Hi, everyone. Let's get started. First, before we do, I'm gonna point you to our normal disclaimer as we are a publicly traded company. Please only make investment decisions on current publicly shared information. Now that that's out of the way, thank you for joining us. My name is Tracy Carson, and I lead our customer marketing and advocacy efforts here at Coveo. I'm thrilled to be here, in fact, and this may be the very best part of my job, connecting our customers with experts and innovators who are just like them, sharing stories, successes, and supporting your efforts to do more and move faster with AI technologies. Before we get started, I have just two housekeeping items. First, please ask questions. Use the q and a box and chat as we go along. We'll do our best to answer those questions at the end of the webinar, but we also have some experts in the wings who, if possible, will answer in real time. Second, yes. We are recording this session, and, of course, you're gonna get a copy in your inbox usually within twenty four hours from our team. So look for that from Coveo. That's it. As you can see from the agenda today, it's a jam packed session with a focus on the latest capabilities that show how Salesforce and Coveo break down data silos, enhance relevance, and drive efficiency across your customer, employee, and commerce experiences resulting in real ROI and real business outcomes. We have a great lineup of speakers today, Balakrishnan Subramanian and Nick Swiers from Salesforce, as well as Richard Tessier from Coveo. As we go through the session, I'll let our speakers introduce themselves. With that, Richard, take it away. Thank you, Tracy. So, hi, everyone. I'm, Richard Desier. I'm a cofounder at Coveo and as VP in charge of product and, focusing on our service, line of business. So we're, all here today because we know our customer experience is a competitive differentiator in twenty twenty four, even more so than it ever was before. As a matter of fact, according to Gartner, around, eighty nine percent of companies compete primarily on the basis of customer experience. So this is a huge deal as we're all well aware of. Now the challenge is that delivering a great customer experience is quite difficult when you have different teams that manage different pieces of that customer experience within a, disconnects disconnected set of systems. Right? You have your marketing managing your websites, and you have a transactional component, commerce, and that's a different team, different system, all disconnected, product catalogs that are difficult to manage and, and actually reference alongside the rest of the content. So each team is managing a different set of goals through a siloed disconnected experience, making it very difficult to actually deliver on the expectations that your customers have today for your, company. And there's a huge impact to, those experiences, and, unfortunately, mostly for those bad experiences. So there's, like, three point seven trillion dollars of revenue at risk in twenty twenty four due to bad customer experiences according to a report from Qualtrics published in February twenty twenty four. So there is a lot of, money at stake for those experiences. Now how do you make a better situation out of this? Our belief is that introducing AI at every point of experience is going to be the critical digital transformation tool that will allow enterprises to deliver on the expectations of their customers around customer experiences. But how do you do that? What do you need in order to achieve this? A robust, platform is required to do this. Coveo has been at this for over twenty almost twenty years now, actually. So, in order to provide that AI at every point experience, you need a single platform that can bring your most relevant content in all use cases through a robust set of advanced AI models. And we've been investing heavily in those, AI models starting all the way back in two thousand, twelve when we started with some behavioral machine learning, introduced deep learning later in twenty eighteen, then started on the journey for semantic search as as far back as twenty twenty, introducing early LLMs in twenty twenty twenty one, all the way up to, relevance augmented generative answering based on the emerging generative technologies in twenty twenty three, and then twenty twenty four with, some capabilities around conversational gen AI, and, and obviously some of the work that we do in commerce as well around, additional ML models. So all of this actually comes into play. And as was evidenced on the previous slide, we've always strived to provide purpose built technology, including AI to improve the experiences of our end users journey from websites where we have a number of AI models coming into play, to commerce later on where also we've got some of the same models being, also repurposed there, but we have dedicated models applicable to only these use cases. Service as well where we bring query suggestions, relevance tuning on content, content recommendation, and, again, more recently, introducing some, capabilities based on LLMs such as smart smart snippets, case assist, which we'll see an example of later, and then, generative answering and, obviously, all of this leveraging advanced semantic encoders so that they, they are producing the kind of results that your users expect. This also drives, some, great results in workplaces. But for today's session, we will be focusing a little bit more on service and what these kinds of experiences actually look like in service