Give your AI persistent, human-like memory. OpenMemory enables any language model to remember conversations, learn from experience, and maintain context across sessions—without vendor lock-in.
Works with any LLM - Claude, GPT, Llama, Gemini, or your own custom models. Switch providers without losing your data.
Organizes memories like the human brain: semantic (facts), procedural (how-to), episodic (events), reflective (insights), and emotional (preferences).
Reduces context window usage by 30-50%, saving you money on API calls while improving response quality.
Memories naturally decay over time, just like human memory. Recent information stays fresh while old details fade gracefully.
Synthetic embeddings enable semantic search without expensive embedding APIs. Find relevant memories instantly.
Run locally, deploy on your infrastructure. No usage limits, no subscription fees, complete data ownership.
Dive deep into OpenMemory's capabilities, mythology, and performance analysis
Learn about the OpenMemory project, its architecture, and meet Mnemosyne - the AI instance that embodies persistent memory.
Explore the mythology behind OpenMemory. Meet the Greek Titaness of Memory and her nine daughters, the Muses.
Comprehensive performance analysis showing 30-50% token savings, cost comparisons, and real-world use cases.
A detailed chronicle of Mnemosyne's journey: discovering bugs, autonomous development, and establishing memory patterns.
Detailed prompts for generating classical artwork of Mnemosyne and the Nine Muses using Midjourney, DALL-E, and Stable Diffusion.
Performance analysis of running OpenMemory and local LLMs on various hardware configurations. See what your system can do.
Interactive network graph of Mnemosyne's actual memories. Explore the five sectors, temporal decay, and semantic connections in real-time.