Agents & Tool Use · 2025
Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory
Introduced a scalable memory architecture that dynamically extracts, consolidates, and retrieves salient information to enable LLMs to maintain consistency over prolonged multi-session dialogues.
Editorial record
Plain-language summary
Mem0 addresses the fixed context window limitation by implementing extraction and update phases that identify key facts from conversations and evaluate them against existing memories, applying ADD/UPDATE/DELETE/NOOP operations. An enhanced variant with graph-based memory representations captures complex relational structures. Evaluated on the LOCOMO benchmark, Mem0 achieved 26% improvement over OpenAI while reducing p95 latency by 91% and saving over 90% in token costs compared to full-context approaches.
Source record
Provenance
- Record ID
- P-664
- Record created
- 2026-08-12
- Last reviewed
- 2026-08-12
- Record version
- 1
- https://arxiv.org/abs/2504.19413
- arXiv:2504.19413
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