Production AI Systems Should Combine Multiple Knowledge Base Approaches
goyalshaliniuk · x · 2026-10-14
- Quick selector: vector for semantic similarity, knowledge graphs for relationships, hybrid search for meaning + exact matches, structured data for precise queries and math, document-centric for heavy documentation, hierarchical for large collections, continuously updated pipelines for changing info.
- These approaches aren't mutually exclusive — a production system can combine several, e.g., hybrid search + knowledge graph + structured data + continuous updates.
- The goal isn't the biggest knowledge base, but getting the right information from the right source at the right time.
Related event: Seven Ways to Build AI Knowledge Bases Beyond Vector Search(5 posts)→
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