Earlier this year, Tracecast launched with the goal of making it effortless for revenue teams to understand and engage with their users. Today, I’m excited to share a new product release that advances this mission.

Tracecast launched with a focus on sales. But it quickly became clear that across the entire customer lifecycle, teams struggle to generate insights from their product analytics data. Customer success teams, for instance, report data warehouse queries being a bottleneck – because typically only BI or engineering teams have access to the data and the SQL skills to get an answer. Product marketing teams struggle to translate usage patterns into personas. Growth and sales teams report on the inefficiency of their reactive approach to data – sifting through key usage signals hours or days after they’ve occurred.

Revenue teams need a new way to understand and engage with their users. They need a solution that maintains the same analytical rigor of an in-house data analyst team, but provides the flexibility and speed that go-to-market teams demand today. The right product insight at the right time can be the difference between a customer churning and expanding. It can be the difference between a free trial signup converting to an enterprise deal or lapsing on their trial.

We’re at an inflection point in how AI can help solve this problem. Tool calling models, armed with tools like ClickHouse MCP or BigQuery MCP, have become incredible at querying large amounts of data quickly and reliably. Advances in deep research, such as LangChain’s Open Deep Research project, have unlocked new ways to ground AI analysis in first party data. Ambient agent architectures have introduced ways to trigger agents from real world events – perfect for responding to a product usage signal, for instance. Combining these themes, it becomes clear how an agent can be constructed that analyzes product usage data orders of magnitude faster, and just as reliably, as the status quo. And that is exactly the intention of Tracecast’s newest release.

Meet Tracecast, the AI product analyst. Tracecast combines the three themes described above – database tool calling, state of the art deep research, and an event driven agent architecture – as a service for go-to-market teams. Tracecast connects to your data, and empowers revenue teams by giving them direct control over product usage insights.

Tracecast handles the complexity of running an ambient product analyst for you. It runs automated research tasks and writes high quality, detailed research reports grounded in your product data. You can ask questions and assign long running tasks – similar to how you’d engage with a data analyst on your team.

Tracecast’s new release is available today. Visit tracecast.co to learn more, demo the product, and book a call.

Malachy Donovan, Founder