About Memori
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 users 95%+ on inference spend. 15K GitHub stars, 200000+ downloads
What you should know about Memori
Memori — Persistent memory from agent trace, not just conversation. It is categorized under AI Tools . On Product Hunt, this tool has received 130 upvotes from the maker community.
Pricing & licensing: Pricing details are not publicly disclosed at the moment .
Use cases & topics: Memori is associated with the following topics: Open Source, Developer Tools, Artificial Intelligence. Teams working in Open Source / Developer Tools / Artificial Intelligence spaces typically evaluate this kind of tool when scoping new architecture decisions or replacing legacy components.
Getting started: Visit the official site to sign up, explore pricing tiers, and start onboarding your team. Most teams hit value within the first week if the tool aligns with their existing AI Tools stack.
Editor's note from Fanny Engriana (Founder, Wardigi Digital Agency): when evaluating tools in the AI Tools category for our agency clients, we look at three things first — license clarity, community size, and active maintenance. Tools with explicit license terms and ongoing commits tend to remain viable across multi-year projects.