Alison, welcome. Tell us, who you are, who are you representing here today, your role, and and the role of your team. Yes. Thank you for having us, Priscilla. I'm Alison Brotman, and I lead customer experience intelligence at UKG. My team designs and scales the end to end customer journey. And if you haven't heard of us, UKG is a workforce operating platform that combines deep workforce insights with people first AI to help organizations build trust, drive productivity, and make smarter decisions about their people. So my team, we really operate at the intersection of experience strategy, AI innovation, knowledge management, and customer intelligence. Ultimately, our goal is really simple. Make it effortless for customers to get what they need quickly and accurately at every stage of their journey with UKG. And what I love about that story is that you didn't just launch, a chatbot. Right? You modernized voice and digital support at an enterprise scale, and you did it responsibly. And that's what we believe is real innovation. But let's start at the beginning and set some context, Alison. Like, have always been early adopters of AI. So what did your customer experience look like before this? So we were already on a strong AI maturity journey. We had successful self-service and agent assist capabilities in place using Coveo, and we knew that relevance was a core strength for us. We had prioritized knowledge management. And, you know, I think we knew that voice was really that next frontier. And let me tell you, it's a very different challenge. So traditional IVRs break down quickly when customers ask open ended, unscripted questions. And as you can imagine, in HR and payroll scenarios, those questions can be nuanced and high stakes. And customers don't wanna navigate menus. You know, they just want a clear, accurate answer. And at the same time, we really needed to scale without simply adding headcount. So we wanted to increase automation responsibly, without sacrificing trust of our customers, and without introducing the risk of hallucinated AI responses. So the problem that we were solving was, you know, how do we modernize our voice and digital support at enterprise scale and do it well? Yeah. And what stands out to me, is your philosophy. Right? The relevance before generation, where you started and then where you went after. And you chose to pair a conversational voice platform with Coveo's Passage Retrieval API, So every voice answer is grounded is in ranked, permission aware knowledge from your, you know, sixty thousand plus documents. Why was that architectural decision so critical for UKG? Yeah. You're right. We have over sixty thousand pieces of content in our knowledge ecosystem. It's complex. It's permission aware content, and accuracy matters for the reasons we've just talked about. We didn't want an LLM generating answers based on probability alone. We really wanted every response grounded and ranked trusted passages from our enterprise knowledge base. And Coveo's Passage Retrieval API allows us to receive the most relevant snippet in sub second time. And that's a huge distinction, especially in voice. In voice, you don't want a list of links or a full document. You want the right sentence. You want the exact right answer. And there was certainly pressure to use native tools or more bundled solutions, but we knew that our knowledge environment was far too complex and trust was just too important to compromise on retrieval quality or security trimming. So we think about relevance being the control plane and generation is that layer on top. So relevance before generation. Yeah. Indeed. Very good. So let's talk about the customer experience. What has changed for your customers compared to the legacy experiences? You know, what's changed for your agent as well as your customers? Yeah. The biggest shift is that the interactions feel really purposeful instead of procedural. So for customers, the experience is no longer about navigating a system. It's about getting an answer. They can ask a question naturally, go a level deeper if they want to, and then actually move forward without friction. Whether they come to us via the web or via voice, there's no menu hopping, no guessing which option applies, no hunting through documentation. I think one of our customers said it best. They can now ask a question, drill deeper if they want to, and then move forward confidently without opening a case, and it's a huge productivity unlock for our customers. For our support team, the change is just as meaningful. They're spending far less time on repetitive, low complexity requests and more time on issues where the human expertise really matters. And then when something does escalate, they're not starting from scratch. So the full context is already there for them, which means faster resolution, less frustration, and more satisfying work overall. So it's not just more efficient. It feels more modern, more intelligent, and quite frankly, human. Yeah. And I think one one thing I deeply respect about, you know, UKG's story and approach is that, you know, many people are chasing that AI hype, and that's not where you where you went, and really the story that you're telling doesn't resonate with that. But why is governance so central to that scalability of AI in such a responsible manner at UKG? So in order in enterprise service, especially in HR and payroll, trust is everything. And one of the things I'm most proud of is how disciplined we were from the very beginning. So anyone who's interacted with AI knows it can look impressive on the surface, but we didn't just accept looks good. We really wanted to pressure test it. So we ran proofs of concepts with multiple vendors and had subject matter experts review hundreds of responses for their accuracy before we ever moved to a pilot. And then we piloted it. We were really intentional getting twelve hundred customers to participate with us in this pilot. And we gathered feedback from them. We iterated for months before going into full production. AI and HR and payroll, it can't just be impressive. It has to be right. And that's why governance isn't an afterthought for us. It has to be foundational. So I like to think our approach was deliberate, validated, and measured, and I believe that discipline is why this is working at an enterprise scale. Wow, it really does and provides some advice for everybody as well. So what's next on the roadmap for you? We've proven the model in voice and digital support, but we feel like this is really just the beginning. So next, we're expanding our scale and coverage across new digital touch points and use cases while we continue to refine based on the customer feedback and interaction data that we're gathering. As we expand, the core principles will remain the same. You know, start with relevance, build your retrieval layer first, make sure your knowledge is permission aware and high quality, and then layer that generation responsibly on top. Love it. Very good. I mean, those are core values that I I agree you should keep repeating for sure. What is the one thing that you would tell someone who's starting or scaling with AI today? That's a great question. I would ask them to think about it differently. Instead of thinking about how do we add AI, I would ask, how do we make our answers more accurate, more trustworthy, and more scalable? I think AI could be really powerful, but relevance is what makes it reliable for an enterprise. So, Alison, what UKG has done is really a blueprint for modern enterprise AI in service in a landscape that is very rapidly changing. Right? So thank you so much for sharing your journey and the story and the story of UKG and taking it very responsibly. It's very much appreciated. Thank you. We really value our partnership with Coveo and the opportunity to share our journey, so thank you.