I Built a Personal AI Agent on a Raspberry Pi — Jeremy Adams, Neo4j

This post details the creation of a wearable personal AI agent on a Raspberry Pi 4B, leveraging NanoClaw and Neo4j Agent Memory. It demonstrates building graph memory using the POLE schema (person, object, location, event) for capturing contextual information, integrating voice-to-text via a USB microphone and hardware button, and implementing an offline-first capture mode with a local Neo4j instance that syncs and enriches data in the cloud. The architecture involves WhatsApp for messaging, Claude for LLM processing, and Neo4j for persistent, queryable memory.