Coveo Solutions Inc.

Good afternoon, ladies and gentlemen, and welcome to the Coveo first quarter fiscal 2027 financial results conference call. At this time, all lines are in listen-only mode. Following the presentation, we will conduct a question and answer session. If at any time during this call you require immediate assistance, please press star zero for the operator. This call is being recorded on Thursday, July 30th, 2026. And now, I would like to turn the conference over to Adir Kadve.

Please go ahead.

Good afternoon, everyone, and thank you for joining us. With me to discuss Coveo's first quarter fiscal 2027 results are Laurent Simoneau, Coveo's co-founder and chief executive officer, Louis Tetu, Coveo's executive chairman, and Kevin Amell, Coveo's chief financial officer. A reminder that some remarks made today will be forward-looking statements within the meaning of applicable securities laws, including those regarding our plans, objectives, expected performance, and our outlook for the second fiscal quarter and full-year fiscal 2027. These are forward-looking statements given as of July 30, 2026, and while we believe any statements we make are reasonable, they are based on current expectations and assumptions which are subject to risks and uncertainty. Actual results could differ materially from those expressed or implied. Coveo disclaims any intent or obligation to update our forward-looking statements, whether as a result of new information, future events, or otherwise. Further information on factors that could affect the company's financial results is included in the filings we make with Canadian securities regulators, including the risk factors section of the company's most recently filed annual information form, as well as key factors affecting our performance section, of the company's most recently filed MD&A, both of which are available on our CDARplus profile at cdarplus.ca or on ir.coveo.com. Additionally, some financial measures and ratios discussed on this call are either non-IFRS measures, ratios, or operating metrics used in our industry. A discussion on why we use these metrics and where applicable, a reconciliation schedule showing IFRS versus non-IFRS results are available in our press release and our MD&A issued today. Finally, please note that unless otherwise stated, all references and financial figures made today are in US dollars. Our presentation slides accompanying this conference call can be accessed on our IR website under the financial information section. I will now turn the call over to Louis to review our platform and strategy, followed by Laurent taking us through our operational and strategic highlights of our first quarter, and we will end off with Kevin taking you through the financial details and provide our outlook for the second quarter and full year fiscal 2027. We will then open the line to your questions. With that, over to you, Louis.

