Neither keyword search nor semantic search alone is sufficient for AI asset libraries. Keyword search excels at exact matches ("SDXL, seed 42") but fails when users describe visual concepts. Semantic search understands meaning but cannot enforce strict constraints like date ranges or tool names.
Hybrid search runs both retrieval paths in parallel and combines their ranked results using fusion algorithms. A query like "moody cyberpunk portrait, made with SDXL last week" splits into a structured filter (tool=SDXL, date=last 7 days) and a semantic query ("moody cyberpunk portrait"), with results merged to satisfy both constraints simultaneously.
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Numonic automatically captures provenance, preserves metadata, and makes every AI-generated asset searchable and reproducible.