AI Solution Architecture

Docs

View source

RAG Data Contract

Use this template before building ingestion or retrieval. RAG failures are usually data architecture failures, not only prompt failures.

Scope

Product/workflow:

Users:

Retrieval use cases:

Out-of-scope data:

Document Contract

FieldDescriptionRequiredExample
document_idStable source document IDYes
source_uriSource system/pathYes
ownerBusiness or system ownerYes
access_policyACL/role/tenant metadataYes
versionSource document versionYes
effective_dateDate content becomes validOptional
retention_policyDeletion/archival ruleYes

Chunk Contract

FieldDescriptionRequiredExample
chunk_idStable chunk IDYes
document_idParent document IDYes
chunk_textText sent to embedding modelYes
chunk_orderPosition in documentYes
section_titleHeading or logical sectionOptional
token_countToken lengthYes
embedding_modelEmbedding model IDYes
embedding_versionEmbedding config versionYes

Query Contract

ElementDecision
Query rewrite policy
Top-k
Hybrid search
Metadata filters
Reranker
Citation format
Low-confidence threshold
Access control enforcement point

Lifecycle

flowchart LR Source[Source system] --> Extract[Extract] Extract --> Normalize[Normalize and classify] Normalize --> Chunk[Chunk and enrich metadata] Chunk --> Embed[Embed] Embed --> Index[Index in vector DB] Index --> Query[Retrieve] Query --> Cite[Cite and evaluate] Source --> Delete[Deletion signal] Delete --> Tombstone[Tombstone and purge]

Retrieval Evaluation

TestPurposePass Criteria
Golden query setMeasures retrieval relevance
Citation auditChecks evidence is cited correctly
Permission testEnsures user sees only allowed chunks
Freshness testEnsures updates and deletes propagate
Drift testDetects embedding/chunking regression

Readiness Checklist