Hybrid Search
Hybrid search uses both exact-word search and meaning-based vector search for one question. It then joins or reranks both sets of results.
Another example
A question includes product code AX-410 and a symptom written in plain words. Exact-word search finds the code, vector search finds fixes with a similar meaning, and a written rule combines their ranks. Simply running two searches is not a complete hybrid design.
Main parts
- 01lexical results
- 02vector results
- 03fusion policy
Use it when
Use this term when a question needs both exact matches and results with a similar meaning.
Do not use it when
Do not add vector search when exact filters and word ranking already meet the measured need.
Name used in code
BM25 + vector kNN → rank fusion Before you ship
Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback.
Outcome: Use or evaluate Hybrid Search to make AI behavior measurable and tied to evidence. User context: A question includes product code AX-410 and a symptom written in plain words. Exact-word search finds the code, vector search finds fixes with a similar meaning, and a written rule combines their ranks. Simply running two searches is not a complete hybrid design. AI method or concept: Hybrid Search. Why it fits: Use this term when a question needs both exact matches and results with a similar meaning. Do not use it when: Do not add vector search when exact filters and word ranking already meet the measured need. AI requirements: Define the input and source evidence. Set model and tool permissions. Use versioned evaluation data and measures. Define failure, decline-to-answer, privacy, speed, and cost limits. Operational safeguards: Keep a clear trace and hide sensitive log data. Show users a safe fallback. Mark steps that need human review. Define how to roll back the model or prompt. Acceptance criteria: Record baseline and target measures on a versioned evaluation set. Test edge cases and hostile inputs. Verify fallback, monitoring, permissions, and rollback. Evidence and limits (evidence boundary): It is official for that source. Other platforms or teams may use the term in another way. Unknowns to confirm: Target task, model and version, evaluation owner, source data, risk limit, tool permissions, and production fallback.
Check this request
Review the current use of Hybrid Search. Definition: Hybrid search uses both exact-word search and meaning-based vector search for one question. It then joins or reranks both sets of results. Release checks: Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback. Before changing code, report the evidence you found, gaps, severity, and the smallest safe fix.