Hello, everyone. It is now my turn to welcome you to Relevance three sixty. And thank you for spending your time with us today. My name is Patrick Martin, and I am the EVP, Global Customer Experience at Coveo. During the next ten minutes, we'll talk about how AI relevance is a critical capability to deliver exceptional digital customer experiences. But before we start, I have a question for all of you. Have you ever walked in your customer's shoes and actually gone through your end to end experience? What would happen if you did? What would you uncover? Would you find that your experience is fluid, connected, and relevant to your customers? Or will you discover that the experience is disjointed, siloed, and introduces friction throughout the journey? I would probably bet that it lands somewhere in the middle, which means that there surely is room for improvement to connect the journey, remove friction, and build a relevant and personalized experience. Why take action now? Why is this important? Well, according to a Qualtrics study, the impact of negative customer experiences equates to three point seven trillion dollars of revenue that is at risk globally on an annual basis. Let me say that again. Three point seven trillion dollars, that's a significant amount of pocket change. The reality is that this money is not necessarily lost. Customers will just spend it elsewhere. They'll take their business to brands that offer experiences that they expect. The data on that is clear. According to a PWC report, thirty two percent of people will stop doing business with a brand after just one bad experience, and that number goes up substantially after two negative experiences. To understand how we got to where we are today, I believe we need to take a step back and review how our customer experiences have been designed. Through time, digital experiences have evolved as new digital channels saw the light of day. And if we look ourselves in the mirror, we have historically been using self-service as a barrier between customers and ourselves. Self-service was mostly seen as a cost reduction effort, not necessarily built to deliver great customer experiences. Channels were created with a specific purpose in mind, bridging gaps in the journey. And when we put it all together, it seems like we have it all covered, having designed an experience that builds on itself. The plan was for customers to start their journey with the website and gradually progress through the channels, searching for the information they need. And only once all these channels have failed to deliver an answer would they contact the customer service team. However, customers don't act as designed. When they have an issue, they embark on a path to resolution, and the truth is they're gonna follow the path of least resistance. If you think back on your own experiences, how much time are you willing to put into resolving issues on your own before you contact support or customer service? Self-service needs to be easy or else customers will not want to self serve. The reality is that customers have the choice of how they're engaging with you and which channels they decide to leverage, whether it be digital or assisted, and you have no control over it as all of these channels are available to them, which means that this is a more realistic representation of what a real customer experience looks like. Customers who are on the resolution path are just like cars on the highway when they take any exit based on where they wanna go. And nothing is worse than taking the wrong exit. You have to find your way back to the highway in order to take the exit you initially needed to take. This highlights the importance of unifying and connecting the customer journey. What do I mean by that? Well, unification of the journey means that a customer should take the exact same experience regardless of the channel they use. If they decide to go on the documentation site for assistance, they should be presented with all relevant information, not just product documentation. The same applies for the support portal or any other digital channel for that matter. If the customer decides to go the assisted route, the agent should be armed with the same information as customers would find via the digital channels on top of having visibility into what the customer has done so far in their journey. Why is it so challenging to achieve the unification of the experience and journey? This is a tangible explanation. All the engagement channels are owned by different teams who have different budgets, different objectives, metrics, etcetera, etcetera. And to top that, these channels probably use different technology solutions, each with their native search technologies and respective knowledge repositories, which makes it almost impossible to unify the journey. As we project ourselves in the future, you can imagine that each of these channels will have an AI agent. And if the AI agent only uses the channel's respective knowledge repository with no integration or connectivity into all the other channels or applications, the customer experience will remain disjointed. To solve for the disjointed experience, you need to build your experience on top of an intelligent AI layer, and this is where AI relevance comes in. With traditional search, the technology was used to render a list of relevant documents based on the user's query. The user then had to navigate through the different list of documents, identify the most relevant ones along with the snippets of information, and stitch it all together from the different sources to finally get the answer or resolution they needed. This would sometimes require multiple different searches or navigating to different channels. We could say that with traditional search, the user was responsible for finding the solution based on the search query and results. With generative and agentic experiences, this gets completely flipped on its head. The technology has to understand the user's intent and provide the solution. It needs to search through all the available content, identify the most relevant passages, and generate the answer the user expects. This is where AI relevance takes all of its meaning. Without it, it would be almost impossible to render an experience that is tailored to the user, including a generated answer, citations, recommendations, follow-up questions, etcetera, etcetera. And this is the power of the Coveo AI Relevance Platform. It acts as the intelligence layer between your content and engagement layers. The four critical capabilities of the Coveo AI Relevance Platform are unified hybrid index, one secure source to content that refreshes in real time and vectorized. The Unified Hybrid Relevance, which is fueled by multiple ML models optimized for relevance. Unified UX Relevance, which brings semantic search, discovery, navigations, recommendations, generative answering, advice, next best questions, conversations as part of the complete user experience. And finally, the unified journey relevance, one coherent experience across the entire journey regardless of channel. So let's see what this looks like in a little bit more detail. The foundation of an AI relevance powered experience starts with the content. It is one of the most important aspects, if not the most important, to have success with generative and agentic experience. Without the content and the context layer, you have nothing to feed your AI. It's just like if I give you a Ferrari but no fuel to put in it. You end up with a beautiful car in your driveway, but it's not very useful. By indexing all enterprise content within a unified index, along with the permissions and security, you're creating a solid foundation to fuel generative and agentic experiences. The retrieval layer comes as another important part of the solution. Since the launch of chat GPT and LLMs, there's been much focus on the generative part of RAG, but many are coming to the conclusion that retrieval is the most critical capability and also the more complex. At Coveo, we refer to RAG as relevance augmented generation as retrieval is only as valuable as its ability to retrieve relevant information. Without relevance, retrieval in itself doesn't add much value. This is what the platform brings in terms of capabilities, the ability to retrieve passages ranked on semantic relevance to feed any LLM. Through these capabilities, we can achieve AI relevance, unifying the experience across the entire engagement layer regardless of channel or applications. As AI agents make their way to the experience, the platform becomes complementary, augmenting agentic orchestration. Companies who have embarked on this journey are seeing real tangible results. For example, Xero and Zoom both have improved self-service success by twenty one percent. Informatica and SAP Concur both have significant savings in their cost to serve. Forcepoint has seen a sixty percent increase in case deflection by leveraging the Coveo platform as part of their self-service experience. So let me finish by asking this simple question. Why is the unification of the experience with AI relevance important? Because it's a problem worth three point seven trillion dollars. And with that, thank you very much, and back to you, Louis.