Good afternoon, everyone, and thank you for joining us. We're pleased to report another successful quarter as we begin fiscal 2027. Revenue came in within our guidance, adjusted EBITDA slightly above our expectations and once again we generated strong positive cash flow. Those are encouraging results and they reflect the discipline with which our team continues to execute. Since quarter end, we've reached another important milestone for Coveo. For the first time, we now have a customer generating more than 10 million US dollars in annual subscription revenue. We've spoken before about our strategy of building larger, more strategic customer relationships as the value and importance of our technology continues to increase. This milestone is a meaningful validation of that strategy. It reflects not only the value customers place in our unique technology, but also their trust in Coveo as a long-term partner. To me, though, this quarter says something even more important. It tells us that the enterprise AI market is maturing and that the characteristics that have always differentiated Coveo are becoming increasingly essential. Over the past three years, we've seen the AI market move through several phases. First came extraordinary advances in foundation models. Then came an intense period of experimentation as enterprises explored what generative AI could do for their businesses. Today, I believe we're entering a new phase. The conversation has shifted from possibility to deployment, from experimentation to production, from excitement to measurable business value. And perhaps most importantly, buyers have become much more educated and sophisticated. Our conversations with CIOs, digital leaders, and business executives are very different from those of 18 months ago. Enterprise leaders now understand what it takes to deliver AI at scale and that using an AI or large language model is only one piece of the puzzle. They understand the importance of trusted enterprise context, security, governance, relevance, orchestration, and continuous optimization. They also understand that AI must work in the real enterprise, not in a demonstration but across thousands of employees, millions of customers, many systems, and enormous volumes of information and interactions. That growing enterprise AI literacy plays directly to Coveo's strength. We're also seeing a healthy impatience around return on investment. Organizations are no longer satisfied with demonstrations or isolated pilots. They want measurable improvements in customer experience, Employee productivity, digital commerce, and operational efficiency, with the P&L and balance sheet keeping the score. They want AI that delivers business outcomes, and that is exactly where Coveo has always focused. At the same time, another important evolution is underway. Over the past two years, much of the market's attention has understandably focused on AI infrastructure, chips, cloud, and foundation models. Those technologies are incredibly important, but attention is increasingly shifting towards applied AI, the software that actually puts AI to work inside the enterprise. That's exactly where Coveo belongs. Our vision is to lead the experience AI market. Our technology helps enterprises compete in the experience AI economy. because if you think about how most people experience artificial intelligence today, the most pervasive use of AI for all of us is through digital interactions. We're online to learn something, to buy something, to solve a problem, to find answers, to fix something, to discover new products and solutions, to move from intention to outcome quickly and effortlessly. Every one of those moments is an AI opportunity and every experience needs to be trusted, contextual, personalized, prescriptive, conversational and precise. Qualities that are not humanly possible at scale without AI. Those same expectations now exist inside every enterprise. Businesses deliver millions of digital interactions every day to customers, partners, suppliers and employees. Those interactions increasingly determine customer loyalty, employee productivity, revenue growth, and competitive advantage. That's the large and consequential market we're building for. Coveo provides the intelligence layer that connects intricate enterprise context and data with AI models to control and optimize those experiences. Our confidence is growing. because enterprises have learned important lessons over the past couple of years. They've learned that AI models do not intrinsically understand your business context. That context is distributed across the organization in many systems and sources of data. They've learned that moving everything into one system to capture context is neither practical nor economical. They've learned that AI models are also evolving quickly becoming more specialized and increasingly commoditized. With hundreds of models now available, including the rise of open source and sovereign AI, locking into a single model is not a sustainable strategy and the cost of tokens is now a key consideration. And now they're learning that AI agents are proliferating and also emerging as a major interface for enterprise software. Our platform was designed exactly for this environment. We're independent of content and data repositories. We're independent of AI models, which we A-B test. We deliver intelligence wherever the experience happens, on a website, in a commerce application, an employee workspace, a service experience, or increasingly through an AI agent, also grounded in Coveo as the unified data and context pane. We ground those experiences in trusted, permission-aware enterprise contexts continuously optimize relevance and deliver precision at enterprise scale. So as organizations better understand the architecture required to operationalize AI, they increasingly recognize Coveo's critical role. We see that recognition translate directly into our business. Customer relationships are growing broader and more strategic. Customers continue to expand their investments with us. Seven-figure subscriptions continue to grow. And today, we are proud to have reached our first eight-figure annual subscription customer. Those are not simply larger contracts. They're evidence that customers increasingly seek Coveo as foundational to their long-term AI strategy and to the experiences they deliver across their businesses. Our partner ecosystem is also encouraging. System integrators and technology partners are investing more in Coveo enablement and bringing us into larger enterprise transformation initiatives. As enterprise AI becomes mainstream, we believe those partnerships will become an increasingly important growth engine. So, our confidence in this growth opportunity shapes how we invest. Since becoming a public company, Coveo has roughly doubled in size while building a business with strong recurring revenue, with subscriptions representing 96% of total revenue, healthy product gross margins of more than 80%, and disciplined financial management. We believe that's an important economic combination. As the applied AI market matures, we believe shareholders are best served by continued thoughtful investment in innovation and in expanding our go-to-market capabilities. Each time we increase the value we create for customers, We create opportunities for larger, longer, and more strategic relationships and strengthen our trusted brand. That's exactly the pattern we're seeing today. So looking ahead, we remain very optimistic. We believe experience AI will become one of the most important applications of artificial intelligence for enterprise competitiveness. Organizations will increasingly differentiate themselves through the performance of the digital experiences they deliver. And we believe Coveo is uniquely positioned to make those experiences trusted, intelligent, and economically measurable. Before I turn the call over to Laurent, I want to thank our employees for their commitment and execution, our customers for their trust, our partners for extending our reach, and our shareholders for their continued confidence as we built this business for the long term. With that, I'll hand things over to Laurent.

