multi-agent-memory-system

Build persistent, structured memory systems for LLM agents that remember user context across sessions, organize information semantically, and retrieve relevant knowledge automatically before responding. Achieves 35% accuracy gains over RAG baselines with 99.9% smaller storage overhead.

Independent GitHub snapshot · Automated classification · Original documentation governs