We can deploy a fully air-gapped AI environment with a local orchestration engine running entirely inside your organization, with no dependency (no Internet) on external cloud services.

At first glance, this appears to eliminate the risk of data exposure to third-party providers. However, many private RAG implementations introduce a critical and often overlooked security challenge: permission loss.

When documents are copied from line-of-business systems, file shares, HR platforms, accounting systems, or other repositories into a vector database, the original security permissions are frequently lost during ingestion.

The result? A user may gain access to information they were never authorized to see. For example, an entry-level employee asking about executive compensation, salary budgets, or financial forecasts could receive answers generated from confidential HR, payroll, or executive planning documents.

Building a private AI solution is relatively straightforward. Preserving document-level security and enforcing permissions at query time is the hard part.