Neo4j blog

Agentic AI

The knowledge layer for enterprise AI

A manifesto for context-rich enterprise AI

Chart of the knowledge layer comprising ontologies, data, and memory

Independent study: GraphRAG makes AI agents 80% more truthful

Illustration representing a context graph for AI agent memory

Agentic AI

What is a context graph?

Welcome, GraphAware

Featured voices

Emil Eifrem

CEO & Founder, Neo4j

See all articles

Sudhir Hasbe

Chief Product Officer, Neo4j

See all articles

Philip Rathle

Chief Technology Officer, Neo4j

See all articles

Most recent

Clustering large graphs with CLARANS

JSON-based agents with Ollama & LangChain

Developer

PyNeoInstance: A user-friendly Python library for Neo4j

Using LangChain and Neo4j to process YouTube playlists and perform Q&A flow

An extremely simple but effective way to improve search over text embeddings

Slow Cypher statements and how to fix them

Object mapping in the Neo4j driver for .NET

A GenAI-powered song finder in four lines of code

LangChain v0.1 – updating GraphAcademy Neo4j & LLM courses

Divya Venkatraman

Graph database

This week in Neo4j: Knowledge graphs, NeoDash, automation, web analysis and more

Unlocking DAGs in Neo4j: From basics to critical path analysis

Unlocking DAGs in Neo4j: From basics to critical path analysis

YouTube transcripts into knowledge graphs for RAG applications