Thank you, Louis, and thank you everyone for joining us. We entered fiscal 2027 with three clear priorities. Deepen our relationships with the world's largest enterprises, continue leading through innovation as enterprise rapidly evolves, and grow our business efficiently while investing for the long term. I am pleased to Let me start with our first priority, deepening strategic customers' relationships. Our customer momentum continues to validate both our strategy and the high economic value and uniqueness of our platform. We see this as a key to increase sales, deal size, and the strategic value of Coveo to our customers. During the quarter, we expanded relationships with customers including Nespresso, ADI Global, Enbridge, Linda Agee, and others, while also signing another seven-figure subscription with a Fortune 500 leader in healthcare distribution. These wins reinforce that as enterprises move from the experienced AI era, competitive advantage increasingly comes from the quality of the digital experiences they deliver. Our customers are no longer buying isolated AI capabilities. They are standardizing on our platform across their digital experiences capabilities. We enable them to compete in the experience AI economy by securely connecting enterprise knowledge and product catalogs, grounding AI in trusted context, and continuously optimizing customer and employee experiences at scale. That is exactly where Coveo is differentiated. Turning now to our second priority, continuing to lead through innovation. Innovation continues to be one of our strongest competitive advantages, and a market adoption we're seeing across our newest AI capabilities reinforces our conviction that we're investing in the right areas, what our customers care about. Our conversational search solution is now live in production with customers, while several dozen additional organizations are actively evaluating. We're also seeing strong early demand for conversational product discovery with customers onboarding and many others progressing through evaluations. During the quarter, we introduced merchandising co-pilot and we're seeing strong early adoption. The majority of merchandisers using the product engage with it at least once each week, demonstrating that it is becoming a regular part of their merchandising workflow. Even more importantly, a growing number of merchandisers are leveraging our AI recommended actions to automate storefront optimizations. In some customer environments, AI driven actions have now surpassed manual merchandising actions, offering an early glimpse of how AI can evolve from assisting teams to actively operating parts of the business. A broader product strategy remains centered on customer choice and interoperability. Rather than locking organizations into a single model or AI ecosystem, Covil provides the trusted intelligence layer that enables customers to adopt the AI technology of their choice while ensuring those systems are grounded in secure, governed, and highly relevant enterprise knowledge. Let me bring that strategy to life with two customer examples. Netcash is one of Australia's leading distribution business across food, liquor, and hardware, generating nearly $15 billion in annual revenue and facilitating more than $4 billion in B2B e-commerce sales. By bringing together information from Adobe Magento, SAP, and Salesforce, Clio created an intelligent experience that understands bulk products and customer context across the buying journey. The results at Metcash have been exceptional. Revenue per visit increased by more than 25%. Conversion improved by more than 30%. An average order value increased by more than 10%. Just as importantly, shortly after going live, Metcash expanded its relationship with Coveo beyond commerce into supplier facing workflows, extending both our AI search and our generative AI capabilities. That is exactly the expansion motion we strive to create. We deliver measurable business outcomes, and this leads to broader strategic adoption across the enterprise. Lynda is another excellent example. As one of the world's largest industrial companies operating across more than 80 countries with highly technical products and complex global operations, Lynda requires AI that performs reliably at enterprise scale. They initially selected Coveo to power their B2B commerce search experience in a single market. Since then, they have expanded our platform across additional markets and languages while partnering with us across a broader vision of unified, intent-driven experiences that seamlessly connect product discovery, technical guidance, and post-purchase support. We believe that vision represents the future of enterprise commerce, and Lynda is helping shape that future alongside us. Finally, I'd like to touch on the largest transaction in Coveo's history. As we mentioned earlier, shortly after quarter end, we closed the largest transaction in Coveo's history, expanding our relationship with a Fortune Global 500 technology leader to more than $10 million in annual subscription revenue. I could not be more excited about this and what this means. This customer now relies on Coveo across multiple strategic AI experiences, spanning both customer-facing and internal applications. Our platform also serves as the grounding and intelligence layer behind their Argentic AI initiatives. What makes it truly meaningful is what it says about the market. This is one of the world's most sophisticated technology companies. They understand AI deeply, work directly with frontier model providers, and possess world-class engineering talent. Yet they chose Coveo as the strategic platform for enterprise AI. Let me close with one broader observation. When I step back and look across these customer examples, I believe they all reinforce the same conclusion. These organizations have the technical capability to build many things themselves. and the authority to engage any technology vendor relationship. But building enterprise AI at high scale and precision that consistently delivers measurable business outcomes requires much more than integrating a large language model. It requires trusted enterprise context, secure and permission aware retrieval, governance, continuous relevance optimization, interoperability across rapidly evolving AI ecosystem, and the ability to deliver those capabilities consistently at enterprise scale. Those capabilities are not commodities. They represent years of investment at Coveo, deep domain expertise, and proven execution working with hundreds of the world's largest brands. That's why sophisticated organizations continue to choose us. As enterprise AI moves from experimentation to production and real results, our customers increasingly question their ability to build these capabilities themselves. We give it to them out of the box, flexible, precise, secure, and cost effective, and we keep them in tune with future AI innovation. The customer momentum we're seeing gives us real confidence that our strategy is aligned with where the market is heading, that our timing is right and that we're a market taker. We solve some of the most important challenges in enterprise experience AI today and that we're well positioned for the opportunities ahead. As a result, our third priority is growing our business efficiently. Everything I've discussed today reflects a deliberate strategy, invest behind innovation, that creates measurable customer value, expand those relationships over time, and do so with discipline. We do this through a repeatable go-to-market motions in high-value industries that generate viable economics. As you'll hear from Kerien, that approach continues to translate into healthy financial performance, strong cash generation, and disciplined investment as we execute against the significant opportunity ahead. With that, I'll turn it over to Karine to review our financial results.

