Camille Rousseau

Internal data analyst chat

Claude agent that translates plain-English questions into SQL against a Postgres warehouse, runs query, returns formatted answer with chart.

Adopted by ops team — 200+ queries/week, no SQL training needed.
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Problem

Ops team blocked on every metric question — had to ping data eng, wait, get a CSV back, then try to read it. Decisions slowed by days.

Users

Internal — 22-person ops team, finance, founder

Key flow

  1. 1User asks plain-English question
  2. 2Agent shows SQL + result + chart, with "explain this answer" toggle
  3. 3User saves the query if useful, or refines and re-runs

What I built

  • Read-only role to the warehouse with row-count and timeout guards
  • Claude generates SQL with schema-aware few-shot examples
  • Auto-charting via Vega-Lite when result looks time-series
  • Saved-query library — non-SQL users can re-run named answers

Limits

  • Read-only — never writes, drops, or updates
  • Joins capped at 4 tables to keep latency under 5s
Internal data analyst chat

AI tools used

  • Claude
  • Anthropic API
  • Supabase