neo4j.com Open in urlscan Pro
3.171.139.82  Public Scan

Form analysis
0 forms found in the DOM

Text Content

This website uses cookies

We use cookies to offer you a better browsing experience, analyze site traffic,
personalize content and serve targeted ads.  Learn about how we use cookies and
how you can control them in Cookie Settings. By using our site. you consent to
our use of cookies. 

Accept CookiesUse necessary cookies only

Labs
Docs
Neo4j DBMS
 * Getting Started
 * Operations
 * Migration and Upgrade
 * Status Codes
 * Java Reference
 * Kerberos Add-on

Neo4j Aura
 * Neo4j Aura
 * Neo4j AuraDB
 * Neo4j AuraDS

Neo4j Tools
 * Neo4j Bloom
 * Neo4j Browser
 * Neo4j Data Importer
 * Neo4j Desktop
 * Neo4j Ops Manager

Neo4j Graph Data Science
 * Neo4j Graph Data Science Library
 * Neo4j Graph Data Science Client

Cypher Query Language
 * Cypher
 * Cypher Cheat Sheet
 * APOC Library

Generative AI
 * Embeddings and vector indexes tutorial
 * GenAI integrations
 * Vector search indexes

Create applications
 * Python Driver
 * Go Driver
 * Java Driver
 * JavaScript Driver
 * .Net Driver
 * Neo4j GraphQL Library
 * Neo4j Visualization Library
 * OGM Library
 * Spring Data Neo4j
 * HTTP API
 * Neo4j Query API

Connect data sources
 * Neo4j Connector for Apache Spark
 * Neo4j Connector for Apache Kafka
 * Change Data Capture (CDC)
 * BigQuery to Neo4j
 * Google Cloud to Neo4j

Labs
GenAI Ecosystem
 * LLM Knowledge Graph Builder
 * Vector Index & Search
 * LangChain
 * LangChain.js
 * LlamaIndex
 * Haystack
 * DSPy

Developer Tools
 * APOC Extended
 * Aura CLI
 * arrows.app
 * Cypher Workbench
 * ETL Tool
 * NeoDash

Frameworks & Integrations
 * Needle Starter Kit
 * Neo4j Plugin for Liquibase
 * Neo4j Migrations
 * neomodel

RDF & Linked Data
 * Neosemantics (Java)
 * RDFLib-Neo4j (Python)


Get Help
Community Forum
Discord Chat
Knowledge Base
Neo4j Developer Blog
Neo4j Videos
GraphAcademy
Beginners Courses
 * Neo4j Fundamentals
 * Cypher Fundamentals
 * Importing Data Fundamentals
 * Importing CSV Data
 * Graph Data Modeling

Data Scientist Courses
 * Into to Graph Data Science
 * Graph Data Science Fundamentals
 * Path Finding

Generative AI Courses
 * Neo4j & LLM Fundamentals
 * Vector Indexes & Unstructured Data
 * Build a Chatbot with Python
 * Build a Chatbot with TypeScript

Neo4j Certification
 * Neo4j Certified Professional
 * Neo4j Graph Data Science Certification

Get Started Free
Search
Skip to content
Neo4j Labs
 * * Labs Home
 * * GenAI Ecosystem
     * Example Projects
       * LLM Graph Builder
         * Features
         * Deployment
       * GraphRAG Demo
       * NeoConverse
       * GenAI Stack
     * Neo4j GenAI Features
       * Vector Index and Search
       * APOC GenAI
     * Cloud Examples
       * AWS Bedrock
       * Microsoft Azure OpenAI
       * Google Cloud Vertex AI
     * GenAI Frameworks
       * LangChain
       * LangChainJS
       * LlamaIndex
       * SpringAI
       * LangChain4j
       * Haystack
       * Semantic Kernel
       * DSPy
 * * APOC
     * Documentation
       * 5 - Core
       * 5 - Extended
       * 4.4
       * 4.3
 * * Arrows
     * Launch Arrows
 * * Aura CLI
     * Documentation
       * 1.0
 * * Cypher Workbench
     * Documentation
       * Cypher Workbench Documentation
 * * Keymaker
     * Documentation
       * Keymaker Documentation
 * * Neo4j ETL Tool
     * Documentation
 * * Halin
     * Documentation
 * * Liquibase
     * Start using Liquibase
 * * Neo4j-Helm
     * Documentation
 * * Neo4j-Migrations
     * Documentation
       * 2.0 (snapshot)
 * * Needle Starter Kit
     * Documentation
       * 2.0
 * * NeoDash
     * Documentation
       * 2.1
       * 2.2
       * 2.3
       * 2.4
 * * neomodel
     * Documentation
       * 4.0.10
 * * Neosemantics
     * Introduction
     * Installation
     * Getting Started
     * How To Guide
     * Troubleshooting
     * Graph App
     * Acknowledgements
     * Documentation
       * 4.3 (Current)
       * 4.2
       * 4.1
       * 4.0
       * 3.5
 * * RDFlib-Neo4j
     * Documentation
       * 1.0
       * 1.1
 * * Neo4j-Spatial
     * Documentation

Is this page helpful?

