In brief

What this examines

Graph-enhanced retrieval is useful when similarity cannot recover a relationship it never indexed. It is a deliberate choice for connected evidence: risk paths, impact analysis, case work, global questions, traceability, conflicts, and temporal state.

Why it matters

The graph should be evaluated as an evidence system. Identity, provenance, authorization, and time are load-bearing controls, and the application must route questions to the least complex retrieval mode that can answer them reliably.

Key ideas

  • Start with a demonstrated retrieval failure rather than a graph-first architecture.
  • Separate index-time compilation from query-time routing and answer generation.
  • Keep policy, evidence, and evaluation visible across the production pattern.
  • Treat identity, provenance, authorization, and time as first-class failure modes.
  • Define pilot hypotheses and pass conditions on the target corpus.

Start with the failure

Similarity search is effective when a question can be answered from a few relevant passages. It fails structurally when the answer depends on a chain of relationships or a property of the whole collection. The retrieval shape should follow the question shape.

Know what you are building

A useful graph compiles entities, relationships, claims, provenance, permissions, and time into evidence that can be traversed. Index-time work establishes this structure; query-time routing decides whether vector, hybrid, or graph retrieval is justified.

Where the graph earns its keep

Strong candidates include risk paths, supplier and component impact analysis, investigations that span many records, traceability across decisions, global themes, conflicting claims, and questions about how state changed over time.

Production controls

Application-level routing should keep simple questions on the simple path. Policy must constrain what can be retrieved, evidence must retain provenance, and evaluation must test both answer quality and the integrity of the connected path.

The pilot test

Pilot on a bounded corpus with representative questions. Compare retrieval modes, measure traceability and operating cost, test identity and permission failures, and stop if the graph does not materially improve the decisions users need to make.