AutoMem addresses the limitation of AI assistants losing context between sessions by combining vector embeddings with typed knowledge graphs. It integrates with Qdrant (vector database) and FalkorDB (graph database) to store both semantic embeddings and structured relationships, enabling richer memory recall than pure vector search alone. The system is designed to run on user infrastructure and includes MCP server integration for AI assistant frameworks.