A space for learning GraphRAG with Microsoft Agent Framework and Neo4j, with a Blazor front end orchestrated by Aspire. Downloads, splits and ingests PDF data into Neo4j, and queries it using an agent workflow. Uses models from Azure Foundry as well as local Ollama models.

Advanced Retrieval-Augmented Generation (RAG) Contract Review Demo—adapting Neo4j GraphRAG for the Microsoft Agent Framework, Azure AI Foundry, and Neo4j. Integrates semantic search, knowledge graph enrichment, and agentic workflows for enterprise-scale intelligent Q&A using the latest Azure and Neo4j innovations.

AutoInsight is an intelligent assistant that converts raw CAN data into structured insights using a Neo4j-based knowledge graph and multi-agent system. It enables users to query vehicle behavior in natural language without deep protocol knowledge, making diagnostics faster, accurate, and accessible.

Advanced GraphRAG system with Neo4j, multi-agent architecture, vector similarity caching, and comprehensive evaluation framework

Agentic framework for constructing and querying hybrid knowledge graphs from structured and unstructured data with Neo4j and GraphRAG.

A chat application that answers questions about clinical trials using a GraphRAG agentic framework. It uses neo4j, streamlit, langchain, and OpenAI.