 * Neo4j Labs
 * GenAI Ecosystem

Edit this Page


GENAI ECOSYSTEM

Knowledge graphs bring more accurate responses, rich context, and explainability
to each generative AI model interaction. By combining knowledge graphs with
native vector search, you get the best of both worlds with Graph RAG (Retrieval
Augmented Generation).

Language models also can be used to extract entities and their relationships
from unstructured text to build up and enrich knowledge graphs.


HOW TO GET STARTED

 1. For an high level overview, have a look at neo4j.com/genai

 2. Use the LLM-Knowledge Graph Builder to turn your own documents into a
    knowledge graph

 3. If you want to learn more take one of the GenAI GraphAcademy courses

 4. Pick your GenAI framework of choice and start building your own GenAI
    applications with Neo4j


GRAPHACADEMY COURSES

If you want to learn how LLMs and Knowledge Graphs combine to improve GenAI
applications, check out the Neo4j & LLM courses on GraphAcademy.




GENAI ECOSYSTEM

The Neo4j GenAI Ecosystem is a collection of tools and integrations that make it
easy to use LLMs with Neo4j.


GRAPHRAG

GraphRAG combines an ingestion process that extracts entities and relationships
from unstructured text and further uses graph algorithms for enrichment and
summarization. The retrieval step then uses the knowledge graph in combination
with vector search to navigate to more relevant information than just the
initial text chunks.

 * The GraphRAG Manifesto

 * DeepLearning AI Knowledge Graph Course

 * GraphRAG Field Guide: Navigating the World of Advanced RAG Patterns

 * GraphRAG Pattern Catalogue

 * GraphRAG Discord

 * (free) Knowledge Graph Book

 * Implementing GraphRAG with Neo4j, GDS and LangChain

 * Microsoft’s GraphRAG project

 * Deploy Neo4j-LangChain GraphRAG w/ GCP Vertex AI Reasoning Engine


GRAPHRAG ECOSYSTEM TOOLS

In Neo4j Labs we built a number of tools, to demonstrate the power of combining
graphs with LLMs. All these tools are open source, you can use and contribute to
them or learn and build your own.

 * LLM Knowledge Graph Builder

 * NeoConverse multi-dataset query, chat, visualization

 * GraphRAG (Retrieval Augmented Generation) Demo

 * GenAI Stack (with Docker, Ollama, Neo4j, and LangChain)


CLOUD EXAMPLES

Neo4j has worked with the main cloud providers to create GenAI integrations and
examples on their platforms.

 * AWS Demo

 * Microsoft Azure Demo

 * Google Cloud Demo


NEO4J GENAI FEATURES

Neo4j added a number of features to make it easier to build GenAI applications
and integrate LLMs with knowledge graphs.

 * Vector Index & Search

 * APOC GenAI Procedures


GENAI FRAMEWORKS

Neo4j and our community have contributed integrations to many of these
frameworks. You can find overviews of these integrations in the pages of this
section, as well as code examples, tutorials and more.

 * LangChain (Python)

 * LangChainJS

 * LLamaIndex

 * Spring AI

 * LangChain4j

 * Haystack

 * Semantic Kernel

 * DSPy


HIGHLIGHTED ARTICLES

 * Neo4j Developer Blog: Large Language Models

 * Tomaz Bratanic’s Medium Blog

 * Joshua Yu’s Medium Blog


VIDEOS & TUTORIALS

 * Unifying Large Language Models and Knowledge Graphs Use-Case and Integrations

Labs Home LLM Graph Builder


CONTENTS

 * How to get started
 * GraphAcademy Courses
 * GenAI Ecosystem
 * GraphRAG
 * GraphRAG Ecosystem Tools
 * Cloud Examples
 * Neo4j GenAI Features
 * GenAI Frameworks
 * Highlighted Articles
 * Videos & Tutorials


NEO4J ONLINE DEVELOPER CONFERENCE

Join us on November 7 for live and unique tech talks over 24 hours across all
timezones.

Register


LEARN

 * Sandbox
 * Neo4j Community Site
 * Neo4j Developer Blog
 * Neo4j Videos
 * GraphAcademy
 * Neo4j Labs


SOCIAL

 * Twitter
 * Meetups
 * Github
 * Stack Overflow
 * Want to Speak?


CONTACT US →

 * US: 1-855-636-4532
 * Sweden +46 171 480 113
 * UK: +44 20 3868 3223
 * France: +33 (0) 1 88 46 13 20

© 2024 Neo4j, Inc.
Terms | Privacy | Sitemap

Neo4j®, Neo Technology®, Cypher®, Neo4j® Bloom™ and Neo4j® Aura™ are registered
trademarks of Neo4j, Inc. All other marks are owned by their respective
companies.