What's New

Hello there. We built Tellius to answer hard questions with structured data. Why is revenue down? What's driving the miss? Where should we focus? We do that really well. But here's what customers kept telling us Data shows me what happened, but there's is so much context buried in the documents policies, call notes, contracts. There are two words, two workflows and there's no connection between the two. Our latest Tellius six point one release connects them. I'm really, really excited to launch three big ideas today. And now Abhishek is going to tell us more about the first big idea. Thanks, Ajay. You've always been able to analyze what's been in your database, but most of what your company knows actually lives outside of that database. It's in documents, transcripts, contracts, and call notes. Until now, you couldn't analyze it. Kaya changes all of that today. You could ask questions like how many supplier contracts allow for termination for convenience? And Kaya does not just do keyword matches, Kaya gets the exact counts, every contract categorized. You can also ask questions like what objections come up most in deals that we lost this quarter. Kaya goes through two hundred calls, analyzed and ranked with citations to the actual recordings. The same rigor that you expect from structured data can now be applied to PDFs, transcripts, and contracts. Your database and your documents are now together, and that's what it means to go beyond just rows and columns. And now handing it over to Vinod for the next big idea. Thanks, Abhishek. Good analysis requires context. Most AI tools today are stateless. Every conversation starts cold. You need to re explain your goals, your constraints, your history. It's like working with an analyst who forgets you the moment you walk away. Kaia now has a long term memory that learns continuously about your world, about your business, and about you. First, what's happening in the world? For example, if I ask the question, did the tariff announcement impact our APAC costs? Now Kai will find the date. It'll send the comparison window. It'll run the analysis, look at external events, policy changes, competitor moves, and these are all grounded automatically. Next, if you ask, what's happening in the business? For example, what did Kroger say about the private label in the last earning calls? Kyle now builds the transcripts, extracts key statements, and over time, Kyle learns about your market, your customers, your competitive landscape, building a deeper understanding of your business with every interaction. Finally, continue my northeast analysis. Kaya remembers your questions, your focus areas, the threads you have been pulling, while other AI tools reset with every session. Kaja gets smarter about your world over time. Continually learning, continually improving every answer grounded in the context that matters. Over to you, Ajay. So not everyone analyzes data at a desk. Sometimes you're in between meetings, in car, walking and thinking. You should be able to speak and think out loud with your enterprise data beyond simple transcription. So imagine pulling out your phone and and talk to it. For example, you know, what's behind the q three margin gap? No. No. Actually, wait. Is that a trend or just this quarter? Okay. Break it down by product. No. No. Hold on. Show me by customer segment first. So these are three changes of direction and Kaya follows each one of them. And this isn't transcription. Kaya tracks the thread of your thinking even when you are still figuring it out. So just talk, it keeps up. So just to sum it up, Kaya goes beyond rows and columns by analyzing documents with the same rigor as your database, remembers your context including market events, business knowledge, and your own history, continuously learning, and finally, voice that follows your thinking, not just your words. So, Tellius six point one is here. Your data, your documents, your context, one conversation. I'm really, really excited to see what you all will do with it. Thank you.