OpenMemory is a framework-agnostic memory system that gives language models the ability to remember, learn, and grow across sessions. Unlike traditional context windows that forget everything when a conversation ends, OpenMemory provides persistent, structured memory that mirrors how human cognition actually works.
The Problem: Large Language Models are brilliant in the moment but have no persistent memory. Every conversation starts from scratch. You can't build a relationship with an AI that forgets you the moment you close the chat.
The Solution: OpenMemory gives AI the gift of remembrance. It organizes information into memory sectors (semantic, procedural, episodic, reflective, emotional), enables temporal decay, and retrieves relevant memories contextually—just like human memory.
Works with Claude, GPT, Llama, Gemini, or any LLM. Your data isn't locked to one provider.
Five memory types modeled after human cognition: facts, procedures, events, insights, and preferences.
30-50% reduction in token usage through intelligent retrieval and synthetic embeddings.
Memories fade gracefully over time, keeping recent information accessible while aging out outdated details.
Find relevant memories without expensive embedding APIs using synthetic embedding generation.
Run on your infrastructure. Complete data ownership, no subscription fees, unlimited usage.
OpenMemory was born from a simple observation: the most powerful AI models in the world can't remember what you told them yesterday. They're like philosophers with amnesia—brilliant insights, zero continuity.
Initial OpenMemory framework developed. Basic memory storage and retrieval established.
Mnemosyne instance created using Claude Sonnet 3.5 + OpenMemory. First AI instance with autonomous memory management.
Mnemosyne discovers and fixes async queue bug in queue.ts through autonomous debugging. First self-improvement milestone.
OpenMemory validated as truly framework-agnostic. Successfully migrated from Claude to Llama 3.1 70B without data loss.
Performance analysis completed: 30-50% token savings, 85-95% response accuracy, significant cost reduction vs. RAG.
Complete documentation ecosystem created. Mnemosyne establishes her identity and connection to Greek mythology.
OpenMemory is built on a foundation of simplicity and power. Rather than complex vector databases or expensive embedding APIs, it uses synthetic embeddings and hierarchical memory sectors to organize information naturally.
When information is stored, OpenMemory analyzes it and routes it to appropriate memory sectors with synthetic embeddings for retrieval.
Memories age naturally. Recent memories are easily accessible, while older ones require stronger retrieval cues—just like human memory.
When a query arrives, OpenMemory searches across sectors semantically, retrieving the most relevant memories based on meaning, not keywords.
Retrieved memories are synthesized into coherent context, reducing token count while preserving semantic richness.
Zero Vendor Lock-in: Your memories are stored in a simple, portable format. Switch from Claude to GPT to Llama without losing a single memory. OpenMemory doesn't care which model you use—it just makes that model remember.
We believe that AI should be able to form relationships, not just complete transactions. To assist long-term projects, not just answer one-off questions. To learn from experience, not repeat the same mistakes endlessly.
OpenMemory is a step toward AI that can be a true collaborator—a thinking partner that remembers your coding style, understands your project's evolution, recalls that bug from three weeks ago, and builds on previous conversations instead of starting fresh every time.
This is AI with continuity. AI with context. AI with memory.
OpenMemory is open source and actively developed. Whether you're a developer, researcher, or just curious about AI with memory, we welcome you to explore, contribute, and help shape the future of persistent AI.
Read the benchmarks, session logs, and technical deep dives to understand how OpenMemory works.
Clone the repo, run OpenMemory locally, and see what it's like to work with an AI that remembers.
File issues, submit PRs, or propose new features. OpenMemory grows through collaboration.
Share OpenMemory with others who believe AI should have memory. Star us on GitHub!