LLM API Data Retention: What AI Teams Should Decide Before Launch

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AI systems create data: prompts, responses, metadata, embeddings, files, and logs. Retention policies decide how long that data is kept and who can access it.

Data categories

Define retention for:

  • prompt content
  • response content
  • request metadata
  • uploaded files
  • embeddings
  • evaluation examples
  • audit logs

Balance debugging and privacy

Long retention helps debugging. Short retention reduces risk. Many teams keep metadata longer than raw prompt content.

Customer controls

Enterprise customers may need deletion, export, or retention configuration.

Final thoughts

Data retention should be designed before launch. Separate metadata from content and document policies clearly.