and the kind of benefits that they deliver for customers in those environments. So when we look at this, we come from a perspective of the evolution of the search box. The search box is a well understood paradigm that users are accustomed to interacting with. From there, we believe and we've introduced what we call the intent box, which actually, introduces the next level of search box. It's no longer just about search keywords and no long longer just about one to two, keyword queries. We're talking about questions, suggestions, and all of this driven from one box that users are accustomed to interacting with. And what do you get once you interact with that, search box? You get obviously capabilities that are newer and that users expect such as a generated answer. Whenever the question is specific enough and you've got the right content to answer it, you wanna be able to surface that answer directly to your users, and that's what we do through generated answer along with, obviously, the all important, content lineage. So you have citations. You know where this is coming from. We don't just have generic answers. They're referenced to your enterprise content. Obviously, all of this powered by, the Coveo index. But we also understand that this cannot be the case for all questions. You will not always have an answer. So for those, we obviously believe that relevant search results are still a very good way to, present content to your users whenever you may not have an answer or the answer is not sufficient and users want to go deeper. So that's always there. You always have your, dynamic navigation capabilities as well. We know that content proliferates within enterprises, so you need a way to be able to slice and dice as a user that content. And, obviously, having this impact all the rest of your experience. So if you start interacting with, the search facets and then pointing to specific silos or content within the enterprise in there, this will impact your search results and your generated answer. Then, obviously, you can have extracts directly from those documents. Sometimes, again, making it easier to just identify that content, right right away without needing to navigate to it, and it's not generated. It's taken directly from your search results. Then, obviously, from a more conversational perspective, you have follow-up questions. You've asked the first questions. Where do you go from there? Do you have extra discovery that you can do through more, advanced questions or follow-up questions that will be presented to you? And in many of those cases, you also get to recommendations. So for your specific context within the intent that you have, what other pieces of content might be interesting for you, or which other data sources should you actually look to consult? And that can all be, found within, a search page. Well, actually, more of a unified AI relevance page where you can drive, remarkable experiences for a variety of users that you're catering to. And, again, as we said, today, we're gonna be focused more on the service use cases and how Coveo plus Salesforce, delivers great capabilities there. Talking about Coveo plus Salesforce, we'll dive a little bit more into what this means and how, our, our joint investments are actually improving the quality of experiences for, those end users. So first of all, first of all, a bit of context disregard here. So, Coveo and Salesforce have been partners for now over eleven years co innovating on great capabilities that our joint customers have been leveraging across a variety of use cases, those being against service, some of them being around commerce. We have over today a hundred and eighty, joint enterprise customers that are, leveraging our solutions. Basically, Coveo allows, Salesforce to reach out to all of that enterprise content and has been doing this for a long time. And as you'll see, we are introducing new capabilities and new ways to actually integrate within Salesforce that will make it even more valuable for our joint customers over the years to come. An example such a such a customer example is, Xero. Xero being a large, SaaS vendor. They have a, a solution where they're catering to, small and medium businesses. They have over four million subscribers to their online accounting system. This is a search page that Xero has been has had live on their website for a long time where, basically, they present content from Salesforce, knowledge into Salesforce experience cloud for their users, again, answering any questions in a self-service manner that, may come to the site. As you can see, this is a long question that a user is asking about. How do I update subscription payment details within the solution? Now getting that response forces or used to force the user to click on one of those results and then go in. Now when they rolled out, and they were one of the first, actually to roll out generative AI in production, the first at Cobell and one of the first, from as far as we can tell in terms of customers, they've actually rolled this out, the AI generative capabilities. So CRGA Coveo generative, answering capabilities on their website. And as you can see to the same question, now they get a rich answer with actually showing directly from the search results that you saw earlier and extract very easy to read, very well presented that answers that specific question directly for the end users. Rolling this out on this, on their side, they've seen major improvements to their, self-service metrics. So they've, witnessed a twenty two, percent reduction