Private AI Knowledge Assistants: User Permissions and Confidential Documents

Map users to document groups

Identify departments, project teams and customer boundaries. Record the source of each permission and how quickly access removal must take effect. A document copied into a search index still needs the original access restrictions. Decide how contractors, shared accounts and staff transfers will be handled before loading confidential content.

Apply access checks during retrieval

Authenticate the user and filter eligible content before it reaches the model. Hiding a source link after an answer is generated does not remove a disclosure. Keep customer or project identifiers attached to indexed content. Test indirect questions that might combine restricted facts from several documents.

Review the complete data path

Document where files, embeddings, prompts, outputs and backups are stored, and which providers process them. Review retention and deletion behaviour rather than assuming a private network covers every copy. Limit administrator access, protect credentials and define incident ownership. Hosting choices should follow the actual data and operational requirements.

Prove isolation with negative tests

Test users who should be denied, recently removed members and documents with changed permissions. Include attempts to persuade the assistant to reveal hidden text or ignore rules. Review logs for both useful audit coverage and unnecessary content capture. Repeat access tests whenever indexing or identity integrations change.

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