Hybrid Search

While Retrieval-Augmented Generation (RAG) is the industry standard for reducing LLM hallucinations, its reliance on vector embeddings creates specific, predictable failure modes. This guide explores why semantic similarity fails on negation, exact identifiers, and acronyms, and how to build a more robust hybrid retrieval architecture.

Discover how to combine the reasoning power of AI agents with the precision of hybrid search to build a next-generation Agentic RAG system for enterprise applications.

A technical guide on implementing Contextual Retrieval, hybrid search, and automatic knowledge expansion to solve the context-blindness problem in RAG systems.