Enterprise RAG, from document to governed decision.
Retrieval-Augmented Generation connects AI to relevant enterprise sources. In Artiplane it becomes a Fashion & Retail operating layer: it retrieves authorised evidence, applies process context and routes each action to the role allowed to approve it.
Definition
What is enterprise RAG?
A RAG system searches relevant content in enterprise sources and gives it to the model with the question. The answer can therefore rely on current documents, data and rules rather than the model's general knowledge alone. Enterprise use also requires identity, permissions, traceability, source freshness and quality evaluation.
Architecture
Six layers, one evidence chain.
01Sources and connectors
Sources and connectors
Documents, knowledge bases and operational systems remain identifiable as distinct sources, with provenance and update dates.
02Identity and permissions
Identity and permissions
Retrieval respects the scope of the user and Digital Worker: an answer must not expose content the requester cannot access.
03Semantic indexing
Semantic indexing
Content becomes searchable by meaning while retaining metadata for brand, market, season and process filters.
04Contextual retrieval
Contextual retrieval
Search selects evidence relevant to the question and operational moment without mixing inapplicable sources.
05Cited generation
Cited generation
The model receives the question, instructions and retrieved evidence. The answer always identifies the documents it used.
06Governed action
Governed action
When an answer proposes action, thresholds, policies and human checkpoints determine who can approve it and how it is audited.
AI governance
Reliable RAG is more than vector search.
Quality is measured across the whole chain: access, retrieval, answer and operational outcome.
Verifiable provenance
Verifiable provenance
Every piece of evidence retains source and context, allowing a person to check why it was used.
Controlled freshness
Controlled freshness
Versions and dates separate current content from superseded or not-yet-approved documents.
Evaluable answers
Evaluable answers
Relevance, source coverage, citations and outcome are observed separately rather than reduced to a generic quality impression.
Human in the loop
Human in the loop
Decisions above a threshold do not become automatic actions: they reach an authorised role with evidence, impact and rationale.
Fashion & Retail
Where vertical RAG creates operational context.
Buying and merchandising
Buying and merchandising
Combines collection guidelines, decision history, commercial calendars and demand signals.
Allocation and replenishment
Allocation and replenishment
Retrieves policies, market exceptions and logistics constraints before proposing a transfer or replenishment.
Store operations
Store operations
Brings procedures and product knowledge into store workflows with answers tied to approved sources.
Governance and compliance
Governance and compliance
Makes policies, roles, controls and logs queryable without separating explanations from the process they govern.
Evaluation
How to evaluate enterprise RAG
Evaluation should use real questions and authorised sources. Test retrieval relevance, faithfulness to evidence, citation completeness, permission compliance, latency, cost and operational outcome quality. A demonstration does not replace evaluation against the organisation's own information scope.
Start with a real decision and its sources.
Artiplane shows how data, documents, rules and approvals become a governed Fashion & Retail workflow.