Provides AI agents with persistent, local cross-session shared memory by combining vector semantic retrieval with knowledge graph relationships, and supports short/long-term memory management and local backups.
Enables AI agents to store, retrieve, and connect information in a Neo4j graph database as persistent memory, with semantic relationships, natural language search, and temporal tracking across conversations.
Enables AI agents to persist memories across sessions and recall them through graph-traversal spreading activation over interconnected neurons with explicit relationship types, supporting multi-hop reasoning fully offline without embedding API costs.
Provides persistent knowledge graph memory for AI agents, enabling them to store, recall, and query facts about people, projects, and relationships across sessions.
Persistent semantic memory for AI agents, enabling storage, semantic search, knowledge graph connections, and inter-instance messaging across conversations using local models via Ollama.
Provides AI agents with persistent, searchable memory using semantic search, auto-linking, and categorization, with zero-config local setup or production-ready external providers.
