Mem0

Mem0, pronounced mem-zero, gives assistants and agents a memory layer so preferences and history survive between sessions. It is aimed at customer support bots, personal assistants and autonomous systems that otherwise forget everything the moment a conversation ends.

The April 2026 algorithm changed how memories form. Extraction is a single model call that only adds, so nothing gets overwritten, and retrieval fuses semantic search, BM25 keyword matching and entity matching scored in parallel.

The pieces that matter when building on it are these.

• Multi-level memory: user, session and agent state are retained separately and adapt over time.
• Entity linking: entities are extracted, embedded and linked across memories to boost retrieval.
• Temporal reasoning: time-aware ranking picks the right dated instance for past and upcoming queries.
• Agent-generated facts: what an agent confirms is stored with the same weight as user statements.
• SDKs: Python and JavaScript packages install from pip and npm, with an optional NLP extra.

Three deployment shapes exist. A library suits prototyping, a self-hosted server starts with docker compose and issues its own API keys, and a managed cloud platform removes the operations work. Published benchmark numbers reflect that managed service, which carries optimizations the open source SDK does not include.