MemoryGraph.dev

The Problem

AI agents are increasingly capable, but they lack memory. Each conversation starts fresh, previous context is lost, and users must repeat themselves constantly. This fundamentally limits what AI can accomplish.

Current solutions are either too simple (basic vector stores) or too complex (custom implementations requiring significant engineering). There's no standard infrastructure layer for AI memory.

The Solution

MemoryGraph provides a graph-based memory system designed specifically for AI agents. It enables:

• Persistent context across conversations and sessions
• Intelligent recall that surfaces relevant information when needed
• Relationship mapping between concepts, entities, and interactions
• Developer-friendly APIs for easy integration

Built as open-source infrastructure, MemoryGraph aims to become the standard memory layer for AI applications.

Why We Invested

We believe AI infrastructure will be one of the most important investment categories of this decade. As AI agents become more capable, the need for foundational infrastructure—memory, reasoning, tool use—becomes critical.

MemoryGraph addresses a real problem with elegant technical architecture. The team combines deep AI expertise with practical engineering experience, and the open-source approach creates strong community dynamics.