Sticking with us here in the afternoon of our 44th Annual Growth Conference here in Boston. Very pleased to welcome back again this year, Coveo. And on behalf of Coveo, Brandon Nussey, who is the Chief Financial Officer. And so, Brandon, just to, you know, level set and set the stage for our discussion, which we're gonna have in a fireside chat format, maybe I'll just get you to, you know, introduce Coveo yourself, and perhaps provide a little bit of an update on the, you know, the current financial situation, just so that we can use that as a launchpad for the discussion today. Sure, excuse me. So Coveo, we're an AI software company. We've been helping large enterprises leverage the benefits of AI to help on things like solving customer service problems, so that customers get answers and don't have to talk to agents. Helping e-commerce sites, so that visitors put more in their cart upon visit. We've been doing this for the better part of a decade, helping large enterprises with these specific problems. Gen AI comes along 18 months ago, and it's been a very noisy, hyped up space for the past 18 months to say the least. And Coveo, you know, we have the advantage of being in this market and doing these things for a long, long time, and a lot of experience in doing it. So as the hype sort of subsides, you know, we view that ultimately as a good thing. Because we're a company with real customers, doing real things, with real revenue and real ROI behind it. Company is about 700 employees. We're based in Quebec City. About $130 million in revenue. We'll generate about $10 million of operating cash flow this year. Growing in the 10%-15% range, let's say that. It's been a disruptive last 18 months with all the noise and hype, but, you know, we think we're well positioned to see that growth start to re-accelerate now. Has that hype gone away yet? I think it's starting to. You know, it's really been unprecedented times, where you have so much interest in what you do, but big enterprises in particular have just needed to go through this process of understanding the black box that is AI. You know, previously, we had to almost pull customers into understanding that AI can do a better job than rules, than humans can, at in terms of giving product recommendations or answers to queries that may come in. We don't have to do that anymore, but the customers have needed to go through this education phase of getting comfortable with security, and privacy, and accuracy, and even cost has been a big driver, and that's what's been happening in our market. You know, they've gone on this education and experimentation phase. We're starting to see the green shoots of companies making decisions and going into live deployments. We're proud to hold up our customer list of companies who've put us through our paces. And, you know, little companies like Dell, United Airlines, SAP, all choosing us to be part of their generative AI solution set. And standing up to getting real results with them. You know, Xero is another one. SMB 4 million customers they have. Since turning on our Generative Answering product, 22% fewer cases go to an agent. That's a real ROI for a company like that, and, you know, we're proud of those results, and, I think we're gonna see, you know, a lot more of these deployments start to move forward now. You know, we'll keep on the theme of AI. It's obviously very central, and it's everywhere right now. But I mean, to say you provide AI solutions for enterprise is something everyone's saying now, but you guys have been doing this for a decade, or I mean, don't quote me on that number, but whatever it is. And before it was generative AI, you've... You know, your software is built on machine learning, and maybe you wanna talk to, you know, what—how that artificial intelligence pedigree provides a competitive advantage for you when you're out there displacing spend for enterprise search, and in the areas that you do. Yeah, so I mean, part of the what we've needed to work through over the past 18 months has just been AI is this very generic term, right? There's a lot of hype, to your point. Every software company on the planet has put those two letters on three-quarters of the slides in their slide deck. That's very different from what we've done, where, you know, we've been using machine learning and purpose-built AI models to solve very specific problems for enterprises, and we've been doing that, as we've talked about, for a long time now. And that's part of the secret sauce is, you know, to do customer service well, it's not just that, can you respond to a query that comes in? You need to do that in milliseconds. You need to do that across... Our customers have their data all over the place, right? The answer to a given query that might come in might reside in Salesforce, it might reside in a product PDF page, it might reside in Confluence, a YouTube video, what have you. We bring all that data together. We respect the security, the permissioning, the privacy that these enterprises have invested bajillions of dollars in. And that's a core part of what we provide, and then from there, our AI models that we've been building over a number of years have learned about your data. What is most responsive to a given set of query? We're really good at understanding the semantics behind what's being asked and what your data is telling you. And then from that, we call it relevance. We take the subset of data that's most relevant to that given query, and we now populate an LLM, or we feed that through an engineered prompt to an LLM and generate an answer. That is a much more efficient process, it's a more cost-effective process, and it drastically reduces the amount of inaccurate results. If you're United Airlines, one of our customers, you care a lot about if somebody comes to your website and asks the question, the one we've been using today: Can I put my pad in the overhead bin? You care a lot about how you answer that question, and that matters