Thank you, Laurent. Q1 reflected the themes and dynamics we outlined during the fourth quarter results. Q1 bookings were driven by our key growth drivers of commerce, including B2B, GenAI solutions, and multi-use case customers. We also closed another seven-figure transaction during the quarter, this time with an existing customer, reinforcing our ability to grow larger, more strategic customer relationships over time. Looking at profitability, we remained disciplined in our spend, allocating capital to the highest and most efficient areas. This resulted in a slight beat on our adjusted EBITDA guidance, and we generated strong cash flow from operations. Let me begin with a brief summary of our first quarter results. With the full deprecation of the legacy Qubit platform, all SAS subscription revenue came from the CoveoCore platform, which saw an increase of 13% compared to the prior period. Including Qubit, SAS subscription revenue was $37.4 million, an increase of 9% compared to the prior period. Total revenue was $38.5 million, an increase of 8%. Product gross margin was 81% and gross margin was 78% comparable to the prior period. Adjusted EBITDA was 0.1 million compared to negative 1.9 million in the prior period. Cash flow from operating activities was 9.2 million and consistent with our seasonal trends aided by positive working capital fluctuations. Cash and cash equivalents were 107.1 million as of June 30, 2026. and we remain debt-free. NER on the CoveoCore platform, which excludes the impact of Qubit, was 102%. Including Qubit, NER was 99%. Subsequent to quarter end, we renewed our NCIB, giving us optionality to repurchase approximately 5.1 million shares over a 12-month period. And finally, as you've heard from Louis and Laurent, In the first few weeks of July, we closed the largest transaction in the company's history, bringing the total annualized SaaS subscription of this customer to eight digits, an important milestone for us. Looking beyond the financial results, let me spend a few minutes on key booking trends we saw during the quarter. In Q1, we secured another seven-figure transaction with an existing customer, a Fortune 500 leader in healthcare distribution. After successfully deploying Coveo to enhance its contact center and self-service experiences, the customer selected us to power its B2B commerce experience as well. This is exactly the type of expansion we aimed to drive, growing across additional use cases within our core ICP of large complex enterprises. The relationship with this customer began with a low six-figure subscription and has now grown to more than $1 million in annual recurring revenue. illustrating both the breadth of our platform and the strength of our land and expand model. Generative AI continues to be a meaningful driver of our bookings this quarter, representing approximately 30% of total bookings in Q1. More importantly, we're seeing a clear shift in customers' buying behavior. As organizations move beyond AI experimentation towards production deployment, They are increasingly designing AI into their digital experiences from the outset. Our generative AI capabilities are increasingly at the center of initial customers' conversations. As I noted last quarter, this creates a compelling land and expand motion, enabling us to establish strategic relationships earlier and expand adoption across the enterprise over time. On the innovation front, as Laurent discussed, we're encouraged by the early adoption of agentic AI capabilities, including search agents, conversational product discovery, and merchandising co-pilot. From a financial perspective, these innovations create new ways for a customer to engage with the Coveo platform, expanding the number of use cases and user interactions we support. As a reminder, Our customers subscribe to the Coveo platform by committing to a defined level of annual platform consumption, which provides us with a predictable base of recurring revenue. As customers adopt additional use cases and platform engagement growth, consumption can exceed committed level, creating opportunities for incremental revenue over time. We believe our continued pace of innovation supports customer expansion and increased platform consumption over time. Moving now on to customer expansion and retention. Our reported net expansion rate excluding legacy Qubit customers was 102% and 99% including legacy Qubit customers. As we've discussed previously, we continue to view this metric in the context of the broader evolution of our customer base. Our strategy cohorts, including customers using B2B and B2C commerce solutions, customers with multiple use cases, and those adopting our Gen AI solutions, continue to expand at a higher rate than our reported NERs, while legacy cohorts continue to wait on the consolidated metric. Again, shortly after quarter end, we closed the largest expansion in our S30. While the timing of large expansions can create quarter-to-quarter variability in our NER, we believe this transaction reinforces the strength of our expansion motion and our ability to grow alongside our customer over time. Turning to guidance, our outlook remains aligned with the plan we outlined at the beginning of the year. We continue to see ongoing customer adoption, Expansion across our strategic customer base and an active pipeline of strategic opportunities. At the same time, as we've noted previously, the precise timing of large transactions remains difficult to forecast. As a result, we are reaffirming our full-year fiscal 2027 guidance, which we believe appropriately reflects both the underlying fundamentals of the business and the normal timing variances associated with large and complex opportunities. As such, we expect Q2 SAS subscription revenue to be between $38.5 and $39 million, representing approximately 10% to 12% growth on the Coveo Core Platinum. Q2 total revenue to be between $39.7 and $40.2 million. For the full year, we expect SAS subscription revenue to be between $154 and $158 million. representing approximately 10 to 13% growth for the CorreoCore platform. And we expect total revenue to come in between 160 and 164 million. On profitability, we remain focused on making the investment that we believe will drive medium to long-term growth. At the same time, we continue to allocate capital with a disciplined focus on the highest return opportunities and operating efficiency. As such, we expect Q2 adjusted EBITDA to be between 0.5 and 1.5 million. For the fiscal year, we expect adjusted EBITDA between 2 and 7 million. And finally, we expect to generate operating cash flows of more than 10 million for the full fiscal year. Note that we will have some quarterly variability here due to timing of working capital. In summary, the underlying trends in our business remain healthy. We're seeing continued demand for large enterprises, customer expansion, and early adoption of our AI innovation. Our strategy remains unchanged, and this gives us conviction in the long-term opportunity ahead. With that, operator, please open the line for questions.

