So we can start pointing at real numbers, especially based on some of the new things that we have access to. And sales use case is obviously the easiest one. But you can imagine now that we can connect to all of these different sources of truth and we can understand, for example, a salesperson -- we're not just looking at did they get onboarded faster. We can now look at things like what their discount rate compared to their peers. And does that imply that their negotiation skill is weaker than their peers? And if we close that negotiation skill gap, can we see their discount rate improve. Those are very -- outcome-driven outcome-based things that we now own the data for versus saying, "Hey, L&D professional hopefully, you're calculating this on the other side because that doesn't always happen. So the closer we can get to give them the real numbers, that's really quite powerful.

[indiscernible]. I think the number you gave this morning was 50% more products shipped in Q1, if I caught that right. And obviously, Scott, you talked about kind of a big product road map coming throughout 2026. So I'm curious if you could talk about the go-to-market, whether it be SIs, resellers the internal team and just kind of how you ensure that the pace of internal innovation is showing up in all those different motions as you go into new enterprise logos, federal and just kind of trying to show up in a unified way.

Interesting question. I mean, that's partially a market question here. But the good news is we're a learning platform. So we have very good internal education as we ship new things. One of the core things that we're trying to do is make sure that the themes on which we're building against are consistent and easily understood, not just by the market, but by our internal people. And if I'm understanding your question, it's more like how do you make sure that people are ready to accept the pace of change. It's customers have to be ready, but also the GTM function has to be ready. And one of the reasons that I'm really excited to work with Mark is because it's not product versus sales at this point. It's -- we're involved in every step of the building the road map and execution. And so fundamentally, we're using our own product internally. We've become customer zero on basically all of our products. Alessio said in the keynote earlier, we don't just build for our customers. We run our own company on it. And so we're able to educate and enable our team way faster than we've ever been able to. And fundamentally, we're building these themes forward. So people understand that it's a small iteration all of these kind of ILT upgrades. We're able to deliver that message and it makes it a lot more simple for people to understand. So it's pretty straightforward together.

I recently asked the question to Mark on certain aspects of our far along we are on our enablement and our success of ramp-up of knowledge on 365, right? And I got a really impressive response recapping what was going on. And so I'm going to pass in the microphone because it kind of makes it feel real and it speaks much to the question you just asked.

I've been very lucky also in my career to work for one of the fastest-growing GTM type companies on the planet. And partly one of the big challenges of that software was the amount of behavioral change required by our customers that often led to people not adopting the platform. And so I've learned through doing that and through helping some other companies and mentorships and whatnot that usually the biggest reason that GTM fails is because we just try to shut too much down their throat too fast. They can't digest it, can't change behaviors fast enough. And then projects initiatives are just abandoned because it doesn't seem like working because there's too much for the reps to do. So we have an extremely regimented enablement framework that's put in place. I spoke about it many, many times. On podcasts, on webinars and whatnot, you can go read about it. If you just Google sales enablement Matrix and Mark [ Costolo ]. But basically, we -- maybe to me is about two dynamics. One, the capability that we want and expect from the reps do we want them just wear something, do want them to be competent or it can be masters. That determines how we certify them in the area and also how big the program that we need to build an enablement is. And then another axis that we use is cognitive load, is it easy change, like clicking another button in Salesforce? Or is it a very difficult change? Like how do they do discovery. That's a very difficult high cognitive load change. We assign point values to products once we score them on those two dynamics. And then my enablement team only has so many points in a quarter that they can give for each role. And therefore, what we do is we say, once you get to that level, the leader has to make a trade-off decision. So they want X or Y because if we do X and Y both fail. If we choose X or Y, one of them will work. And so my field teams have three kind of task masters. Product with new product innovation, marketing with the awesome and innovative stuff that Kyle is doing with campaigns and whatnot. And then my sales operational stuff that I'm doing and the changes I'm making. That's a lot of stuff coming out of rep. And so we have to have a very tailored way of doing it. So what Alessio is talking about specifically is he asked, "Hey, how are we doing in transitioning." So we created a very, I think, really great plan when we took over 365 of having a period where we shared and they helped in more kind of like a support service on top of our sales team. And then we enabled our sales team to a certain degree. And now at the end of this month, we just go to just we're doing it ourselves. But we have what we call an overlay rep, which I'm sure you're familiar with that concept, who's a specialist in that specific product. But when we do that, we now lose that support system with the 365 reps. So how do we make sure that goes on? Well, one, we've done extensive product knowledge on 365. Two, we then said to each of our managers what do you need? And we [ say ] we don't feel like we're experts on skills-based organizations. So we did a general overall knowledge of how do I just talk like an expert on skills? Then we rate that by having three live call record scored by each manager for each rep that shows how good are you coming along in that area. Then we have a measurement that we are doing right now, where we look at [ coloring ] in 365 ICP accounts. We measure exactly what percentage of available accounts are we having skills-based conversations? And where are our reps avoiding it? Happy to report 84% of all of our ICP that can buy skills right now and buy 365 is being talked about skills and 365 are being talked about in those conversations, what I think is super strong after less than 90 days post acquisition. That they just found out about it like 90 days, it gets pretty insane. And then what we do is then we have multiple overlays because we've actually seen on par demand with what we expected. So we have like overlays and we're hiring to help with the industrialization and the capacity there. So that's just an example of you can listen been in companies where I've acquired stuff and it just kind of gets thrown over the fence and then like figure out how to sell it. And I remember as a seller that happening, I don't like it. I remember having as a VP, I don't like it. As a CRO, I have a little bit more control and a very supportive executive team. that allowed us to create a really awesome plan. And I think we're working the plan. And as Brandon said, in 71 days to do a 6-figure deal on an enterprise customer that's pretty awesome.

