Documentary RAG and Data Security: What you need to know

# AI and Data Security: secure RAG in practice Retrieval-Augmented Generation (RAG) unlocks powerful knowledge discovery by combining search over your documents with a generative layer that composes human-friendly answers. But when that data is corporate and sensitive, security and governance must come first. ## Core principles we follow - Least privilege: the system respects Microsoft 365 permissions so a user only gets answers sourced from documents they can already access. - Data residency: index content and run optional processing within European datacenters (Azure France Central) on request. - No model training on customer data: we do not train or fine-tune public models on customer documents unless explicitly contracted and isolated. - Auditable pipelines: every query and source reference is logged for traceability and compliance. ## Architecture overview 1. Connector layer authenticates with Microsoft Graph and streams documents metadata (and optionally text) into a secure indexing pipeline. 2. An index (vector + metadata) is stored in a secure store with encryption at rest. 3. A query service uses the requesting user's identity to enforce permission filters when retrieving candidate passages. 4. The generative layer composes answers from the filtered passages and returns citations to the original sources. ## Threat model & mitigations - Unauthorized access: mitigated by enforcing Microsoft 365 ACLs and short‑lived service credentials. - Data exfiltration: minimized by returning short excerpts with citation links instead of full documents and by rate limiting plus monitoring. - Model hallucination: reduced by grounding answers in retrieved passages and exposing source citations so users can verify claims. ## GDPR and legal considerations Hosting within the EU, signing Data Processing Agreements (DPAs), and providing deletion/portability mechanisms keeps deployments compliant. We also provide configuration to avoid storing PII in logs if required. ## Real-world checklist for deployment 1. Define scope (which drives/folders to index). 2. Confirm data residency and DPA requirements. 3. Configure Microsoft 365 app consent and least-privilege scopes. 4. Run pilot with audit logging enabled and review sample answers. 5. Tune retrieval and citation thresholds to balance precision/recall. ## Conclusion RAG can be deployed securely and responsibly when permission enforcement, hosting and audit controls are in place. If you want, we can run a short security review and privacy impact assessment for your Microsoft 365 tenant.