Introducing Memory Decay In Mem0

Mem0 has introduced Memory Decay, an optional per-project feature that makes long-term AI agent memory search more time-aware by softly favoring recently accessed memories over idle ones. Rather than deleting, hiding, or filtering older records, it applies a search-time relevance scaling factor ranging from up to 1.5× for recently used memories down to 0.3× for stale ones, allowing strongly relevant historical facts to remain discoverable while reducing their prominence. The feature tracks up to 20 retrieval timestamps per memory, widens search candidates before reranking, preserves API score limits and existing storage, embeddings, metadata, and add workflows, and requires no migration or reindexing. It can be enabled or disabled through the Mem0 dashboard or SDK, with older memories initially using their last-update time as a fallback. Mem0 positions the feature as useful for coding agents, personal assistants, and support bots, and plans future category-aware weighting and project-specific automatic tuning.

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