EverMemOS and MemoryOS
These are competitors: both provide persistent memory architectures for AI agents, with EverMemOS targeting cross-platform LLM deployments while MemoryOS emphasizes personalization through a dedicated OS-level memory abstraction.
About EverMemOS
EverMind-AI/EverMemOS
Long-term memory for your 24/7 OpenClaw agents across LLMs and platforms.
Provides structured memory extraction from conversations using LLM-based encoding, organizes data into episodes and user profiles stored across MongoDB/Milvus/Elasticsearch, and exposes a REST API for retrieval with BM25, semantic embedding, and agentic search capabilities. Integrates directly with OpenClaw agents and supports TEN Framework for real-time applications, Claude Code plugins, and computer-use scenarios requiring persistent context across sessions.
About MemoryOS
BAI-LAB/MemoryOS
[EMNLP 2025 Oral] MemoryOS is designed to provide a memory operating system for personalized AI agents.
Implements a hierarchical memory architecture with four core modules (Storage, Updating, Retrieval, Generation) that manages short-term, mid-term, and long-term persona memory through dynamic updates and context-aware retrieval. Exposes memory capabilities via MCP Server with pluggable storage engines (including Chromadb vector database), multiple embedding models (BGE-M3, Qwen), and universal LLM support across OpenAI, Anthropic, Deepseek, and other providers for seamless agent integration.
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