Rob Young from Canaccord Genuity. In just two short [indiscernible]. First would be on FedRAMP. Can you just put that into context for us? The backdrop is really complex but just given the [ rate ] guy and the comments on the pipeline, can you just give us an update on FedRAMP? And then the second one, can you give us just a bit of context around the acquisition of side where it fits in if there's any financial implication for us to consider.

From a FedRAMP perspective, I think we we're really looking at the government sector in two avenues. Number one is the Fed, number two is SLED. SLED is a segment we've been in for roughly probably 18 months. And we're seeing strong demand. We're showing the logos every quarter, and they actually have a different seasonality than Fed Q2, June 30 is the most states where the department ends further budget cycles. And we are actually seeing from a demand perspective in SLED, Q2 will have a contribution from SLED more outsized than Q1, Q4 of last year. And from a Fed perspective, we're seeing the pipeline. The one thing that I'd say is from a Fed perspective, they tend to be less units at higher value, so it's really up to us to execute and hit those units. They certainly will happen on September 30. So if we think about revenue contribution for 2026. We're really only talking about 90 days of revenue contribution. So from a sled perspective, it's going to contribute to 2026. It's going to contribute to revenue growth. from a Fed perspective, while it could contribute to ARR, it's more meaningful from a revenue perspective in 2027.

We acquired the Zive team because it was a very natural complement to what we were already in the process of building. As I said earlier, Rob, you should think about it in the context of accelerating road map and the talent acquisition. Peers and team, peers joins Docebo with a handful of highly sophisticated AI native developers. And what they've built is something really strong. They have essentially built an AI knowledge platform supported by agents designed for the enterprise-grade customer. If -- to simplify it, Zive built a business that is not too dissimilar in its principles from something clean that you guys may be familiar with. In our context, we're not a company that goes and sells as a primary business buyer to the CIO office for IT horizontal projects. So that is what knowledge management business in tender in its own category would be. That is what we're going customers ourselves at Docebo. We understand that business really well. Our CIO is here, and he can tell you everything about that. Our intent with Zive was first to have a technology that is proven to help us accelerate our ability to expand upon the need that we heard from customers that knowledge, the assets, the know-how of the company was existed well be on the [ debate ] of the LMS. And that was something that we had begun to tackle with our project Armony, but we saw an opportunity at the right cost compromise to accelerate that implementation. And the second thing has been the [indiscernible]. Zive gives us, thanks to the knowledge of enterprise knowledge module that we're inheriting. The opportunity to build very strong agents with an agentic store that already is part of it.

Just want to add on Zive, just to be completely transparent, the purchase price was immaterial, which is why we haven't announced it, and it's not going to contribute any revenues to 2026. We're essentially taking our existing product. We're shutting it down and we're having them focus solely on embedding in their technology within Docebo. We have time for one more question.

Richard Tse with National Bank. In some of those demos this morning, it sort of looks like you guys bought up against kind of HR a little bit. So if you kind of look at L&D or the system of record, is there a path to being a system of record for HR in a broader context as a software company.

I'm sorry, is there what?

Human resources like back office systems for HR?

The -- if you look at our product road map, and if you think about skills being a critical part of the story integrated with learning, there certainly is an adjacency with the HR buyer. In fact, we -- Mark was mentioning enablement, one of the critical aspects of the enablement is how to talk to a Chief People Officer, a Chief Talent Officer, on the topic of skills. It is not something that we're doing before. But learning in most enterprises runs into the HR business. So in regard, not a -- I don't believe that we are in any way, aiming to enter the HR camp. But I would agree that the skills capabilities get us one step closer to the HR buyer persona, no doubt about that. We are not intentional about going towards the HR route, if that was what you were asking, Richard. If you think about our road map, there's many other developments that go actually in an opposite direction. Think about the innovations also on the e-commerce side and the desire to amplify that customer experience business and the business of transforming Docebo in the revenue engine for our customers. But the internal use cases are big. And the more we work with these mega enterprises, like I said before, in order to unlock the magic sauce, and the magic sauce for us is what? Internal plus external training to unlock the viability of winning the full share of wallet that is in a customer. We have to have this proficiency and its capabilities that range from the more HR learning side all the way down to the CX customer experience side.

Thank you, everyone, for coming, and we'll be around for Q&A after as well.

Thank you.