Today, I'm delighted to talk to you about how AI profitizes every experience. So at a high level, one on one personalization data and AI are shaping the new digital experience economy. We all understand that consumer expectations have been forged by digital leaders because we're all consumers. We all understand these companies, Amazon, Spotify, Netflix, Wayfair, Booking dot com, etcetera. What these companies all have in common is they invested herds of developers and data scientists to essentially disrupt their industries by creating experience that are highly individualized. And what a lot of people don't know is that these companies also have the ability to control experiences so that they maximize their business outcomes, their revenue, their consumption, costs, profits, etcetera. If you think about your Netflix experience within ten millisecond, Netflix understanding the data about all other users as well as observing your behavior, can create an experience for you within ten milliseconds. You can search, you don't need to. They understand the entire repertoire, and they create a great experience. All you have to do is to navigate and press play. So all of this is designed not only to create better experiences, but to improve their business. What people expect has changed for good. We now all expect highly personalized, individualized experiences that are not only give us what we want, but that are prescriptive and coherent across all channels. Yet, ninety nine percent of companies report that this is a huge challenge, and this is a big problem because if the end user is a prospect or buyer, all that end user has to do is pop up a new window, and there you go. It impacts future revenue. If that end user is a customer, failure to create an individualized experience and and serve it negatively impacts loyalty and, obviously, revenue. And if that end user is an employee, it impacts productivity. There are two crucial things that digital leaders do, that winning enterprises do. Number one is they understand customer centricity, constantly improve it using technology. And number two, they understand how to do that while increasing efficiency. And the only way to deliver on both, in fact, is to use AI. And fundamentally, it's about two things. It's about it's about designing the experience so that you can serve a million individuals, not fifteen persona. And it's about understanding how to drive these experiences so as to drive business outcomes, not just drive the experiences to serve popular content that will convert. Only data and AI can solve that problem, especially at scale, because what companies deal with is high volume and variety of content or products. You can have fifty thousand, a hundred thousand. Some of our customers have five hundred thousand skews or millions of documents that you need to serve to a very large and diversified audience, sometimes global. Thousands to millions of users, each and every one highly individualized. The only way to do that at scale is to use AI. Otherwise, profits will erode. So what we're seeing is the emergence of a new category of software. We call them systems of intelligence. Every company has a layer of record, the cloud infrastructure, the data, the data lake, the databases, etcetera. They have systems of engagement, CRM, portals, intranets, all of that, websites. There's a new category of software that we call systems of intelligent. Every every company is engaged in digital transformation, but forget the word digital. Digital's old news. It's about transformation, and experience is at the epicenter of that transformation. While digital is old news, intelligence is not. And this is why at Coveo, we've been investing in the relevance cloud because we wanna democratize the very platform that allows every company, not just the digital leaders that hire herds of data scientists and developers, to compete in the digital experience economy. We believe twenty twenty three will be the inflection point of the AI imperative in business. We already see boards talking about it, ex the executive suite. The re main reason is is been the democratization. We've seen recently CHAD GPT. CHAD GPT is not the only application of AI in the enterprise, obviously, but it certainly has done a great job at democratizing for hundreds of millions of people the fact the simple fact that AI is powerful and is different. And that creates new consumer expectations. At the same time, companies are feeling the pressure of competing against companies that are much better equipped with AI, and that's very hard to do. So why we exist at Coveo has been precisely to accelerate the application of AI platforms within enterprises to help them solve that challenge of delivering great experiences profitably. And for more than fifteen years, we've been applying AI to some of the largest datasets in the world, working with the greatest brands in the world, perfecting a platform that uses machine learning, deep learning to personalize fully dynamically while optimizing the outcomes. Coveo Relevance Cloud is designed not only to deliver personalized interactions, but really across the journey, not within each and individual silo. So think about a journey that starts on an Adobe or a Sitecore powered website that's followed by a transactional experience on a commerce platform that then goes into a Salesforce or a portal, a Salesforce community, and then ends up in a contact center talking to an agent. How do you link it all? How do you learn from every interaction across the journey to serve the next? We're very proud that we've been recognized for the seventh year in a row as a leader by Gartner in providing the best level of personalization across all vendors, but we're interested in much more than that. We think the real power of AI is not only to personalize at scale, and we've solved that problem, but to profitize at scale. And that's why if you go on our website, if you look at some of the research that we've been doing, you're gonna hear a lot about ROI. We're changing the way that we engage with our customers along with our systems integrator partners. Historically, customers have dealt with us to deploy software. They subscribe to software as a service, and we've been known for improving intelligent search and recommendations at scale. And we've done that with hundreds of the largest global brands in the world across multiple sectors. And we've generated quite a bit of results and and we're able to compute the financial value. With our leading customers, we've worked to improve that, to drive more advanced levels of personalization, intent driven personalization, understanding behavior, prescriptive create prescriptive experiences, conversational experiences. What