Thank you. Ladies and gentlemen, we will now begin the question and answer session. If you have questions, please press the star followed by the number one on your touchtone phone and you will hear a prompt that your hand has been raised. If you wish to decline from the polling process, please press the star followed by the number two. One moment for your first question. And your first question comes from the line of Athanasios Mouskopoulos of BMO Capital Markets. Please go ahead.

Hi, good afternoon. Maybe just starting off with the eight-figure customer, can you provide some color in terms of what drove that upsell? So was that a function of the customer adding a use case? Was it just adding regions or product lines or, you know, their increased usage of the platform? What was the catalyst there?

Hi, Thomas. Hello here. So it was an existing customer that where, with Coveo created a lot of value over the past 18 months. And Coveo became an integral part of their AI infrastructure strategy. So they expanded in both new use cases, more experiences, and more consumptions, more languages, for instance. So it's all of the above, Dennis.

Good to hear. And you recently appointed a new head of sales. I know it's early days, but just any initial thoughts in terms of, you know, changes or tweaks to the go-to-market strategy, or is it more just about maintaining the strategy but improving execution?

Yes, absolutely. And Thanos, as you know, we're investing in both our new and existing customer emulsion. We continue to strengthen our leadership bench. Last quarter we announced the arrival of our new CSO that is focused on new customer in motion. So it's been arrived in 30-something days ago, so far so good with progress, but the general The general picture here is we're in strengthening our bench. We're investing in this team that is greatly positioned to go after the opportunities in front of us.

Okay. And just on that note, I guess the problem question is you alluded to how the conversations are becoming more strategic, larger in nature. And so as you think about the motion needed there, Is there some upskilling of the Salesforce supplier? Do you have the right team in place for that? How has that changed your thinking in terms of as you execute on those larger deal sizes?

Yeah, Thanos, Louis, I'll answer the first part of that question. We're seeing a meaningful difference as in the prepared remarks in terms of the strategic nature, scope, value of the conversations with the customers. who, as we said, realize the importance of the Coveo infrastructure to essentially make AI work in a trusted way. That leads to some pretty interesting dynamics in terms of how we deploy our sales motion. In particular, Laurent commented last quarter and this quarter on the forward deployment engineering function, which is essentially designed to help customers understand the art of the possible, discover value opportunities, and essentially, in our case, we have a very agile model to prototype these abilities within a matter of days and weeks, which leads to Thank you for joining us. It's continuously evolving, and we're perfecting that model, and as we nail the model, we certainly are ready to invest and scale it.

And if I may, just as a compliment, basically what we're seeing is the more we're doing up front to reduce the risk and eliminate the risk and crystallize value up front, of course, we increase the probability of a larger deal and faster. We adjust with the timelines of customers and prospects, but we see great value in investing up front with those motions of FDEs. and business value experts.

All right, thanks for the caller. I'll pass the line.

And your next question comes from the line of Suthansu Kumar.

Please go ahead.

Good afternoon, guys. From my first question, I wanted to touch on net new deals. Can you speak a little bit about how Average deal sizes here have been trending. And what's been changing in how net new customers are procuring your offering? I'm just wondering if there's more assessment pre-sales activity that you're seeing? Is there multiple use cases out of the gate now and our partners being more involved? I'm just curious kind of what's changed in the overall end-to-end sales process, you know, in the past year.