of, of cases requiring assistance, and now they are at a point where ninety six percent ninety six percent of the questions are answered by self-service help content now for their end users. These are amazing results that, Xero was very, very excited about. But Xero has, again, as I said, a SaaS solution. So they also have within their product, they are surfacing the same content, the same generated answers, Again, answering questions in the flow of work from the same system. Again, showcasing the capabilities and the power of Coveo integrations across multiple systems within, within within Xero. So, again, that content being brought to bear in different scenarios, and in this case, directly in the flow of work solving customer, customer issues without them having to navigate away from, from the system. Basically, we can see this at play in other customers as well, Dell being a great example of this. Dell has a very complex support, architecture because they sell complex product from laptops to, network switches, network routers, all the way to servers. So this is actually a page that they've put together, again, showcasing Coveo's ability to perform with a high volume of searches, complex, difficult content, and in multilingual and multi region and for multilingual and, multiregion audiences. So this looks like, again, the search page that you saw earlier, again, with your search box, now the intent box for long questions. Then you go in and you identify, obviously, that this content, yes, some of it resides, in in known systems, Salesforce knowledge bases. They also have, you know, downloads and drivers that are in different systems. They've got forums where users can help each other resolve these issues. All of this is brought together by the Kuveo index and then can be leveraged to power the generative answers that we are seeing here. Again, extracted from the most relevant results that we will see just below. Again, this is a complex question, how to update firmware utility on a specific Dell doc. So not an easy question to actually pinpoint or easy answer to pinpoint within all the content that you have. You need great relevance to be able to do that and the ability to identify those relevant passages within your content. Again, we talked earlier about sources and citations. So these are always presented, and you can, as a user, make sure that this is coming from pieces of content that you trust and that you will, that you will actually, see as the authority to providing those responses. Then we talked about query suggestions. So how do you dig deeper? Are there other related queries? Again, this can be found as you scroll down in the page. We also have recommendations for specific actions that you can take there, or specific pages that you can visit. In this particular case, the Support and Drivers webpage might be a very good place to go. Then your traditional search results. So you always have those search results available, and, and you can again dig deeper through these. This is again a well known paradigm that end users continue to relate well to and interact with in all of the, testing and rollouts of our, solutions that we've done. Now what kind of results are our customers seeing thanks to, deploying those capabilities? So the results have been massive. We already talked about the twenty percent plus increase in self-service success at zero. We have other examples at f five where they also saw double digit improvements in self-service success on their website. Again, one of those f five being a company with complex product with a lot of content sources that need to be brought to bear in, in the case of, solving, issues in self-service. Forcepoint is another great example where, actually, they're seeing case deflection improvements from introducing the introduction of, generative answering within their case submission flow. They've seen amazing results of sixty percent, increase in case deflection. And, SAP on their side have seen a massive eight million euros in, in actually, savings, from a cost to serve perspective. So their, their their loads of cases per a thousand search session has gone down significantly, again, driving that, huge improvement in, in the cost to serve. Now as we were having those discussions and those successes with our customers, we were continually discussing this with our friends at Salesforce, identifying different ways to bring this these capabilities across a wider range of capabilities within Salesforce. So and this was really tying in well with some of the investments that Salesforce was doing on their side, which has led us to a, announcements that we made a few, a few weeks ago about basically a partnership that is being extended to cover a broader set of technologies between, Salesforce and Coveo. And we have here a quote from a Salesforce, executive, Kishan Chathan, talking about the fact that Coveo helps complement Salesforce in cases where it, it helps really customers. And in this particular on this particular slide, I'd like to bring in Barca Submaran in to actually, give us a bit more context as to how Salesforce is viewing this partnership from their angle. Hey. Thank you so much, Richard, and hi, everyone. My name is Barca Subramanian. I lead the pro service cloud product management team, at Salesforce. Great to be here on this webinar. Knowledge management is an integral part of delivering high quality customer service as well as employee service. And this is even more important in the age of AI, where grounding AI on high quality knowledge