Neo4j, a graph intelligence platform, today announced a $100 million investment to accelerate its role as the default knowledge layer for agentic systems and critical infrastructure for generative AI (GenAI). The funding will support product innovation, including the launch of two new agentic offerings, Neo4j Aura Agent and Model Context Protocol (MCP) Server, and startup programs for AI-native companies worldwide, supporting 1,000 startups over the next 12 months.
The investment addresses a critical industry challenge: the difficulty enterprises face in moving GenAI from pilot to production. According to MIT research, 95% of GenAI pilots fail to deliver meaningful returns, often due to a lack of context, memory, and learning capabilities. Neo4j’s graph-based technology aims to close this gap, enabling enterprises to scale AI reliably with accurate, explainable outcomes while reducing wasted spend.
“Agentic systems are the future of software,” said Emil Eifrem, Co-Founder and CEO of Neo4j. “They require contextual reasoning, persistent memory, and traceable outputs—capabilities that graph technology uniquely delivers. This investment allows us to accelerate that vision.”
Driving Enterprise Adoption of Graph Technology in GenAI
Neo4j is trusted by 84 of the Fortune 100 and more than half of the Fortune 500. Its platform powers agentic deployments at companies including Uber, Walmart, and Klarna, providing structured memory and context for AI agents to reason, act, and remember—foundational capabilities for production-grade agentic AI.
In the past 12 months, Neo4j claims to have recorded six times growth in GenAI customers; 58% revenue growth in cloud consumption and 82% growth in Product-Led growth.
“Graph is essential. It is the skeleton to the LLM’s flesh,” said Charles Betz, VP Principal Analyst at Forrester, highlighting the importance of structured data for enterprise AI.
New Products Simplify Enterprise Agent Development
The newly announced Neo4j Aura Agent (early access) allows enterprises to build, test, and deploy AI agents directly on their data within minutes, offering automated orchestration and AIOps for graph-based knowledge retrieval. The MCP Server integrates graph-based memory and reasoning into existing AI agents, supporting natural language querying, auto-generated graph models, and automated database management. Both products are set for full availability in Q4 2025.
“Enterprise knowledge graphs are critical infrastructure for reliable agentic AI,” said Conor O’Shea, AI Architect at Daimler Truck. “Neo4j Aura Agent and MCP Server will make these capabilities more accessible for enterprises building next-generation intelligent applications.”
Global Startup Program for AI-Native Companies
In addition, Neo4j announced a startup program designed to support over 1,000 AI-native companies worldwide, offering cloud credits, technical enablement, and go-to-market support. The program already counts 208 members, including Firework, Garde-Robe, Hyperlinear, Mem0, OKII, Rivio, and Zep.
“Eight out of ten GenAI-native startups I speak with are re-platforming on Neo4j,” said David Klein, Neo4j Board Director and Co-Founder of One Peak. “Neo4j is the natural choice for building intelligent systems with context and memory.”
Executive Appointments to Support Growth
Neo4j also announced leadership appointments to support its growth agenda:
- Sudhir Hasbe promoted to President and Chief Product Officer
- Mark Woodhams, ex-Oracle, appointed Chief Revenue Officer
- Ajay Singh, ex-Databricks, appointed Head of Global Field Engineering
“These leadership moves, together with our investment and product launches, set Neo4j up for the next chapter as the graph intelligence platform for agentic AI,” said Emil Eifrem.
Investing from Strength
Neo4j surpassed $200 million in revenue in 2024. The $100 million board-approved investment reflects confidence in the company’s technology, leadership, and market traction, positioning Neo4j as a foundational platform for large-scale GenAI adoption.
“Neo4j is transforming how enterprises turn data into knowledge, which is essential for AI to work at scale,” said Patrick Pichette, Partner at Inovia Capital and Neo4j Board Director.
