Webinar
Vector Search in Memgraph: Turn Unstructured Text into Queryable Knowledge
Unstructured text is everywhere. But how do you make sense of it?
In this demo, Josip Mrden, Head of Solutions at Memgraph, showcases how he built a Q&A and quiz generation app using Wikipedia as a data source. And he built it all in just one weekend!
Using a powerful combination of a graph database, semantic vector search, and LLMs, Josip created an app that lets you chat with your data and generate context-aware quizzes with answers. This innovative approach helps you turn unstructured text into truly queryable knowledge.
What You’ll Learn
In this demo, Josip Mrden, Head of Solutions at Memgraph, showcases how he built a Q&A and quiz generation app using Wikipedia as a data source. And he built it all in just one weekend!
Using a powerful combination of a graph database, semantic vector search, and LLMs, Josip created an app that lets you chat with your data and generate context-aware quizzes with answers. This innovative approach helps you turn unstructured text into truly queryable knowledge.
What You’ll Learn
- Why Memgraph is ideal for combining structured and unstructured knowledge.
- How to build smarter, grounded LLM applications without needing a separate vector database.
- How to use Cypher to expand and traverse retrieved knowledge semantically.