is key to having more relevant, more accurate engagement, with both autonomous as well as assisted, agent for service agents that we announced, Salesforce announced at Dreamforce last month. So we are excited about our renewed partnership with Coveo to help you, you know, create those deep and powerful search and recommendation and answering experiences on our combined platforms. A few examples of which, Richard just walked through. So really the power of the Salesforce platform, knowledge management and service cloud combined with the advanced capabilities in Coveo, such as the search customization options or content ranking and filtering, high scale connectors. All of these, we believe, will really help our largest enterprise customers ingest in near real time high volumes and high sizes of of documents. So we look at these capabilities as things that extend, that complement and extend Salesforce capabilities, and really help deliver those precise answers that, the service cloud general manager, Kishan, refers to in this quote that you see on on this slide. So with that, I'll hand it back to Richard to walk you through a few more specifics here. Thank you very much, Bala. So, in terms of specifics, we are actually, again, as Bala was saying, we're looking at this from two angles in terms of how we complement each other. So there's the content aspect to it. So, again, talking about large volumes of content, Coveo indexing north of a million documents for many of those customers and being able to bring that into, again, those advanced experiences. And then we also talk about the audience, size, and diversity. Going back to the example of, Xero that actually have their, content, yes, in a more traditional, support portal, but they also have that within the application, within the flow of work. So this is more individualized than personalized experiences, and it requires the capabilities to go through advanced search customizations. And, obviously, we know that Salesforce does a wonderful job catering to, a segment of the Barca, and then we see how Coveo actually can complement this when you look at those very multiple diversified experiences, those those end product experiences as was shown by Xero, those very large and global enterprises with languages that sometimes go above the most common ones. They'll be able to power that through Coveo, such as Dell, such as what Dell is doing. And, again, the variety of content there with forums, with downloads and drivers, some content a bit more structured, a bit more unstructured. Again, flexibility and connectivity and the real time aspect of it also being very important. And then we've got some customers that have some very complex document structures because of the complexity of their products, sometimes multiple versions, identifying the right content from those multiple versions. Very important, like what we're what we've seen at Synopsys. And this is where Coveo can complement Salesforce and the joint solution becomes, that much more powerful. But now how do we bring that content and that intelligence and all of what users are actually performing as actions in Koveo, make those available to Salesforce, in, other scenarios, sometimes in assisted service, especially. So that's where the Salesforce data cloud integration comes into play. So with Coveo being available as a content, source and also as a behavioral data source, so, again, having all of those intents being available to the rest of the organization, we can basically start integrating that with Salesforce through data cloud. So feeding relevant parts of the index to data cloud so that it can perform its indexing and its vectorization capabilities to then power additional workloads, in Einstein. And, Barca was referencing, Agent Force and how important that is through, to Salesforce going forward. So the more content you can bring to bear and, again, the more also behavioral data that you can bring to bear in those Agent Force action, the better you'll actually be able to, again, perform for your end users. And that's exactly what we've started doing. And, again, here we see a little bit of an agent, force panel. And, again, I would like to bring Barca in to give us a bit more context as to how important Agent Force is going forward and how it actually relies on that, important content sources that can be coming from, various parts of the enterprise. Yeah. Absolutely. And in fact, you know, a colleague of mine at Salesforce had a very catchy phrase that he often used that data without AI is worthless, and AI without data is pointless. An agent for service agents in Salesforce really opens up a world of possibilities for creating those rich service interactions using the those autonomous AI agents. But these AI agents need good data to provide relevant and accurate responses that really, answer the question that's being asked in that engagement interaction. So Salesforce's data cloud is really a gateway to all of this data. Data from Salesforce, data across the enterprise, and data from various partner apps such as Kwayo. Agent Force provides the right structures through what we call topics, instructions, and actions. Some of that you see kind of on the left side of the screenshot here, to really open up those data sources to the AI agents. So integrating index content from Goio and all the other data sources across the enterprise into data cloud really opens up all those richer knowledge driven experiences within agent force. And from a business perspective, it improves case deflection, handle