Deep Memory – Vocabulary-driven graph memory for AI agents

Deep Memory is a vocabulary-driven graph memory system that enables AI agents to store, retrieve, and reason over long-term knowledge using structured semantic graphs instead of flat text. It is designed for developers building autonomous agents or conversational AI that need persistent, context-aware memory. The project is interesting because it bridges symbolic reasoning with neural networks, allowing agents to dynamically update and query memories based on learned vocabulary, improving coherence and personalization over extended interactions.