Independent research: GraphRAG makes AI agents 80% more truthful | Read the report

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The knowledge layer that makes AI accurate

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80+ Fortune 100 customers

Uber
Cisco
Walmart
Santander
Comcast
BNP Paribas
UBS
Airbus
BT Group
BMW
Boston Scientific
Novo Nordisk
Dun & Bradstreet
Intuit
Adobe
Levi's
NBC News
Siemens
Transport for London
Merck

Context, memory, and reasoning

A knowledge layer gives your organization the context of its relationships, history, and decisions. So your team and their agents can act faster and more confidently, no matter the use case.

Learn more about the knowledge layer

Graphs & AI drive better decisions with built-in context

AI gets smarter
with graph

Power fraud detection, customer experience, operations, and more on one connected platform.

A graph fanning out from several hub nodes
A Neo4j console prompt being asked to get started with insurance claims fraud

AI that earns
your trust

Model relationships in a graph to trace every decision back to its source and reduce token spend.

44% fewer hallucinations
80% more truthful agents
2x better factual precision & recall

Enterprise-grade

We provide robust controls, encryption, and compliance across any cloud for a secure, governable, and scalable environment.

7.8 month payback on investment
230% ROI
IBM
Microsoft Azure
Google Cloud
McKinsey & Company
Deloitte
Amazon Web Services
Databricks
Capgemini
Snowflake
Accenture

170+ partners

We fit right in

Works everywhere with everyone

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IBM
Microsoft Azure
Google Cloud
McKinsey & Company
Deloitte
Amazon Web Services
Databricks
Capgemini
Snowflake
Accenture

Loved by devs.
Deployed worldwide.

Intuit built its security knowledge platform on a Neo4j knowledge graph, allowing it to map, monitor, and visualize network interdependencies and rapidly respond to security threats.

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100M customers protected using Neo4j
75M database updates made per hour into the graph
500k DNS endpoints attributed to host names in milliseconds

How a digital twin of the world’s most intricate transport network, built on Neo4j’s graph solution, boosts incident response time, improves journeys for millions and lays the groundwork for the metropolis of the future.

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10% estimated congestion reduction
$750M estimated annual economic savings
$1,500 annual time savings value for every driver

BNP Paribas Personal Finance, a subsidiary of banking giant BNP Paribas Group, specializes in retail financing through consumer credit and installment payment services where sniffing out fraudsters is a critical part of their mission.

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800k applications processed per year
20% reduction in fraud with Neo4j
2s maximal query latency with Neo4j
“We’re using Neo4j not as just a data store, but as a place to analyze data and store those new characteristics of the data back in the graph and then extract it for traditional analysis,”

Eric Wespi Data Scientist, Boston Scientific

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“Agentic AI without a knowledge graph is like a self-driving car with no GPS map. Kind of brilliant, but dangerously unaware.”

Natalie Romanov Associate Director, Knowledge Management & Data Strategy, Merck Group

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“Graph databases are a natural way to express interconnected data. The simplicity extends from humans to LLMs — making our configurations more accessible and explainable.”

Vignesh Murugesan Senior Staff Engineer, Uber

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Manage context and
build agentic GraphRAG

Keep your agents intelligent with adaptive data capabilities that evolve as users interact, requirements shift, and AI advances.

Provide accurate, explainable LLM outputs with Agentic GraphRAG.

Learn how
KnowledgeGraph Vectorsearch Graph datascience

What’s new

Neo4j acquires GraphAware

Our longtime partner and a leading provider of intelligence analysis software for government agencies.

Read more

Build GraphRAG from Scratch

Learn how to feed your LLM context to boost RAG performance, accuracy, and traceability in Essential GraphRAG from Manning.

Learn to build

230% ROI

IDC validated $4M in annual value and a 7.8-month payback for enterprises running Neo4j.

See the results

Get to know Neo4j

What is Neo4j?

Neo4j is the knowledge layer that delivers accurate, explainable, and trusted AI. You can build a knowledge layer with the Neo4j Graph Intelligence Platform.

How can I try Neo4j?

You can get started with Neo4j AuraDB, our fully managed graph database.

What is a knowledge layer?

A knowledge layer connects your AI systems to your data so AI can reason and understand not just individual facts, but how they relate to each other, what has changed, and what has been decided before.

What is a knowledge graph?

A knowledge graph is an organized representation of real-world entities and their relationships that help people and agents. It is typically stored in a graph database, which natively stores the relationships between data entities. Entities in a knowledge graph can represent objects, events, situations, or concepts.

What is a context graph?

A context graph is a structured, three-tiered memory architecture for AI agents that connects long-term enterprise knowledge, short-term conversation history, and reasoning/decision traces in a unified graph, giving agents the accurate, explainable, and governable memory they need to act reliably in production.

What is a graph database?

A graph database collects and stores data as a network, foregrounding the connections between data entities. Unlike relational databases, which store data in tables, graph databases are organized around nodes and relationships.

Knowledge is at your fingertips

Make your AI accurate, explainable, and trustworthy.

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