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graphrag.com
Neo4j, Inc is the company behind graph technology and knowledge-graph solutions, focusing on patterns and resources that enable scalable data understanding and retrieval.
Neo4j, Inc is a technology company that develops graph-based data platforms and knowledge-graph solutions. It focuses on enabling retrieval-augmented information access and related data integration patterns that leverage connected data. The organization serves developers and organizations looking to organize, query, and derive insights from complex networks of information.
Mission statement
Advance retrieval-augmented generation using knowledge graphs, providing patterns and resources to help developers build graph-powered data solutions.
Products & Services
GraphRAG Pattern Catalog Platform
Facilitates access to diverse GraphRAG retrieval patterns and knowledge graph models.
graphrag.com- ✓ Pattern Catalog of GraphRAG Retrievers — Comprehensive Retrieval Patterns Collection
- ✓ Vector Similarity Search — Fetches Relevant Chunks Quickly
- ✓ Knowledge Graph Pattern References — Access Diverse Knowledge Graph Patterns
- ✓ Graph-Enhanced Vector Search — Enhance Retrieval Accuracy
- ✓ Document Chunking and Embedding — Enables Efficient Text Retrieval
- ✓ Open Collaboration and Updates — Engage with a Collaborative Community
- ✓ Compatibility with Retrieval-Augmented Generation — Enhances RAG Capabilities
- ✓ Dynamic Cypher Generation — Automate Cypher Queries
Market Segments
Knowledge graph management
Capabilities to model, store, query, and maintain enterprise knowledge graphs, including graph data models, Cypher query generation, and integration with upstream data sources.
Retrieval-augmented generation platforms
Capabilities that integrate enterprise data retrieval with large language models to provide contextually accurate, up-to-date responses using RAG, vector storage, and secure enterprise data connectors.
Vector search and GenAI data management
Semantic vector search, hybrid retrieval, and AI-focused data features that accelerate generative AI applications and enable agent memory, semantic caching, and fast similarity search.
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Common Questions
- What does Neo4j, Inc do?
- Neo4j, Inc is a technology company that develops graph-based data platforms and knowledge-graph solutions. It focuses on enabling retrieval-augmented information access and related data integration patterns that leverage connected data. The organization serves developers and organizations looking to organize, query, and derive insights from complex networks of information.
- What is Neo4j, Inc's role in the Knowledge graph management market?
- Capabilities to model, store, query, and maintain enterprise knowledge graphs, including graph data models, Cypher query generation, and integration with upstream data sources.
- What is Neo4j, Inc's role in the Retrieval-augmented generation platforms market?
- Capabilities that integrate enterprise data retrieval with large language models to provide contextually accurate, up-to-date responses using RAG, vector storage, and secure enterprise data connectors.
- How was the Knowledge graph management market size estimate for Neo4j, Inc calculated?
- Multiple industry reports in the search results estimate the knowledge-graph market at roughly USD 1.3–1.7B in 2024–2025 with multi-year forecasts to ~USD 8–9B by the early-to-mid 2030s. GMI and MarketResearchFuture provide similar CAGR estimates (~18.6–19.4%), while MarketsandMarkets projects a higher CAGR (31.6%) to a 2032 figure. I select a current market size of ~USD 1.5B (2025) and a growth potential ~19.4% CAGR as the consensus-aligned estimate supported by multiple sources.
- How was the Retrieval-augmented generation platforms market size estimate for Neo4j, Inc calculated?
- Primary estimate uses Precedence Research’s explicit 2025 market size and forecast (USD 1.85B in 2025; CAGR 49.12% 2025–2034). This is corroborated by AtScale’s citation of a Grand View Research estimate (~USD 1.043B in 2023) and a similar high-growth projection (44.7% to 2030), indicating strong consensus on rapid multi-year CAGR.
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