Vector search alone gets you 70% of the way for many enterprise RAG use cases. The remaining 30% — multi-hop reasoning, entity disambiguation, semantic precision — often requires a knowledge graph alongside the vector store.
This talk shows when hybrid retrieval is worth the engineering and operational cost, with reference architectures, query-routing patterns, and evaluation criteria for picking between vector-only, graph-only, and hybrid approaches.
Takeaways: A decision framework for retrieval architecture. Query-routing patterns for hybrid systems. Evaluation criteria that surface when the graph pays off.

Preferred length: 30 min.
Audience: AI engineers, data architects, RAG practitioners.
Level: Intermediate.
First public delivery: 2026.