UPDATE.AI / AI Customer Success Platform

At UpdateAI, I worked at the early stages of the product, helping the team turn a large body of research into a clear, testable MVP direction for an AI platform focused on Customer Success.

UpdateAI helped account and customer success teams transform customer conversations into meeting, account, and portfolio insights. The product supported workflows such as meeting notes, prep, follow-up, risk detection, expansion opportunities, product feedback, and shared visibility across customer-facing teams. The company was later acquired by Gainsight, one of the leading platforms in Customer Success, to strengthen its Atlas agentic AI strategy.

My work focused on helping the team move from research and ideas into a concrete product strategy. Before working with me, UpdateAI had already done significant research, but the insights had not yet been translated into actionable product decisions. The challenge was to make that research pay off by defining what the MVP should be, what problem it should solve first, and how the product experience should be validated before development.

To do this, I led a one-month design sprint process adapted for early-stage product definition. A design sprint is a structured process for answering critical business questions through strategy, design, prototyping, and user testing; in this case, we expanded the methodology across a month to support deeper research synthesis, iteration, and MVP planning.

A major part of the work was transforming scattered research into a focused product direction. I helped define the MVP, created and refined the prototype, ran user tests, incorporated feedback, and tested again to validate the direction. This allowed the team to move from broad opportunity areas into a more concrete product experience with clearer priorities, stronger user value, and a realistic development path.