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OpenAI’s data productivity team built Kepler, an AI agent that understands their data platform context and writes iterative SQL to answer complex data questions. It handles table discovery, query refinement, follow-up prompts and even visualizations, cutting analysis time and reducing errors.
- OpenAI built Kepler, an internal AI agent that writes iterative SQL to answer data questions across 70,000 datasets and 600 petabytes daily, deployed via Slack, IDEs, or web UI
- It doesn't just query once—it discovers tables, refines CTEs, verifies numbers against dashboards/Notion, and proposes hypotheses (e.g., duplicate logging) for anomalies like a WAU spike
- Memory for self-learning plus rigorous evals let it improve over time without regressing
- Rolled out to 80% of the company, turning multi-engineer, multi-hour investigations into minutes