#Cypher query
8 related articles
·3 min
Knowledge Graph-Enhanced RAG: Building a More Powerful Q&A System
A deep dive into the DeepLearning.AI & Neo4j course 'Knowledge Graphs for RAG' — covering core concepts, vector retrieval synergy, and hands-on SEC filing demos.
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YouTrackDB Deep Dive: Core Features an…
·3 min
YouTrackDB Deep Dive: Core Features and Use Cases of an Object-Oriented Graph Database
YouTrackDB is a general-purpose object-oriented graph database combining OOP paradigms with graph data models, supporting classes, inheritance, and polymorphism for knowledge graphs, social networks, and recommendation systems.
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·5 min
Context Graphs: The Key Technology for AI Agents to Remember and Reuse Past Decisions
Context Graphs use graph structures to store decisions, causal relationships, and outcomes, enabling AI agents to accumulate experience and reuse historical decisions without modifying model weights.
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·7 min
AI Agent Memory Layer Comparison: Mem0, Zep, Letta, and Cloudflare — Four Major Solutions Evaluated
In-depth comparison of four AI agent memory layer solutions: Mem0's extract-retrieve approach, Zep's temporal knowledge graphs, Letta's self-editing memory, and Cloudflare Durable Objects as infrastructure primitives.
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·4 min
GitHub AI Weekly: Agent Ecosystem Support Tools Explode onto the Scene
June 2026 GitHub AI trends: Agent ecosystem middleware tools surge — PM Skills, Agent Reach, Graphify, and Skill Spectre signal the Agent middleware era.
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·3 min
Andrew Ng's New Course: A Complete Guide to Enhancing RAG with Knowledge Graphs
Deep dive into Andrew Ng's Knowledge Graphs for RAG course with Neo4j. Learn how knowledge graphs overcome traditional RAG limitations to enable cross-document relationship reasoning.
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Tutorials·2 min
Building a Local Knowledge Graph RAG System with Dify + Neo4j: A Hands-On Guide
A hands-on guide to building a local knowledge graph RAG system using Dify, Neo4j, and Docker for multi-hop reasoning and secure local deployment.
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Deep Dives·3 min
CodeRAG Technical Deep Dive: Four Core Components That Help AI Truly Understand Your Codebase
Deep dive into CodeRAG's four core technologies: vector similarity search, file system tools, Code Knowledge Graph (CKG), and DeepWiki — how they work together to help AI coding assistants truly understand enterprise codebases and eliminate hallucinations.
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