LLM + Graph Database for RAG

LLMs can provide answers that sound realistic to almost any question, even if those answers are entirely made up. To anchor an LLM in reality and mitigate the risk of generating false information or unauthorized access to sensitive data, try incorporating a Knowledge Graph. This prevents the model from producing inaccurate responses and ensures a more reliable and secure outcome.
This presentation will show you the benefits of Graph Databases over regular databases and how to use GenAI with RAG to eliminate hallucinations, enforce security, and improve accuracy. We will also discuss why a vector index plus Knowledge Graph provides better, smarter, faster results than a pure vector database.

Andreas Kollegger is a technological humanist. Starting at NASA, Andreas designed systems from scratch to support science missions. Then in Zambia, he built medical informatics systems to apply technology for social good. Now with Neo4j, he is democratizing graph databases to validate and extend our intuitions about how the world works. Everything is connected.