What is the difference between Mem0 Open-Source and the Platform?

The open-source version is a self-hosted library/Docker stack you run on your own infrastructure. The hosted Platform provides managed scaling, analytics, enterprise features like SSO, and managed deployments.

What is a memory add request vs. a retrieval request?

An 'add' request is when you save or update memories (from conversations or data). A 'retrieval' request is when you search for relevant memories to inject into your AI's context.

How does Mem0's memory compression work?

Mem0 uses a proprietary single-pass hierarchical distillation algorithm to automatically condense chat history into compact, meaningful memories. This reduces token usage and latency while preserving critical context.

Can I use Mem0 with LangChain or CrewAI?

Yes, Mem0 provides dedicated integration guides and plugins for over 20 frameworks, including LangChain, CrewAI, LlamaIndex, and the Vercel AI SDK.

What is 'Dream' (Memory Consolidation)?

Dream is an advanced feature on Pro/Enterprise plans. It automatically consolidates and refines stored memories over time, similar to how human memory works, improving retrieval relevance and reducing noise.

Do you support on-premise deployment?

Yes. On-premise deployment is available for Enterprise customers, allowing you to run Mem0 within your own data center or private cloud environment with full control.

Directory/Chatbots/AI Memory/Mem0

Mem0

Mem0 is a production-ready memory infrastructure for AI agents and applications, providing persistent context across sessions and tools. It features a memory compression engine that automatically condenses chat history into compact memories, reducing token usage and latency while maintaining relevant context. The system learns, updates, and retrieves key memories in real-time as users interact with the AI. The platform offers a simple API for adding, learning, and retrieving memories, with SDKs for Python and Node.js. It supports advanced features like graph memory for entity linking and 'Dream' for memory consolidation. Designed for both developers and enterprises, it includes governance, security (SOC 2, HIPAA, GDPR), and deployment options ranging from cloud to on-premises. Target users include AI developers, product teams, and enterprise engineering squads building applications in healthcare, education, sales, and customer support.

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Sep 22, 2026

AI MemorySDKAPIPersistent ContextToken CompressionGraph MemoryEntity LinkingSOC 2HIPAAOn-prem

Product information

Everything worth knowing about Mem0

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Drop-in Memory Infrastructure

A simple SDK and API to add persistent memory to AI agents and apps without pipeline changes.

Memory Compression Engine

Automatically condenses chat history into compact memories to reduce token usage and latency while preserving context.

Multi-Signal Retrieval

Retrieves key memories as users interact, using various signals for accurate context recall.

Graph Memory (Entity Linking)

Links related memories and entities, creating a knowledge graph for more sophisticated context understanding.

Memory Consolidation (Dream)

Periodically merges and summarizes stored memories to maintain relevance and reduce noise over time.

Technical capabilities

Single-Pass Hierarchical Distillation

A proprietary algorithm for efficient memory extraction and storage in a single processing pass.

Gateway

Controls exactly what each AI agent can access and do within the memory layer.

Must watch videos

OpenClaw is Broken? Give Your AI a Real Memory with Mem0

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Tutorial0:48

OpenClaw is Broken? Give Your AI a Real Memory with Mem0

OpenClaw agents forget. Details you shared earlier stop showing up. Memory capture and recall are left to the LLM, so neither is guaranteed. This video shows how to add persistent memory to OpenClaw using @mem0/openclaw-mem0. Memory is captured outside the agent loop and reinjected on every turn. No prompt rewrites. No lost context after restarts. What you'll learn: - Why OpenClaw's default memory breaks on long sessions - How auto-capture and auto-recall work under the hood - Connecting Mem0 via OTP (no API key, no config edits) - Running Mem0 in open-source mode for self-hosted setups - Verifying memory survives a restart from the CLI - The 5 memory tools your agent gets out of the box ⏱ Chapters 0:00 The problem with OpenClaw memory 0:00 How Mem0 fixes it 0:00 Setup walkthrough (OTP flow) 0:00 Self-host mode 0:00 Verifying persistence 0:00 Memory tools reference 🔗 Resources Full guide: https://mem0.ai/blog/add-persistent-memory-openclaw Setup command: https://mem0.ai/claw-setup Docs: https://docs.mem0.ai GitHub: https://github.com/mem0ai/mem0 Discord: https://discord.com/invite/skNhacB39h #Mem0 #OpenClaw #AIAgents #LLM #AIMemory

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Tutorial1:54

Introducing OpenMemory Chrome Extension

OpenMemory - The Universal Memory Layer for AI Assistants Built by the Mem0 team You shouldn’t have to repeat yourself every time you switch AI tools. OpenMemory keeps your memory and context consistent across ChatGPT, Claude, Gemini, Perplexity, etc, so each one picks up right where the last left off.

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Tutorial2:24

OpenMemory MCP

OpenMemory MCP is a private memory server for MCP-compatible clients powered by mem0.ai

Who uses it

Real use cases, no hype

Personalized Customer Support

Retain customer history, preferences, and past issues across interactions for faster, context-aware resolution.

Healthcare Patient Assistants

Remember patient history, allergies, and treatment preferences across visits for consistent, personalized care.

Adaptive Education Tutors

Track student progress, learning styles, and effective methods to tailor lessons that evolve over time.

Sales & CRM Context

Maintain persistent context through long sales cycles, remembering objections, milestones, and preferences.

Long-Running AI Agents

Enable agents to recall prior work, decisions, and user feedback across multiple autonomous runs.

Companion Chatbots & Voice Agents

Build assistants with consistent personality and memory of past conversations for natural interaction.

What's great

Drop-in memory for AI agents and apps
Persistent context across sessions and agents
Reduces redundant context and token costs
SOC 2, HIPAA, GDPR compliance ready

Technical strengths

Single-pass hierarchical distillation for efficient memory compression
Multi-signal retrieval across user, session, and entity IDs
Supports graph memory with entity linking on Pro/Enterprise plans

Where it falls short

Free tier has tight monthly request limits
Advanced features (graph memory, Dream) require paid plans
On-prem deployment only for Enterprise tier
Open-source version has limited features vs. platform

Technical limitations

Retrieval and add requests are metered, not truly unlimited on lower tiers
Custom integrations and SSO are gated behind Enterprise

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

Yes, the Hobby plan is free. It includes 10,000 add requests and 1,000 retrieval requests per month, unlimited end users, one project, and community support.