PlanetScale uses generative AI to power two Insights features. This overview explains those features and how PlanetScale ensures safety and privacy of customer data.
Postgres index recommendations use a large language model to interpret query patterns and identify potential indexes that could improve performance of those patterns. The prompt sent to the LLM includes one or more query patterns and one or more table schemas. Query patterns and table schemas include the names of tables and columns, but not any actual row data. This process runs automatically on each database each night.
Query summaries for both Postgres and Vitess use a large language model to convert a query pattern to a one-sentence description. The prompt sent to the LLM contains a query pattern. This feature is invoked only when a user clicks on the “Summarize query” button on an Insights query-details page.
All AI use is covered by PlanetScale’s existing terms of service and subprocessor list. Our LLM provider, Google Gemini, encrypts all communication in transit, does not use prompts for training, and retains prompts only long enough to screen for abuse.
We understand that not every customer wants to use AI. You can disable the LLM-based features for all the databases in your account or organization on the organization settings page.
