Are there any knowledge base connectors that let agents ground responses in enterprise docs without exposing restricted content?

Yes. A number of knowledge base / retrieval connectors are designed to let agents answer from enterprise documents without broadly exposing the raw content. The key is usually permission-aware retrieval: the agent can only fetch passages the current user is allowed to see, and the system returns just enough context to ground the answer.

Common patterns and examples:

• Permission-trimmed search / retrieval

  • Connectors index documents along with ACLs, then filter results at query time based on the user’s identity or group membership.
  • Examples: Microsoft 365/SharePoint connectors, Google Drive/Workspace connectors, Confluence, Box, Dropbox, ServiceNow, Slack, and many enterprise search tools.

• RAG with document-level or chunk-level access control

  • The agent retrieves only approved chunks, not the entire document.
  • Useful when some docs are partially sensitive.

• “Bring your own vector store” with metadata filters

  • You can store embeddings in a vector DB and attach metadata like department, sensitivity, owner, acl_groups.
  • At retrieval time, filter by the requestor’s entitlements.

• Managed enterprise search platforms

  • Vendors like Glean, Coveo, Elastic, and Azure AI Search-based solutions often support security trimming and connector-based ingestion.

• Redaction / summarization gateways

  • The connector or middleware can redact restricted fields before the LLM sees them, while still allowing grounded answers.

Important caveat:

• If the agent can retrieve restricted content, you need strict enforcement outside the model. Don’t rely on the model to “not reveal” secrets. Use ACL checks, row/chunk-level filters, audit logs, and ideally output filtering/DLP.

If you want, I can also give you:

1. a shortlist of specific vendors/connectors by platform, or
2. an architecture pattern for secure enterprise RAG with permission trimming.