times, and time to resolution. That's really the business value of of all of this, technology that is coming together. So back to you, Richard. Thank you, Bala. This is this is just wonderful, and the timing for these things to come together is, is is so great now, that we will see traction, and we will see customers deploying those more advanced agent force agents agent force powered agents, within within the enterprise. Again, leveraging the best of what Coveo has to offer in combination with the best, that Salesforce has to offer. So in, in summary, you know, we've seen today how Salesforce and Coveo elevate the service experiences that you can provide to your users. We've already saw some great examples of self-service portals within, within a ver a variety of customers. We'll see a little bit more about case submission, in, in a few minutes as we, transition over to an example of how Coveo helps with that at Salesforce. Then we saw some assisted support, and, obviously, now the the rise and maybe the second rise, which will be, quite interesting of those conversational interfaces than that are now that much more intelligent through the use of LLMs and, again, the right set of grounding data to, grounding content and data to bring the right content, to your end users. So with this being said, we will turn it over to Nick, Swears to actually take us through an example of how Coveo is used at Salesforce in, in some of these scenarios. Great. Thank you, Rich. And and hello, everyone. My name is Nick Swiers, and I run our digital experiences team here at Salesforce within our customer success group. One thing I'm gonna do real quick before we jump into the slide is actually show you a live demo of our experience today where we use Coveo case assist. And so with that, I'm gonna go ahead and share my screen here. And so what you're seeing in front of you is our help site, again, live today in production. And, before I get started with the case assist piece, I do wanna acknowledge, right, we have Coveo implemented, pervasively across all of our digital experiences from a search standpoint. So when it comes to unified searches, which was describing earlier, that that is something that we do continue to leverage and we've seen great results from both the discoverability and, of course, customer outcome standpoint as a result of that search integration. But for today, let's jump into our case submission experience and where we've also implemented Coveo to really solve two key, customer issues as part of this experience. So what you're seeing here is essentially our standard case form. We start off by asking the customer, to describe whatever their issue or question might be. In this case, I'll put in a question here where I want to build a report, for Journey Builder, which is a feature in our Barca Cloud product. And as soon as I enter in that query, you'll notice that a product topic suggestion or recommendation is offered to me directly into the form. Now previously what customers had to do and this option is still available in case customers, don't see the right product topic, is customers would have to essentially select from our entire taxonomy of products and topics which option best matched their issue description. So in this case, I would have to scan through all the different products. And once I picked a product, then I would have to go in and essentially select a topic as well. Here we go. And so in this case, I picked advertising studio, which is actually incorrect relative to the actual issue that I entered, which of course leads to a ton of case misroutes for our support delivery team, which drives up total time to resolve and of course lowers our customer satisfaction. If I actually go back to the recommendations again powered by Coveo case assist, I see one recommendation here that seems like it matches exactly what I'm looking for as far as my issue description is concerned. And upon clicking that, I will be presented with the different channels I can engage with for assisted support. Now the other issue or I guess you could call it opportunity from a business standpoint that we were looking to solve is with this within this experience, often customers may easily have a solution available to them versus having to go through assisted support. And so you'll see down here again powered by Kaveo Case Assist, potential solutions that are derived from the index we already have set up with Kaveo today. So we're pulling knowledge articles, product documentation, even posts from the community to essentially try to address the customer's question before they have to move on to create a case. In this case, you can see relative to my issue before around Journey Builder reports, I have an article that I can click on and essentially get more information. Let's do one more example just to kinda show how the recommendation engine works, and then I'll shift back to the slide to talk about some of the impacts. So let's say I'm on contact us and it's more of a troubleshooting issue this time. So I, keep getting let's do I keep getting an error, when trying to use DataLoader, which is a common topic that we typically see come into our support teams. Again, as soon as I enter in that topic, now you're gonna see that I actually have three options for the product topic combination. But there is still one recommended here, and that's for a couple of reasons. One, the model is smart enough, right, to understand that the majority of cases that we get related to DataLoader are tied to our Sales Cloud instance. Even