Thank you, Sutan, for your question. I would say that we didn't see a major shift into what we had seen and we've talked about and what you've heard from us in the last couple of quarters. Our unit economics are trending in a better direction. We're happy with the opportunities and the logo we're engaging with. And over time, yes, we're seeing the average deal size value growing. So I would say that this quarter aligns with what we've seen in the last couple of quarters.

Okay, great. And then, you know, just, you know, shifting the lens to your existing customer base and more specifically the legacy cohort, what's the strategy in navigating that base? You know, it feels like it's more of a question of when, not if, Gen AI becomes a more important strategy for this cohort. How would you guys, you know,

What's the strategy there? What we call the legacy cohort is, again, the minority of our AIR, which has not yet transitioned to GenAI, to your point, and agent tech. We can't predict exactly how every one of them will. But to your point, I think I'm repeating what you said. I agree with your statement that the future is generative and agentic. And we're obviously designed for that. So there are two things that happen here. We're obviously working to, for those of them who don't feel the burning desire to move quickly on that, we're working hard to keep them. and renew their subscription. As we said before, smaller customers that have bought a search engine on limited content and et cetera for let's say 50K a year or whatever, you will understand that this is not where we put our major investment in. And then the second thing is we're working to obviously transition particularly all the enterprise, the larger enterprise of this cohort, we're working to grow them Again, in line with our prepared remarks, we're seeing more opportunity as the understanding and the literacy of these customers increases and they appreciate the part of the stack that Coveo brings. So that's sort of the color of that cohort. On the flip side, you know, the vast majority of our, well, the majority of our is the strategic cohorts, you know, that's commerce, B2B, industrials, distribution, large enterprise, knowledge verticals, multi-use case customers, etc. And so those in this case are expanding. We said on the last call, we qualified it as high double digits. You know, it's a very, very healthy segment. So that's sort of the dynamic we're in right now. Obviously, the legacy brings down our overall metric, but from an NER perspective and a growth perspective, the company is clearly designed to serve, you know, the majority of our ARR and where we're focused. I appreciate that. Some numbers and colors.

Well, I think there is not much. I think your answer was pretty consistent. And I would say, Stan, the Q1 went pretty much in line with what we were expecting. So, yeah.

Okay, great. And just the last one for me. You guys have been seeing sustained strength here in commerce. Agente Commerce, as a theme, it sounds like it's gaining a lot of momentum here. How are you guys positioned to play into that theme?

Thank you for that question.

So, first of all, you have to remember that Coveo is built expertise in both dealing with complex catalogs and commerce, and also a and many more. Thank you very much. or getting support on a product. And this applies in retail and B2C, but even more into industrials and distribution. So we're quite excited about this one. As we said in the prepared remarks, we have customers that are running production right now and a lot in pilots. So that's an area that is highly strategic for us in the future.

and maybe I should add an area where we're highly differentiated because to Laurent's point, we understand semantic, we understand content. Coveo grew in that world of very advanced, long-tail, intricate customer support in particular where deep engineering and knowledge, content and so on is the norm. And so new shopping experiences require not only the SKU itself but Everything around the SKU, not only the metadata, but if you think about a chainsaw at a DIY supplier, you will index all the engineering manuals, the user manuals, maybe the customer comments and all the service records of that particular SKU. And so you end up in the industrial world where they may have 2 million parts. for aftermarket and complex diagnostic and engineering documents and etc. And you combine all of that to create a unified experience. And that's pretty unique to Coveo because of our ability to merge and blend both the commerce and the knowledge experiences, which is now becoming the norm in enterprise commerce, both in B2C complex commerce and particularly in B2B.

Great.

Thank you for taking my questions. I'll pass the line.

And your next question comes from the line of Paul Traber of RBC Capital Markets. Please go ahead, Paul.

Thanks for taking the question. Good afternoon. You mentioned in the prepared remarks that you're seeing increased engagement with systems integrators. Can you speak to the magnitude of that impact and the change? And then also just generally speaking, with larger deals in your pipeline, how has the dollar value of your pipeline changed over the last several quarters?

Yeah, Paul, hi. Thanks for the question. As you know, we don't report on pipeline, but we would qualify the pipeline as healthy. And certainly growing in... and Strategic Value, which links it to the first part of your question. Systems integrators are also feeling the maturing literacy of customers. I would say combined, and we talked about it briefly, but combined with a very healthy impatience on the part of customers. It is a fair qualification. We see it enough where customers can no longer wait. They need to see the P&L impact of AI. Enough AI talk essentially and show me AI results. And so that pressure is certainly felt upon the system integrators that in turn want to be at the center of AI transformation and then turn to us and probably other companies that can deliver. But I would argue that it's not the majority that can deliver at that scale. And we're certainly one of them. And we've proven the results and we can prototype that, as I said, within days and weeks and show. And so they increasingly come to us because they they've proposed to their clients an AI transformation. They have the pressure to show results quickly to continue to expand that transformation and they need our technology to ground these models in particular that CIOs no longer want to lock themselves into any particular model and they're seeing the increasing cost of tokens and etc. So all things that Coveo helps them Manage and Deliver. So that's really how I would qualify it. And of course, it's a very positive tailwind for our business.

