Advanced RAG with Knowledge Graphs (Neo4J demo)

I recently created a demo for some prospective clients of mine, demonstrating how to use Large Language Models (LLMs) together with graph databases like Neo4J.

The two have a lot of interesting interactions, namely that you can now create knowledge graphs easier than ever before, by having AI find the graph entities and relationships from your unstructured data, rather than having to do all that manually.

On top of that, graph databases also have some advantages for Retrieval Augmented Generation (RAG) applications compared to vector search, which is currently the prevailing approach to RAG.  

Connect with me on LinkedIn: LinkedIn: johannesjolkkonen
▬▬▬▬▬▬  T I M E S T A M P S   ▬▬▬▬▬▬

0:00 - Intro
2:16 - Demo starts
2:55 - Creating graph from unstructured data
4:23 - Chatting with the knowledge graph
5:55 - Advantages of Graphs vs Vector Search