But until recently, those signals were difficult to understand. Dashboards hinted at trends but missed the why. Deep dives took weeks of work from a data scientist. A product leader might want to know how a new feature landed with a unique audience type. But answering required a data scientist to conduct a detailed analysis.

“The process required deep technical expertise, and it was cutting off our curiosity,” says Molly Jackman, Head of Business Data.

We built a research assistant to unlock curiosity that scales. It combines two modes of exploration: dashboards for patterns and a conversational interface for digging deeper. You can start with a chart of trending issues, then ask follow-up questions in plain language.

We built it by blending what already worked. On one side, classifiers and charts that structured millions of tickets into product areas and themes. On the other, GPT‑5, which could summarize raw tickets and generate flexible reports in plain language. The combination gave us both speed and depth that was simple enough for anyone to use.