AI agents don't just answer wrong—they act wrong. When agents hallucinate during execution, they
fabricate API parameters, invent confirmations, and make decisions based on false data. Traditional
RAG retrieval makes this worse by returning approximate matches instead of precise answers. In
this hands-on session, we'll build a travel booking agent and compare two approaches: traditional
vector search (FAISS) vs Graph-RAG (Neo4j knowledge graph) on 300 hotel FAQ documents. You'll see
how structured knowledge graphs eliminate fabricated statistics and incomplete retrieval—achieving
better accuracy on precise queries. Walk away with a working pattern you can apply to any domain
where AI agents need reliable, verifiable data retrieval. No prior graph database experience
needed.