Original guideAI Architecture

Enterprise RAG: What Retrieval-Augmented Generation Needs to Work

RAG does not automatically make an answer accurate. It creates a retrieval and evidence system whose content, permissions, evaluation, and operations determine trust.

Treat content as a governed product

Identify authoritative sources, owners, update processes, retention rules, and access classifications. Remove duplicates and obsolete documents, preserve useful structure, and attach metadata such as business unit, jurisdiction, effective date, audience, and document type. Retrieval cannot repair contradictory source material by itself.

Enforce permissions before results reach the model. Index-level separation, identity-aware filtering, and source authorization should prevent a user from retrieving content they cannot access directly.

Evaluate retrieval and generation separately

Build a representative question set with expected sources and acceptable answers. Measure whether the correct evidence is retrieved, whether irrelevant evidence appears, and whether the model answers faithfully from that evidence. A fluent final answer can hide retrieval failure.

Test acronyms, ambiguous terms, tables, scanned files, versioned policies, multilingual content, and questions whose correct response is that the source does not contain an answer. Citations should point to accessible, specific evidence.

Operate for freshness and feedback

Monitor ingestion failures, permission changes, stale content, retrieval quality, unsupported claims, user corrections, latency, and cost. Make source owners responsible for content health and provide a way for users to report inaccurate or outdated answers.

Use retrieval when current or proprietary evidence matters. For stable tasks that do not require enterprise knowledge, simpler prompts or workflow logic may be more reliable and economical. Architecture should follow the problem.

Leadership checklist

  • Assign owners and freshness rules to source collections.
  • Enforce source permissions before retrieval.
  • Evaluate retrieval, grounded generation, and abstention separately.
  • Monitor ingestion, staleness, corrections, citations, latency, and cost.