a lot to that brand. Hallucinations and answering that question wrong matters deeply to them. Because we've got all this intelligence and all this relevance layer, and we're really good at this 'cause that's what our company's built on, we're able to get to that finish line with, with a much higher accuracy rate, in a much better way. One of our customers that lets us talk publicly about the results is F5 Networks. They put us head-to-head against the internal build project of, you know, IT and licensing, an LLM, and data lakes, and all of that, with the big platforms that you can imagine would be calling on an F5, with Coveo purpose-built, right? To solve customer service problems for them. And, I think their quote at one point was, "We would actually get a negative ROI through these other initiatives," meaning there'd be more cases because of the inaccurate results, "and Coveo is a gold standard." And so now they stand up, and they talk about 11% case reduction the first month using us. You know, that's a real company paying us real money to—and it's live, and people can go see it and touch it themselves. So it's, it's been a journey, but, you know, we're optimistic on where this market's going from here. So it brings me to the million, billion-dollar question. You know, AI, it seems like you're right at the center of a lot of very powerful trends. You know, albeit with some noise right now, why not faster than 10%-15%? And I'll ask probably 10 more questions that are gonna be around getting to that answer. You're the first person to ask that. I must be. It's, it's incredible. No, I think it's... That's the dynamic we've been battling. The hype's been there. Customers get the marketing messages from every direction right now. The new shiny start-up, the big platforms, the internal build. And our market has really gone through this period of, I'll say almost freezing, right? As they go, and they get educated, and they experiment, and they run proof of concepts, and they start to see, "Okay, not getting the results we wanted to see from platform XYZ. Okay, starting to like what we're seeing from Coveo," and it's just been the process. We have dozens of these proof of concepts that are currently underway. We've now signed 30 of our 700 enterprise customers onto our generative answering. 30's not 300, but 30's 30. That's -- you know, we're making some reasonable progress here. I do think that this market is now across the education cycle and ready to start to move forward. That's been the biggest headwind. There's obviously things that we can do better, and we've made a number of changes internally as well, but that's been the journey. The market has been challenged. Enterprise spending, we hear it from countless, software companies here that sell into the enterprise. There's pressure on those budgets, those decisions. What are you seeing there? Yeah. So the nice thing about what we do is AI is getting prioritized inside of budgets, and companies are going out of their way to try and free up AI budgets. That's the positive, you know. Still got to go through that journey of, you know, getting comfortable with what they are, where their data's going, all the security, everything I just talked about. But the nice thing about our space is two things: One, it is topical, and companies are going out of the way to prioritize budget for it. And two, we drive real ROI. You know, like, when F5 can say 11% fewer cases hitting agents, that matters. On the commerce side, we're able to see revenue per cart, revenue per cart visit, increases of 5%+, which for a big retailer, you know, leveraging the benefits of AI to show the right product, personalized to your intent and your journey, makes a huge difference. That's the stuff that's getting prioritized inside companies. No question, a more lenient macro would be a welcomed thing. But yeah, our space does have some advantages. Feel free to jump in at any time. If you guys have questions, raise your hand. I do wanna make this interactive with the audience. Failing that, I will just keep going with my barrage of questions about your growth rate. This relative, the generative answering product is an upsell to your existing product. You've gone through the beta phase and the early adopter pricing, but maybe just, you know, let's just step back and maybe talk about what that could mean to your revenue line as more of these 700 customers start migrating, and maybe just you could just give an example of what that looks like. Yeah. So the average customer that we have is just under $200,000 a year in revenue they'll pay to us. It's a subscription fee, entitlement package that goes into that. That's our average customer. We've priced the generative add-on at 40% of a customer's ACV. In the early days, in part because, you know, managing our own capacity and our own bandwidth, we set a minimum price of $150,000 per year per customer on that. We've relaxed that a little bit, but our average is not too far off of that right now. You know, at our last capital markets day, we went through our 700 customers, and we'll do, you know, a wide range of things for a wide range of customers. Not everyone's gonna want generative AI capabilities. We estimated a little more than half of our customers are a good fit for this solution. So that's that, and that's one opportunity, is just upselling existing customers, this generative AI add-on. The bigger opportunity, frankly, is, you know, we can do a number of things to help a company, whether it's commerce that I've talked about, customer service I've talked about, internal knowledge management, of getting answers to your employees. You know, big financial services companies use us. Some of the biggest banks down here, some of the biggest insurers down here use us. And we'll do just, you know, like for United Airlines, on united.com, we power the website search that's behind that. 30% of our customers use us for one of those things. Sorry, for more than one of