though Service Cloud leverages DataLoader as well, the majority of questions we get are tied to Sales Cloud. In addition, the model also knows that I, as a user, typically use Sales Cloud versus some of our other products. So it's recommending that ahead of any additional options that are close, but not quite as relevant. So in this case, I pick it. Again, similarly, I see the actual channels and then potential solutions down here. In this case, derived from the community since it's more of a specific troubleshooting topic. So just a couple of examples of where we've leveraged Coveo within the case submission experience beyond what we've already done with search to both improve the customer experience and help us as a business best meet customer needs. And what I really wanna highlight here is some of the successes that we've seen in solving these problems through, Coveo case assist. First and foremost, right, with those potential solutions that I showed at the bottom, that's saving us over twenty thousand cases per year. Right? We still wanna ensure that we're driving customer success through digital solutions. And if we can avoid a case in doing so, which will typically always take longer, that's a benefit to both the customer and us. In addition, through the Coveo case assist recommendations in the form, as you can see in the screenshot as well, fifty percent drop in case transfers. And as I alluded to at the start, that's made a huge difference in terms of the total time to resolve cases and its improved customer satisfaction as well. In fact, you can see at the bottom of the slide, we've gotten some customer feedback directly in the experience itself acknowledging just how much easier this is for customers as they're trying to submit a case. And we've seen our CSAT go from around three point o in this experience all the way up past four point o and into the four point one, four point two territory. So really happy with the success here, and we'll keep building on it as we extend the customer experience. Back over to you, Rich. Thank you, Nick. This was a great example of how, Coveo can be brought in to complement a lot of the capabilities that you will find in your Salesforce deployments and bring, the content from the enterprise right within, the the flow of work as your end users are going through, potential case submission on the site and helping them self serve as much as possible. Again, delighting them on the experience side and allowing your company to focus on those more complex, issues that, that you do have to resolve. So that, is it as far as what we have for content today. But fear not. We do have a bit of time left, and we would like now to open it up for, q and a. And, with this, I will turn it over to Tracy. Thanks, Rich. Thanks, Nick. Thanks, Barca. That was a thorough walk through, brought a lot of clarity to all of those opportunities, like you said, Rich, for for these these two technologies to work together. Bala, I'm gonna go to you first if you if you don't mind. There was a lot of exciting announcements. We've seen that reflected in the content today around Agent Force and data cloud. I wonder if you can share, you know, just four weeks later, you know, what are you most excited? What are you seeing with the enterprise customers you're talking to today, and and how are they getting started? If you could if you could share some insights, we'd appreciate it. Yeah. Absolutely. Thanks, Tracy. So, you know, what we are most excited about is really the transformation that is happening at customer service right now. So all our customers, especially our enterprise customers, they see a tremendous value unlock with, AgentForce. So AgentForce powers, as you know, an autonomous AI agent experience across multiple engagement channels and across a domain of service topics. And those service topics are really within the control of, of a customer. So what our customers are excited about is how easy it is to actually activate these agents. Unlike traditional chatbots that require sort of a tedious elaboration of, like, decision trees and so forth, AgentForce agents can be configured using just natural language topics and instructions, and, you know, use of already configured Salesforce actions. So in Salesforce, if you have flows and API calls and Apex and all of that already configured, that fits in very well into the Agentforce, architecture and the Agentforce way of working. So really, it's the better experience, it's the reduced time to value, and, you know, the truly transformational nature of these agents that our customers are most excited about. And then I think you also ask me kind of a follow on in terms of, you know, how how how should customers actually get started. My advice is really, like, to try it out today. So if you have, if a as a customer, you have Salesforce Enterprise Edition or our Unlimited Edition, you already have Agent Force, and thousand free conversations in your Salesforce org. So have your Salesforce experts configure an agent, try it out, you know, really for a kind of a ring fenced use case that you are comfortable with as a customer. Reach out to your Salesforce AE who can help answer any questions you have on how to activate this in your Barca. And, of course, you know, work with Coveo on how to integrate Coveo data and experiences into agentforce. And, Nick, I'm gonna throw it right to you. You are a customer. You're a customer of your own technology, of course. You know, none of this has happened overnight in terms of where we've gone together so far. Can