How large a document set does RAG handle well?

Hundreds of thousands of pages is routine with the right chunking and retrieval design. Quality degrades from poor structure and stale content long before it degrades from volume.

Where should the vector index live?

Alongside your existing data-residency commitments. We deploy in-region indexes for clients with UAE or Saudi residency requirements.

How large a document set does RAG handle well?

Hundreds of thousands of pages is routine with the right chunking and retrieval design. Quality degrades from poor structure and stale content long before it degrades from volume.

Where should the vector index live?

Alongside your existing data-residency commitments. We deploy in-region indexes for clients with UAE or Saudi residency requirements.

AI Engineering

8 min read Priya Nair, Principal AI Engineer

RAG that survives an audit: sourcing, citations and retention

Retrieval-augmented generation becomes enterprise-grade when every answer is traceable to a specific document version, filtered by the asking user's permissions, and retained according to policy.

Published 21 April 2026 · Updated 28 June 2026

RAGLLMComplianceDocument Intelligence

Key takeaways

Index document versions, not documents; answers must cite the version they used.
Apply access control at retrieval time, never at display time.
Chunking strategy affects answer quality more than model choice in most deployments.
Measure groundedness continuously, not once at launch.

Lineage beats cleverness

Store source, version, effective date and owner alongside every chunk. When a policy changes, superseded content must stop being retrievable, and previous answers must remain explainable against the version that produced them.

Permission-aware retrieval

Filter the candidate set by the requesting user's entitlements before ranking. Post-filtering leaks information through summaries and is not defensible in a review.

Chunking and evaluation

Structure-aware chunking that respects headings, tables and clause boundaries typically improves answer quality more than upgrading the model. Validate with a groundedness score on a fixed question set and track it release over release.

Preserve tables as structured content rather than flattened text
Keep clause and section identifiers in metadata for citation
Re-embed on document change, not on a fixed schedule alone

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