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Mem0

Drop-in memory layer for AI agents, metered on add and retrieval requests

freemiumHobby is free for individuals and side projects with unlimited end users, 10,000 add requests/month, 1,000 retrieval requests/month, 1 project and community support. Starter is $19/month for solo builders shipping a first agent, with unlimited end users, 50,000 add requests/month, 5,000 retrieval requests/month, 1 project and community support. Pro is $249/month for production apps, with unlimited end users, 500,000 add requests/month, 50,000 retrieval requests/month, unlimited projects, multi-project support, private Slack support, advanced analytics, graph memory with entity linking and Dream memory consolidation. Enterprise is custom-priced with unlimited add and retrieval requests, unlimited projects, SLA-backed support, on-prem deployment, audit logs, and custom integrations and SSO. The open-source project is free to self-host.View full pricing →

About Mem0

Mem0 is drop-in memory infrastructure for AI agents and applications: a hosted layer that stores what a user said and preferred, keeps it across sessions and across separate agents, and returns it as context on the next call. It is one of the most widely adopted open-source projects in this category, with over 62,000 GitHub stars, which matters practically because the self-hosted path is a real option and the API surface has been exercised by a large number of implementations rather than a handful. The billing model reflects how memory systems are actually used and is a useful contrast with per-token pricing: plans meter add requests and retrieval requests separately, with retrieval allowances roughly a tenth of add allowances, because agents write memories far more often than they read them back. End users are unlimited on every tier including the free one, so a consumer app with a large user base and light per-user memory is not penalised for its user count. Higher tiers add graph memory with entity linking, which moves the product from flat fact storage toward relationship-aware retrieval, and Dream, the company's memory consolidation feature that keeps stored memory accurate as it grows rather than accumulating contradictory entries. Multi-project support, advanced analytics and private Slack support arrive at Pro; on-prem deployment, audit logs, SSO and custom integrations at Enterprise.

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Key Features

Persistent memory across sessions and across agents
Unlimited end users on every tier including free
Separate metering for add and retrieval requests
Graph memory with entity linking on Pro
Dream memory consolidation keeps stored memory accurate
Open source with 62k+ GitHub stars, self-hostable

Tags

agent-memoryopen-sourcepersonalizationragy-combinator
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