Vector search gets you 70% of the way for many enterprise RAG use cases. The other 30% — multi-hop reasoning, entity disambiguation, semantic precision over compliance language — often needs a knowledge graph alongside the vector store.
This talk compares vector-only RAG, GraphRAG (Microsoft), and hybrid retrieval architectures with concrete evaluation results, query-routing patterns, and the cost model that determines when each approach is right.
Takeaways: A side-by-side comparison of vector-only, GraphRAG, and hybrid approaches. A cost-vs-quality model for picking between them. Reference architectures for each.

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