those things right now. 70% use us for only one. Capturing more of that white space is a big opportunity, I think, for our business. The average ARR per customer goes up drastically when we can start to turn that dial. And so how do you do that? I mean, on one hand, you're talking to a customer support leadership. On the other, it's someone managing an e-commerce website. How do you, how do you break those silos down to penetrate that better? Yeah, it's a great question. It's real work, is the answer, which is why we reorganized our sales organization. Previously, we had a, let's say, a homogenous sales organization that could sell to new customers, and we're also responsible for growing the base. You know, during tough macro, selling new customers becomes harder. If you weren't a line item in somebody's budget, that's a tougher sell. So we saw our sales team gravitate towards generative AI upsells, and, you know, why go, you know, cross those silos, as you said, if, if I can make quota by just upselling gen AI right now? Which is fine. Ultimately, we want it all. I don't discriminate on the type of bookings we get. I'll take them all. You know, that focus, what we did is create a hunter-farmer organization now inside of sales, where the hunters are primarily responsible for new logos. Farmers are, their job is to grow. It is real work, and that's okay. That's why we're paying you. We've now got dedicated folks around that to go after that opportunity. That's pretty new for us. April first is when we formally launched it into the wild. Early days on that, but all designed to drive better outcomes on both sides, on the new logos as well as upside, upsell. One of the things you guys have been, you know, very vocal about and talking about as you justify that price increase, is that there's quite a big cost increase to providing this service, and that's not something that a lot of the competitors are talking about. I mean, if you wanted to dump your entire corporate data into OpenAI, and then start having every customer use it, you're gonna boil the ocean for power and compute resources. So how do you guys manage that internally? What is it about Coveo, and the underlying technology that helps you get a leg up on the competition when it comes to that? Yeah. So, you know, again, rewinding, and I know some of this is repetitive, but it's all context and all important. When OpenAI, ChatGPT, take the world by storm, you know, however long ago that was, 18+ months ago, it didn't take our company long to start to say things like: "Yeah, but what about security? Yeah, but what about privacy? Is anybody thinking about cost?" In the beginning, it was like us yelling into a really noisy, crowded room. Ultimately, that's where companies are coming out the other side. They're recognizing that, "Okay, so I gotta go build a vector database and put all my data in that, and then I gotta go feed all that to an LLM and train that LLM. And when the LLM releases a new upgrade and forces me off of this model, I gotta go retrain that new thing again." The costs inherent in this for a company are huge. What we do and our value prop, that's resonating increasingly more now, we don't move your data. We connect securely to your systems of record. We build an index around it, and then when it comes to a given query, we're taking just the subset of that data and feeding that LLM, and that really helps manage costs for these organizations and take that out of the equation. And it's sourceable, and there's a whole... you know, competitive differentiation in doing that versus a black box- Yep. LLM. Let's talk about the partnerships that you are working on. I mean, with the generative AI, it sort of receded to the background in terms of, you know, what you've been asked about in recent earnings calls and the like, but, you know, very potent partnership aspirations. So maybe why don't you expand, just, you know, where, where are you now? Where would you like to go, and with whom? So this company's always, it's been a strength of this company, that's helped build it to $130 million in ARR right now, or thereabouts, is leveraging alliance partners. My predecessor's in the room here somewhere, so I take no credit for any of this. But, Oh, there he is. In the customer service space, Salesforce has been a long-standing alliance partner of the business. Salesforce is one of our biggest customers. Service Cloud runs a lot of the support portals for a lot of the world's biggest companies. Salesforce, we have an alliance agreement whereby, you know, for their most complex customers, they bring it, like themselves, Salesforce being one of them, they will bring Coveo into those opportunities to help solve these challenges that, you know, Salesforce is good to a point, but they kinda top out at a certain level of complexity. And that's where Coveo steps in. Adobe Gold Partner, so for website, empowering just website search for, you know, Adobe-based websites, we're a gold partner there. And the one that's that we're excited about, not that we're not excited about all of them, but recently was named an endorsed partner of SAP for their CX groups. And what that means is, SAP's got 2-3,000 of their customers. Some of the biggest manufacturers and retailers use SAP's commerce platform, and Coveo is the exclusive endorsed app for AI-powered search and recommendations for those, for that platform. And what that really means is that, if you're an SAP salesperson, you get full quota relief every time Coveo's sold to one of your accounts. So we've announced that partnership about 18 months ago. It's been, you know, over the last 18 months, we've gone through the process of identifying the opportunities, enabling the sales organization, starting to build pipeline, and as we look ahead to solve our growth rate question, we expect to start to see this partnership and that pipeline turn into bookings at an increasing pace. We announced a deal with a book retailer called Thalia, which