From Questions to Queries: How to Talk to Your Graph Database With LLMs?

Learn how Memgraph is redefining graph data queries with GraphChat, an innovative AI-powered feature in Memgraph Lab. This past Community Call dives into the magic of converting natural language questions into Cypher queries and showcases how GraphChat simplifies interacting with complex graph data.

What’s in the Webinar?

• Introduction to GraphRAG. Katarina Supe, Head of Developer Experience, provides an overview of GraphRAG, the foundational technology enabling GraphChat and bridging AI with graph databases.
• Behind the scenes with GraphChat. Toni Lastre, Head of Platform, takes you through GraphChat's two-phase AI process, highlighting features that boost Cypher accuracy, manage errors seamlessly, and enhance AI-driven graph query capabilities.
• Live demo. Watch GraphChat in action as it translates Plain English into Cypher queries, demonstrating how you can interact with your graph data effortlessly.

What You’ll Learn

• How GraphRAG powers AI-driven graph solutions and why it’s critical for GraphChat.
• The technical workflow of GraphChat, including its two-phase AI process that ensures accurate and efficient query handling.
• Key features enhancing Cypher query accuracy, error management, and query execution speed.
• Practical applications of GraphChat through a live demonstration, showing how it simplifies querying graph data for developers and analysts alike.
• The future of AI and graph databases – what’s next for GraphChat and Memgraph.