smrti
Memory engine for AI agents
What it does
smrti is an AtomSpace-inspired graph database for agent memory. Each node—an atom—carries a Bayesian truth value, an emotional valence, and an attention weight. Retrieval ranks by computed salience across five dimensions, not by timestamp. Your agent remembers what matters, not just what happened last.
Does the same job
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- ALA local-first memory store for LLM agents (SQLite)Dec 2025 · github.com · ▲48
- YAYourMemory, agentic memory is a pruning problem, not a hoarding problemJun 2026 · yourmemoryai.vercel.app · ▲19
This is a project that I have been building for a while now, YourMemory is a solution to agentic memory which focuses on pruning of noise rather than hoarding of data. In the current state of agentic memory most of the context is stored in the form of a MD file or is derived through a RAG model where you store each and everything. Both of the solution leads to bloated context which does not optimize the usage of any tokens. In this system we only keep relevant data in our memory and prune all the unnecessary data. The relevance of a data is derived through multiple factors such as recall…
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, March 2026
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