Structured Retrieval with Small Adapters

Manufacturing & Production • ~7 min read • Updated May 25, 2025

Context

Most enterprises already run capable structured stores—SQL, doc DBs, graph—before they add vector search. Full “data fabric” rewrites aren’t necessary to get hybrid retrieval working. A thin adapter layer can route queries, fuse scores, and expose confidence without blowing up your architecture.

Core Framework

  1. Mode Detection: Classify incoming queries as structured (filters, ranges, joins), semantic (conceptual, fuzzy), or hybrid. Use cheap heuristics first; graduate to a small classifier if needed.
  2. Adapter Layer: A stateless middleware that:
    • Parses query + metadata
    • Executes the right plan (SQL/Graph/Vector/Both)
    • Fuses results and returns an evidence bundle (source, scores, facets)
  3. Schema-Aware Embeddings: Generate embeddings for key fields (title, abstract, tags) and store field IDs so you can bias semantic ranking with structured facets.
  4. Score Fusion: Normalize scores (e.g., z-score or min-max), then combine with tuned weights or learning-to-rank for consistent ordering.

Recommended Actions

  1. Start Read-Only: Keep adapters off the write path until retrieval patterns stabilize.
  2. Instrument Routing: Log why the adapter chose SQL vs. vector vs. hybrid; review weekly for drift and misroutes.
  3. Expose Confidence: Return retrieval provenance, top features, and fusion weights for downstream UIs and audits.
  4. Golden Queries: Maintain a small, versioned set of real questions for regression checks on relevance and latency.

Common Pitfalls

  • Over-engineering: Building a heavy “data fabric” when a few routing rules would do.
  • Opaque ranking: No visibility into how structured filters and semantic scores were combined.
  • Ignoring schema semantics: Treating typed fields as plain text reduces precision and control.

Quick Win Checklist

  • Add a lightweight route_plan header to every query/response for observability.
  • Bias semantic ranking with 1–3 key facets (type, product, region) from your schema.
  • Benchmark hybrid vs. vector-only on goldens; tune fusion weights, then freeze.

Closing

Small adapters let you keep precision where structured stores shine and add recall where vectors excel. It’s an incremental, testable path to hybrid retrieval—no heroic refactor required.

By OneMind Strata Team

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