you talk a little bit about this the same steps that you that you've recommended in terms of your your path to adoption and how you've gotten your team around you moving forward with these technology this technology, I'm sorry, Did they? Go ahead. Absolutely. And, as we all know, right, this AI space is burgeoning. Right? It's been emerging over the last few years. But one of the things I I've talked with my team about is we've really gone in and invested heavily and right through Coveo and of course Salesforce, companies that have been doing this for a while. Right? And so Mhmm. Despite the emergent technology that we're seeing today that we're all latching on to especially the generative side, One of my first pieces of advice is, you know, there's a lot of lessons learned and pitfalls to avoid and so forth with companies that have been in this space for a while and and to really look at companies again like Coveo and Salesforce that, have really learned from that experience and can deliver best practices and insights. That that's probably step one. From my standpoint, from my experience, especially in the customer success space, one of the first things that we did and that we continue to do and refresh every twelve to eighteen months or so is building out a journey map of the entire customer journey from the point of sale to the point of renewal. Right? And that journey should, you know, ideally repeat on a cycle, right, as customers expand their product suite and buy new products. But that journey map is critical for us because previously, we would look at that journey map to identify pain points and opportunities where we could make incremental improvements. And now with the advent of all these AI technologies that are out there, we can make step change improvements at each point in the journey much quicker than what we've been able to do in the past. And to Balas' point, right, the biggest opportunity here is or the biggest, advantage here is you can go in and test and start using this this these AI capabilities now and really figure out what works for you as a business as well as your customers. Yeah. I love that answer. And, Nick, if I could give you another shout out just because I've got you is, for anyone curious about Nick's journey map, I highly recommend you jump on the Dreamforce plus channel. Look for his session from from Dreamforce. It was an impressive, feat to get that done. But as you said, becomes that road map, and and that's something that you can go back to time and again and make these adjustments quickly with sort of that uniform belief of the team behind you as to how to how to get it done. You know, we're gonna be pressed for time. We had a lot more questions to get through. But, Rich, I thought maybe if you wanna close this out, you know, you pointed to a few great customer examples today. I'm wondering, you know, when they came to us and Salesforce and started exploring Gen AI use cases in self-service, what did they do to make a decision with us quickly? We saw some really early adopters, really leading innovators, emerge. How did they get started? I wonder if you could offer your perspective. Yeah. So, definitely. So there, obviously, you need to, start with the content as, and and I loved Balas' quote about Retail. AI, versus, data and and how it's integral, in, in actually ensuring the success. So making sure that you can get to the right content from your enterprise in order to ground those, models is, is absolutely, primordial. Looking at the security requirements that you have there, do you, do you wanna basically, and is it valuable for your company to inherit the security permissions that you have on those source systems, or is that simple enough that you can basically just feed that into a system and try and build a demo quickly? Nick was pointing out that these technologies are now more and more readily available. It's pretty easy to to roll them out, test them. And we're seeing this in all of our deployments. All of our customers are doing a significant chunk of testing, on on the generative, models they're putting out, making sure that they get the right balance of answer rate versus, versus the guardrails that are in place to make sure that the models stay within the right content and do not, start, hallucinating, which can be a challenge there. So, ultimately, these are all factors that play into your decision. And, again, I would go back to, these technologies being available and getting in touch with, both Salesforce and Coveo in order to have, have us be able to, also guide them, to identify whether the use cases that they're looking at falls more on the advanced side and really thinking about a Coveo plus Salesforce or whether, they, they have a use case that can be well, well served with, the built in capabilities. And then think about those, bigger interoperability capabilities that are now available so that if they do go to Coveo route, they can leverage that content, within agent force as well for the next steps maybe in assisted service. Yeah. Tremendous. Well, I'm afraid I have to wrap this up. I wanna thank Paula, Richard, Nick for your time today and to all of you who are able to join us. As I mentioned, we will get the recording to you, to your inbox within twenty four hours. Give us a few minutes. Also, if we didn't get to your questions, we're gonna have our team follow-up. So thank you for submitting them. Super interesting. I hope you all have a great day. I hope to see you again soon. And with that, we'll say goodbye. Take care, everyone.