Mem0 is a memory layer that gives AI assistants and agents persistent, personalized context: it retains user, session, and agent-level state, recalls preferences and history across conversations, and continues learning over time. It is available as an open-source library (Python and TypeScript) with a fully managed hosted option, and the README highlights use cases in customer support, AI assistants, healthcare, and adaptive productivity tools. Agents can even self-provision an API key from the CLI, with a human claiming the account later.
A revised memory algorithm (April 2026) replaced update/delete logic with single-pass ADD-only extraction — memories accumulate rather than being overwritten — added first-class storage of agent-confirmed facts, entity linking across memories, fused multi-signal retrieval (semantic, BM25, and entity matching), and time-aware ranking for queries about current state versus past events. Reported benchmark results, all single-pass retrieval:
| Benchmark | Old | New | Tokens | Latency p50 |
|---|---|---|---|---|
| LoCoMo | 71.4 | 91.6 | 7.0K | 0.88s |
| LongMemEval | 67.8 | 94.8 | 6.8K | 1.09s |
| BEAM (1M) | — | 64.1 | 6.7K | 1.00s |
| BEAM (10M) | — | 48.6 | 6.9K | 1.05s |
The evaluation framework is open-sourced so the numbers can be reproduced independently.
Integrates with
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LangGraph
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