Use case
PuppyGraph Knowledge Graph RAG Chatbot Demo
In this demo, we walk through a conversational AI interface for PuppyGraph that turns natural language questions into Cypher queries using Retrieval-Augmented Generation (RAG).We’ll explore the Northwind dataset, a classic retail dataset that models how orders move through the supply chain from suppliers to customers. Along the way, we’ll ask questions like:
- How many suppliers are in the system?
- Which suppliers are associated with the products that appear most frequently in customer orders?
- For our top supplier, how can we segment its customer base by spending habits and preferences?
Knowledge graphs add the missing context your AI assistants need. PuppyGraph makes it straightforward to create a knowledge graph from your existing data. No separate graph database, no duplicate data.
Want to try it yourself?
We've open-sourced the sample dataset, graph schema, and graph queries on GitHub, so you can recreate this demo in your own environment.
Visit GitHub Repository
