Replaced a 40-request analytics backlog with a 5-minute AI agent
How a natural language data agent eliminated an entire analytics queue — and gave back hours every week.
The problem
A fast-growing digital health platform had one analyst and a backlog of 40–50 analytics requests at any given time. Each request — "how many users completed the onboarding flow last week?" or "what's our D30 retention by acquisition channel?" — took a full day to answer. The data lived across 83 tables with broken attribution, inconsistent naming, and no documentation.
Founders and product managers were making decisions on gut feel because the data they needed took too long to get. The analyst was overwhelmed and couldn't focus on actual analysis.
What we built
We spent the first two weeks doing nothing but understanding the data — mapping tables, tracing how events were logged, finding where attribution broke down, and defining business logic (what counts as an 'active user'? what's a 'completed session'?). This is always the hardest part.
Then we built a natural language AI agent on top of the database. Anyone on the team could type a question in plain English and get a structured answer — with the SQL shown for transparency, the result in a table or chart, and a plain-English interpretation. No tickets, no waiting.
“The build took one week. Understanding the data took six. The hard part of AI automation is never the technology — it's translating how a business actually works into something a machine can reason about correctly.”
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