😭 GraphRAG is good and powerful, but the official implementation is difficult/painful to read or hack. 😊 This project provides a smaller, faster, cleaner GraphRAG, while remaining the core ...

Neo4j Aura Agent is an end-to-end platform for creating agents, connecting them to knowledge graphs, and deploying to production using low-code and autogeneration tools. Let’s dive in. You may be ...

For decades the data landscape was relatively static. Relational databases (hello, Oracle!) were the default and dominated, organizing information into familiar columns and rows. That stability eroded ...

Abstract: This paper introduces MedImgGraphRag-Corrector, a hierarchical hybrid framework that combines a specialized medical imaging dictionary with GraphRAG-enhanced knowledge inference to correct ...

What if your AI could not only retrieve information but also uncover the hidden relationships that make your data truly meaningful? Traditional vector-based retrieval methods, while effective for ...

This project is maintained again as of 2026-06. The current goal is to keep the original py2neo v3 / Neo4j 3.x example usable for learners, notebooks, and legacy projects while adding a current Neo4j ...

While retrieval-augmented generation is effective for simpler queries, advanced reasoning questions require deeper connections between information that exist across documents. They require a knowledge ...

Microsoft announced an update to GraphRAG that improves AI search engines’ ability to provide specific and comprehensive answers while using less resources. This update speeds up LLM processing and ...

Retrieval-augmented generation (RAG) allows AI systems to provide additional information and context to a large language model (LLM) when generating a response to a user query. However, traditional ...

In today’s data-driven world, efficient data retrieval has become critical for organizations striving to maintain a competitive edge. Slow retrieval processes and high operational costs are common ...