About OpenMemory
Long-term memory for AI systems. Open source, self-hosted, and explainable.
What is OpenMemory?
OpenMemory is an open-source, self-hosted long-term memory system for AI. Unlike traditional vector databases, OpenMemory uses a cognitive architecture that organizes memories by type (semantic, episodic, procedural, emotional, reflective), tracks importance over time, and builds associations between related memories.
It gives AI systems persistent memory that stores what matters, recalls it when needed, and explains why it matters - delivering 2-3× faster contextual recall at 6-10× lower cost than cloud alternatives.
Key Features
- →Multi-sector memory - Different memory types for different content
- →Automatic decay - Memories fade naturally unless reinforced
- →Graph associations - Memories link to related memories
- →Temporal knowledge graph - Time-aware relationships with fact evolution
- →Pattern recognition - Finds and consolidates similar memories
- →User isolation - Each user gets a separate memory space
- →Framework agnostic - Works with any LLM or agent system
Performance Highlights
Speed
- • 115ms avg query time
- • 338 QPS throughput
- • 95% recall accuracy
Cost
- • $8-12/month self-hosted
- • 6-12× cheaper than cloud
- • Local embeddings support
Use Cases
OpenMemory is perfect for:
- →Long-term AI agents and copilots
- →Personal AI assistants with memory
- →Cognitive journaling applications
- →Educational and research tools
Get Started
Ready to give your AI systems persistent memory? OpenMemory is open-source and easy to deploy. Check out our GitHub repository for documentation, examples, and deployment guides.