Memori

Persistent memory from agent trace, not just conversation

206 followers

Persistent memory from agent trace, not just conversation

206 followers

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AI Infrastructure Tools

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LLM Memory

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OpenClaw

Memori launched its new agent-native memory infrastructure, enabling agents to create structured, long-term memory directly from agent trace — including execution paths, tool results, workflow steps, outcomes, and decision-making logic. This allows memory to also be generated from what an agent actually does. Benchmark results: 81.95% accuracy on LoCoMo using only 1,294 tokens per query, roughly 5% of full-context cost, saving up to 95.03% on inference spend. 15K+ GitHub stars, 200000+ downloads

Memori Alternatives

Exploring options beyond Memori’s trace-based memory? Check out Cortex for unified workspace search, Mnexium AI for structured, persistent agent memory, Langfuse for LLM telemetry and evals, GetProfile for long‑term user profiles, and Mistral AI for fast, open models.