RAG vs verifiable document memory: when to use each

Two layers, not one replacement

RAG (retrieval-augmented generation) excels at finding relevant passages across a large corpus using semantic similarity — popularized in production by vector databases and frameworks like LangChain. Verifiable document memory excels at proving what was captured from a specific source file at a specific time.

Most teams need both: RAG for search breadth, signed bundles for audit depth. DocImprint is not "RAG but better" — it is the proof layer that RAG pipelines lack.

When RAG alone is enough

Use vector search without cryptographic proof when:

• Stakes are low (internal brainstorming, draft summaries)
• Users can tolerate occasional hallucination
• No third party will audit the agent's sources
• Document versions change rarely and you control ingestion

Examples: internal wiki Q&A, marketing copy drafts, developer documentation search.

When you need verifiable memory

Add evidence bundles when:

• Regulators, courts, or auditors may challenge agent output
• Multi-agent handoffs must preserve provenance
• Source documents change and you must detect drift
• Customers require offline verification without your dashboard

Examples: contract clause review, SEC filing extraction, insurance claim-check, research citations. See our programmatic comparisons and legal workflow page.

Architecture pattern: capture then index

Recommended flow:

1. Capture with POST /v1/extract → receive bundle_id + manifest_sha256
2. Index verified markdown into your vector store (Pinecone, pgvector, etc.)
3. Cite with chunk_id + Merkle proof in agent responses
4. Verify offline before high-stakes actions

RAG handles recall. DocImprint handles proof. Neither replaces the other.

Cost and auth comparison

Use our x402 cost estimator to model agent spend before integrating.