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fintech · Series B fintech

A support copilot that shipped with real evals

A retrieval-grounded support copilot taken from demo to production behind an evaluation set, cutting resolution time.

-43%
First-response time
94%
Answer accuracy

measured on eval set

1 in 3
Tickets auto-resolved

The challenge

Support volume was outpacing the team. An earlier AI prototype gave confident wrong answers and nobody trusted it enough to ship.

What we did

We built an eval set from real tickets first, then a RAG pipeline grounded in the product docs with citations, guardrails, and a clean handoff to humans. Every change was measured against the evals before release.

Stack

AnthropicLangChainVector DBsPythonTypeScript
Our support copilot went from demo to production with real evals behind it. Resolution time dropped and customers noticed.
Head of Product · Series B fintech

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