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Mem0

Mem0 is a scalable memory layer for AI agents that provides long-term, personalized, and efficient memory storage and retrieval.

Overview

Mem0 (“mem-zero”) is a memory layer designed for AI assistants and agents. It enables hierarchical memory management and efficient retrieval to support personalized, long-term interactions.

Key features

  • Multi-level memory: supports user-, session-, and agent-level memories with adaptive personalization.
  • Cost-efficient long-term memory: reduces context cost using retrieval and summarization strategies to lower token consumption and latency.
  • Developer-friendly: cross-platform SDKs (Python/TypeScript), hosted and self-hosted options, and integrations with common vector backends.

Use cases

  • Personalized chat assistants that retain user preferences and long-term context.
  • Customer support systems that recall historical tickets and user interactions.
  • Multi-modal agents that require persistent state across long-running tasks.

Technical notes

  • Supports multiple vector stores and flexible retrieval/indexing strategies; offers managed platform features and an open-source SDK with demos and documentation (OpenMemory integration).

Comments

Mem0
Resource Info
🌱 Open Source 🧏 Memory 📚 RAG