I'm told is the Barnes & Noble of Germany. That's an SAP account. That's a recent win that we announced in Europe. Nespresso is another good joint customer win of the two organizations, and there's lots more to do there. So we're excited about that one. And so just to wrap up the growth line of questioning—here, with two minutes left, you've seen, you know, a lot of this generated by AI, some of these other growth initiatives. We've seen them go from a qualitative description about, you know, the level of engagement with your customers to identify potential pipeline. And now what you're saying, I think you've started to see, is that start to convert to bookings, and then ultimately will drive the revenue growth inflection that everyone's looking for in the quarters ahead. Is that a fair— It's- representation of how things look right now and where we are in this process? It works real well on my spreadsheet. Let's just say that, that's the thesis. We do think that, and it, enterprises have gone on the journey, and it's not just us. In the beginning, it felt like it was just us saying this, but there's enough financial industry analysts now that are writing the exact same set of commentary that, you know, experiments are expected to turn into decisions and, deployments, and we're optimistic that we'll be a beneficiary of that. It'll take work. It'll need. We need to keep doing, good things on innovation. We need to execute well. We need, we got a new CRO in town, you know. Want that to go well, so, you know, we need to, of course, do our part in all of this, but, we're optimistic that that's the phase we're at. Let me switch gears here. We're gonna... CFO, ex CFO. Let's talk about costs and profitability, and that's- Yeah. ’cause that’s been a good part of this story over the last— Yeah - quarters. Yeah. And, and so you're now at a... You're profitable, you're expecting to generate cash flow this year. How do you balance that against the growth opportunity, the level of spend, as you try and navigate towards a target model? Maybe you wanna describe what that might look like. It's the toughest problem, I think, for most certainly public organizations, is to balance that. Of course, us, like anyone else, is, the rule of 40 is what guides us. And you're trying to figure out the right recipe for your business. We've worked hard. One of the things, again, I think I inherited from my predecessor, that this company's really good at, is making the most important thing, the most important thing, and making the difficult trade-off choices there. You know, one source of revenue that's dragging on our overall growth rates has been a decision we made to disinvest in a certain product line. So, you know, we're seeing some churn from that decision, but we're far more focused, and we're far more profitable as a result. So these are the tough choices that I think this company's done a nice job of demonstrating. We've held OpEx, and if you go back, you can look, I think, the last four fiscal years, if you were to include the current year's guide, basically flat for four years and let 100% of the revenue growth flow to the bottom line. And underneath the covers, underneath the waterline, there's a ton of trade-off choices and tons of decisions being made there as to what we're prioritizing and deprioritizing. But we're doing that, to answer your question directly, we're proud of the progress we've made. Our intent is to stay cash flow positive. Our priority is to increase our growth rates from here. There's other levers we can pull to maximize cash flow, but, that's not our choice right now. It is so 'cause you've also got a very healthy balance sheet. Even after spending another chunk of money buying back stock, that continues to be your preferred use of excess cash, it seems. So maybe you can confirm that. Talk about what the level of comfort is, how much of your cash is considered excess in your mind that, you know, you could use to continue to buy back stock or for other initiatives? Yeah, we have $130 million in cash. To your point, we've done two SIBs, two substantial issuer bids, over the past 14 months. You know, we see a share price that, in our view, doesn't reflect our prospects. It's not a real healthy M&A environment out there right now, so we are cash flow positive. Supporting the stock is with some of our excess cash, is putting our own money where our mouth is, and that's been a decision that's been a straightforward one for us. Going forward, you know, we, we've got an NCIB in place, and we'll look to use that in opportune spots, and otherwise, look to reinflate growth rates. We're just about out of time here. I'll just do one last call for any questions. There's one. I had a question on the agents that, you know, Google says that the agents, the AI agents. So, do you feel that they are kind of coming into Coveo's space, or how do you feel about it? I think all the platforms, Microsoft, Google, Salesforce, ServiceNow, they'll all have some initiative in and around this. Our space in this market is complexity, right? So Dell is a big customer of ours. For you to do a good job of customer service at Dell, you need to be really good at handling complexity. Lots of visits, lots of languages, lots of SKUs, lots of different types of questions that come in, and building a productized experience around this so that the Chief Customer Officer at Dell can get whatever analytics they want, to get whatever set of reports and metrics they need, and to know that CSAT is going up. I don't think that's the DNA of the platforms. I think that's a specific challenge for a company like Coveo. That's where we're focused. Is it fair to say that being independent of all those platforms is a selling feature as well? Absolutely. You can talk to all of them- Yeah ... as opposed to being beholden. Yeah. Okay, we're out of time. So with that, I'll thank Brandon for the time today, and Coveo, and we'll clear the stage for the next presentation. Thank you.