Cognitum Seed Device is a palm-sized edge AI appliance built on a Raspberry Pi Zero 2 W, firmware v0.8.1. It runs ~2.5M-parameter INT8 models at 10+Hz while juggling five sensor streams (reed switch, PIR, vibration, ADS1115 ADC, BME280), an append-only RVF vector store chained by SHA-256 witnesses, an Ed25519 device-bound key, 13 drift detectors, and a spectral-graph cognitive container. Think of it as a tamper-evident memory and nervous system for any LLM.
Why it’s suddenly everywhere
Reuven Cohen’s RuView — the WiFi DensePose project that reads human pose, breathing and presence from plain router signals — went viral this week on GitHub Trending, r/LocalLLaMA and dev.to, with writeups at Cybernews, GBHackers and Let’s Data Science. The catch: RuView’s ESP32 mesh nodes (as low as $9 each) all feed into a Cognitum Seed. Every thread pulls the Seed into the conversation.
It speaks MCP, 114 tools out of the box
Agents don’t SSH in. The Seed exposes an MCP Proxy with 114 JSON-RPC 2.0 tools. Any MCP-capable agent — Claude, Cursor, homegrown — can write vectors into RVF, query kNN, pull PIR/ADC streams, trigger drift detection, or sign payloads with Ed25519. Rust, Node and Python SDKs ship alongside fleet management and OTA updates. Typical integration: the LLM as the offline sensing backend for a home or factory, with persistent memory the agent actually owns.
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