And just on partnerships, specifically speaking to the LLMs, you mentioned wanting to be agnostic. Is there an opportunity to go deeper with the LLMs in terms of creating partnerships with specific ones? I just mentioned this in light of one of your search competitors, did announce a deeper partnership earlier today. And so just what's your thoughts on going deeper with the LLMs?

Hi Paul, this is Laurent. Thank you for your question. So our strategy is really to focus on agnosticity and interoperability, which in plain English means that we're going to adapt what our customers want to use. Large language models have different characteristics in terms of cost, in terms of speed, in terms of reasoning capability, and it depends on the use case. where you want to use, that customers want to use. So while we may have different partnerships with different LLMs in the future, we really build our architecture to support what the customers want and optimize for scale for cost depending on the use case.

Paul, as we speak, there are 62 vendors or 63 vendors of large language models and about 460 plus models. and that number keeps increasing. So models are both commoditizing, specializing with open source and sovereign AI on the backdrop across the world. And so that creates a dynamic where If you could go back just three years ago when LLMs came out, many, many companies said, oh, we're going to train our model and et cetera. That all went away. And then some of them said, no problem. We're just going to get tokens from OpenAI through Azure credits or whatever, and we're going to dump it in our data. And you know what? It didn't work. I hate to say it, but we predicted that. We've mentioned that all along. I don't think the market was either ready or educated enough to understand it. Today, CIOs do. All companies, in our view, will run multi-models. So the idea of locking ourselves with one particular provider, we did see the Elastic deal, and we understand why. Of course, customers want to have an intelligence layer to organize their information so they can ground it into AI applications, and Elastic didn't have that. And OpenAI needs something like that underneath. But our customers, again, as Laurent said, are looking for agnosticity and interoperability. and we continue. That is 100% our strategy and we're absolutely convinced of that. And the reason we're convinced of that is we talk to CIOs every day.

Okay, thanks for that. I'll pass on.

And your next question comes from the line of David Kwan of TD Collin. Please go ahead.

Good afternoon. Just getting back to that 10 million plus ARR customer, can you comment on how much they were spending with you beforehand and how much the incremental is?

No, David, as you know, we don't provide details with any particular transaction. We did mention this eight-figure deal because we think it's a very important milestone for us, and we're really proud of that, but the intent was not to speak to one specific customer here.

Okay. Can you say, Corinne, maybe if that $10 million ARR, is you're realizing that right now, or is it going to take a while to scale up to that?

No, no, we're realizing, as you know, like a rateable model, when we report something in our bookings is because we're ready to recognize the revenue on that transaction.

Okay, that's helpful. Thanks. And then in terms of the guidance, they didn't change for fiscal 27. Is that because you guys were already baking this into the guidance already or maybe just being a bit conservative given the macro? No.

Yeah, thanks, David, for your question. I mean, look, this is the first quarter, right? So we met a couple weeks ago and the Q1 went broadly as we expected. We're happy, we're pleased with the execution. As I said in the prepared remark and on the call, the largest variable for the balance of the year remains the timing of some of the largest enterprise transactions. And, you know, given that dynamic reaffirming the guidance, we believe was the appropriate approach at this stage of the year.

I appreciate the color, Corinne. And maybe just one last question just on cap allocation. You guys didn't buy shares back this quarter despite kind of the shares trading at or near all-time lows. Can you comment on the rationale for that and how you're looking at cap allocation going forward?

Yes, thanks for your question, David. As you alluded to, indeed, we didn't buy back in Q1 by nature and seasonality of reporting. As you know, we really have a small window where we can buy back in Q1 given the blackout periods, the statutory blackout periods. Look, David, I mean, we've been active in buying back in the last years through SIB and NCIB. We just announced that we renewed our NCIB in July for the next 12 months. We maximized it to like 5.1 million shares that we can buy back. And as usual, we'll remain disciplined and thoughtful throughout our capital allocation and what drives the highest value for our shareholders on the long term.

I appreciate it. Thank you.

Your next question comes from the line of Koji Ikeda of Bank of America. Please go ahead.

