Memori and EverMemOS
A SQL-native memory layer designed for multi-agent systems complements rather than competes with a long-term memory OS, as the former provides structured persistence while the latter handles temporal state management across distributed agents.
About Memori
MemoriLabs/Memori
SQL Native Memory Layer for LLMs, AI Agents & Multi-Agent Systems
This tool helps developers give their AI agents and large language models (LLMs) the ability to remember past interactions and learn from what they do, not just what they say. It takes conversations and actions from your agents and uses them to provide relevant context for future interactions. This is for developers building AI agents, multi-agent systems, or applications that use LLMs, who want their AI to have persistent, long-term memory.
About EverMemOS
EverMind-AI/EverMemOS
Long-term memory for your 24/7 OpenClaw agents across LLMs and platforms.
This project provides long-term memory capabilities for AI agents, allowing them to remember past interactions and information across various platforms and sessions. It takes conversations, documents, or observations as input and helps the AI agent recall relevant context. This is ideal for developers building always-on, continuously learning AI assistants, virtual characters, or automated systems that need to maintain context over time.
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