we're really excited about is the next generation of software and research that we're doing that will drive much superior levels of performance and profitize balanced personalization against optimization. When you think about AI, AI, the most fundamental and interesting thing about AI is that it learns. It finds the rules. You don't need to write the rules. And the more you feed AI, it's called machine learning for a reason, it continuously learn. So it's a flywheel effect. So once you've deployed Coveo, you have a data platform, an AI platform, the ability to apply AI models on top of it, and now the ability to optimize these models in order to drive better outcome. And we think that ability to profitize is the holy grail. You're gonna see Coveo teaming up with you, not as a software as a service provider, but as an outcomes as a service provider, and we're already in the field doing that with a lot of our leading customers and very excited about that. Coveo, therefore, is a subscription not to software, but to innovation. I invite you to to to inform to be informed about our research and investments, what our compounded network of clients do, and how we use that compounded effect to innovate and team up with you in achieving business and financial outcomes. Let me give you an example In commerce, what if you could increase revenue by ten percent, loyalty by thirty points, while improving margins by twenty five? You've seen us in the past year release the Coveo merchandising hub, which on the merch on the right hand side is is basically designed not so much to just deliver personalized experiences, but really to maximize business outcomes. We actually felt that was very, very important because having had our roots and such fifteen years ago, we understand more than most that actually simple search in commerce in particular can actually drive revenue and margins down contrary to the capabilities of AI, which I'll explain in a minute. And if you're interested, I'd like you to do a little test. Pop an anonymous session so that there's no cookie or anything like that, and go to staples dot com and try to find something like an office chair. Ironically, what you'll see, and this is because search engines typically serve what's most popular and what's most popular in commerce are discounted products that are that people convert a lot. So what you're gonna see is that without even knowing you, a company like Staples will show you a bunch of office chairs that they don't make any money on, that are heavily discounted. They don't even know yet whether you would buy a full price chair. And so the idea here and and and the reason is that the search engine learned that what people like are things that are popular and that are heavily discounted. But the problem on the business side is you're not gonna make any money. And what's gonna happen with the long tail of the inventory that's not shown to that end user, that's gonna stay in the warehouse and need to be discounted down the road? We thought about this problem for a decade. If you think about AI, it has the ability of dealing with multiple factors, not only conversion, which in commerce is click through rate and add to carts, but, you know, what if the product has a different gross margin? What if you have excess inventory that in fact if you don't sell today and show customers, if you don't show the catalog coverage, it's gonna stay in the warehouse and has have to be discounted? What if there's a higher return rate on product a? Despite the fact that it converts more, you know, If there's a higher return rate, that might not be a good equation, etcetera, etcetera. We at Coveo are interested in that, and we're investing heavily in research. And you as a subscriber subscribe to that future and to that research right now that we're doing with our customers. And this is why we've released the merchandising hub, and we're constantly at work to improve that. In customer service, I think especially in this day and age with the current economy, customers companies are very, very challenged to keep their customer customers happy so that they keep buying, renew, and potentially buy more because they're lower cost to sell to. But at the same time, no company right now is in a position to increase costs. AI has the power to increase customer satisfaction and NPS, create better self-service, and and and and agent assisted experiences while at the same time reducing cost cost to serve. We're gonna see a huge revolution in service. You've seen recently chat GPT. This creates an amazing opportunity for Coveo Because because the world suddenly, the worlds of intelligence search, self-service conversational, and prescriptive experiences are all converging. Consumers and customers are gonna ask for a more modern experience paradigm. And Coveo is uniquely positioned to immediately solve these GPT challenges because we have access to content in the near real time. We're highly secure. We understand sources of truth and relevance and factual, and we can deliver factuality at scale. Microsoft is not alone, by the way. There are a number of chat assistance and and and open source large language models. And in fact, Coveo has been loo using large language models in production since twenty twenty, but we started our research way before that. Some of you use smart snippets in question answering or case case classification from us in in in in your case deflection workflows and your self-service. This is powered by large language models and generative AI. The way we're gonna solve the GPT challenges is quite interesting. First of all, we don't believe the world of search will go away. We believe that question answering, delivering answers, generating answers, not links, is a is a very interesting paradigm. And so what we're gonna do is, in fact, combine the two, because one of the things you can't do as an enterprise is assemble an answer from content that wouldn't be secure. Or you've heard about hallucination from GPT. You cannot hallucinate with a customer in customer service. You need to be accurate. And you need the search channel and the conversational channel channel to deliver the exact same answer. Coveo, thanks to our infrastructure, has access to all the data, has access to all the relevance layer, and can feed generative AI with the relevant data corpus that actually will deliver consistently factuality across all conversational channel channels, and we're already at work with our customers to deliver on that. I wanna conclude by reiterating that Coveo is the AI platform company for the experience economy. We are the company that serious enterprises engage with to apply AI to the complex problem of economically efficient personalization.