Spotify built an AI data assistant, Vedder, to let anyone query its 70,000+ datasets in plain English. It uses domain-specific clusters—each with selected tables, vetted question-SQL pairs, and docs—curated and maintained by experts to ensure accuracy and trust. A continuous health score and feedback loop keep clusters up to date as data and schemas evolve.

• Spotify rejected 87.5% of auto-generated example query pairs, keeping only human-vetted ones to avoid encoding bad query patterns
• Domain experts curate "clusters" (tables, vetted Q&A examples, docs) rather than dumping full schemas into the LLM, since context windows and raw schemas can't capture business nuance
• Each cluster gets a continuous health score tracking schema drift, example validity, and query reproducibility, auto-flagging maintenance tasks when things break
• User interactions feed back to cluster owners, turning experts' role from answering one-off questions into maintaining a shared context layer that scales to thousands of users