Yeah. Hey, guys. Thanks so much for taking the questions. I wanted to ask maybe another question on that $10 million deal, and not on that deal, but how that deal relates to the pipeline, meaning how many other prospects do you have in your pipeline are kind of deep in discussions at that type of level? and maybe 5 million plus in ARR. And is that something you could speak to and maybe help remind us like what is the historical conversion rates of deals of this size and like sales cycles? Thank you.

Hey, Koji. I'll start by saying that first of all, this deal was an expansion. So I think for now at this stage of the company, the company growth and history, The motion is probably not to land an initial $10 million plus customer, but likely to land a seven-figure customer and grow it. over a reasonably short period to multiple seven-figure and then more. Obviously, that's not average. What's important to us here is the value, is the threshold in terms of the capability of the technology and the firm to generate that kind of value across multiple use case. It's also a demonstration of the Coveo vision of the need for a single spinal intelligence layer across data and context to ground AI as opposed to siloed AI, something that probably was not well understood or we didn't articulate it well. I think many of our customers understood it, but it's starting to materialize very, very well. Again, as Laurent said, you know a layer of software that's agnostic to data that's agnostic to models that is full MCP agnostic to agents and can be headless into NAPIs into any app and we continue to believe that in the end that's where it lands that's what CIOs want and so again back to your question Koji don't expect us at least we don't we're certainly going to take the deal if we see more but Don't expect us over the next couple of quarters to land a deal of that magnitude, but we certainly have customers that have potential to grow in that kind of zip code over time.

And if I may add, Koji, I mean, look, the five last quarters, four out of those five, we reported a seven-digit transaction, either expand or lend. These are the type of transactions we're looking to see looking forward. And you asked a couple of questions around pipeline and so on. I mean, I think the evidence I just talked about, meaning us delivering on those transactions, speaks to it. On top of it, Koji, what I would add is, either the customer growing to seven digits or lending to seven digits. The way I look about pipeline is the, you know, the texture or the brand, the potential they have with us. Like, are they looking for, you know, are these distributors that we know we can help a lot and so on? And when I look into this, I'm happy where we are.

Yeah, Koji, if I may add, I want to comment on that. I think if you think about Coveo, you know, We were obviously historically I think the company grew as you know in search you've been following the company for some time generative AI hits initially people say search is dead full reversal of events people now see search and and relevance technology as the grounding layer to control and govern AI which is is growing in in diversity initially you know if you go back a few years ago obviously our average deal size was smaller and we were probably a little more transactional. I think today, to Karen's point, we look at long-term customer margin value and margins at 80%, so it's pretty easy calculation, but that's what really matters is when you look at your CAC, your customer acquisition costs relative to the type of customer you go after, you kind of create an educated view of the long-term customer margin value. take 15% IRR, for instance, on top of your CAC. And so we're much smarter about that, I would say. We're much more intentional. We're much more focused about going after these types of verticals that have this potential to grow. And that starts before the land and obviously through the expand. So I guess that gives you a little sense, perhaps a little color on how we've evolved the business and how we manage and focus the business.

Gotcha. Thank you so much. And maybe just a follow-up here. One metric that I stare at a lot for you guys is net expansion rate. And so it sounds like with all the expansion and deals and pipeline, I mean, is it safe to say or assume that Net expansion rate, your NER is kind of stabilizing here at 102 and should expand from here. And is that is what's embedded in your assumptions and your guidance? Thank you.

Thanks, Koji. As we've discussed, the timing of large enterprise expansion can create quarter-over-quarter variability in NER. And you've heard from us, the largest expense transaction in the history closed shortly after a quarter end. So as you can imagine, if we were to take a picture today of the NER, it would look different than the picture we've taken on June 30th. The more important thing here is that we focus on strategic customer cohorts. We continue to exhibit stronger expansion characteristics. We've talked about this large transaction. We also talked about the customer expanding to B2B commerce on the prepared remark. We believe those transactions talked about the strength of our expansion motion.

Hey, Koji. We reported last quarter the top 25 customers of the company you know north is that all seven figure uh that cohort grew on north of north of 150 percent over the past three years and so you know and and again in in the strategic verticals uh where we operate work we're uh we're growing uh uh the any the ner obviously is is is above double digits so it's double digit plus and so So overall, obviously, it's a blend, but the straight answer to your point about 102 is absolutely not. We're absolutely not aligned on that, not even close.

Thank you.

And there are no further questions at this time. I will now turn the call over to Laurent Simoneau. You may continue.

Okay, great. So thanks everyone for joining us today. And I want to thank all of our shareholders for their continued support. Looking forward to updating you on our progress during our Q2 FY27 results. Thank you.

Ladies and gentlemen, this concludes today's conference call. Thank you for your participation. You may now disconnect.