Mem0
Gives AI chatbots and agents a real memory — so they remember what you told them last week — instead of forgetting everything the moment a conversation ends, the way most AI apps do by default.
🔗 Visit Mem0
Description
Talk to most AI chatbots twice and they won't remember anything from the first conversation — every session starts from zero unless a developer builds custom memory logic themselves. Mem0 is a plug-in memory layer that solves that: it stores what a user told an AI agent, what it learned about their preferences, and past interactions, then feeds the relevant pieces back in on future conversations, the way a good assistant remembers your usual coffee order without being told again each time. Mem0 is an open-source (Apache 2.0) memory infrastructure layer for AI agents and applications, combining vector, graph and episodic memory to persist context across sessions. With 61,000+ GitHub stars, it's the most widely adopted project in this space and is the exclusive memory provider integrated into AWS's Agent SDK, with published integrations for Anthropic's SDK, OpenAI's Agents SDK and Google's ADK. Pricing runs Hobby (free, 10K memory-add requests/month), Starter ($19/month, 50K add requests), Pro ($249/month, 500K add requests, unlimited projects, graph memory, Slack support), and custom Enterprise with on-prem deployment, SSO and SLA support. It's SOC 2 Type 1 and HIPAA compliant, and reports over 90,000 developers building on it.
💬 Our review
The short version: Mem0's 61,000+ GitHub stars aren't just a vanity metric — they reflect genuinely being the default choice for AI agent memory right now, reinforced by being AWS's exclusive memory provider for its Agent SDK, which is about as strong a third-party validation signal as this category gets.
The honest trade-off against more specialized competitors: Mem0 covers vector, graph and episodic memory in one general package, whereas a tool like Zep focuses specifically on temporal knowledge graphs and Letta focuses on full self-hosted agent state control — Mem0's breadth is convenient but means it's a generalist rather than the deepest option on any single memory approach. Pricing scales cleanly with usage (10K free requests, then $19 and $249 tiers), which is reasonable for most team sizes, though heavy graph-memory users should check whether the Pro tier's request ceiling fits their actual traffic before committing. For most teams adding memory to an AI agent for the first time, Mem0's adoption, AWS integration and broad framework support make it the safe default; for teams with very specific memory-architecture needs (pure temporal reasoning, or full self-hosted control), the more specialized alternatives are worth a direct comparison first.
💰 Pricing
📊 Global score
🤖 AI-enriched data
Pros
Fournisseur mémoire exclusif de l'AWS Agent SDK — validation tierce forte
61 000+ stars GitHub, projet le plus adopté de sa catégorie
Combine mémoire vectorielle, graphe et épisodique en un seul produit
Conforme SOC 2 Type 1 et HIPAA
Cons
Généraliste plutôt que spécialisé sur une seule approche mémoire (contrairement à Zep sur le temporel, ou Letta sur le contrôle self-hosted complet)
Palier Pro à vérifier selon le trafic réel pour les gros utilisateurs de mémoire graphe
Financement précis (montants de levée) non détaillé publiquement
❓ Frequently asked questions
- What is Mem0 used for?
- Giving AI agents and chatbots persistent memory — remembering user preferences and past interactions across sessions — instead of starting from scratch on every conversation.
- Is Mem0 open source?
- Yes, Apache 2.0 licensed with over 61,000 GitHub stars, making it the most widely adopted project in the AI agent memory category.
- How does Mem0 integrate with AI frameworks?
- It's the exclusive memory provider for AWS's Agent SDK, with published integrations for Anthropic's SDK, OpenAI's Agents SDK and Google's ADK.
- What kind of memory does Mem0 support?
- Vector memory (semantic similarity), graph memory (relationships between facts) and episodic memory (specific past interactions), combined in one system.
- Is it worth the money compared to alternatives?
- For most teams adding memory for the first time, yes — the free Hobby tier and $19 Starter tier are accessible, and the AWS integration plus broad adoption reduce integration risk compared to a newer, less-proven memory tool.
- Which tool should you pick for your case?
- Want the most widely adopted, general-purpose agent memory with strong framework support: Mem0. Need specifically temporal/knowledge-graph reasoning: Zep. Need full self-hosted control over agent state: Letta.