Provides AI assistants with persistent memory across sessions using local SQLite and keyword search, allowing storage and retrieval of user preferences, project context, and decisions.
Gives any AI tool persistent, searchable memory across sessions using hybrid semantic and keyword search, running 100% locally with no API keys or cloud dependencies.
Gives AI assistants persistent, shared memory using the Zettelkasten method, so they retain corrections, preferences, and decisions across sessions and across tools via local, hybrid search.
Provides persistent AI agent memory using a local vector database for long-term semantic storage and short-term session scratchpads. It enables low-latency memory operations including search, storage, and bulk management without external cloud dependencies.
Provides local vector-based semantic memory storage for AI assistants to persist context and decisions across sessions using local embeddings and LanceDB. It enables private semantic search and session handoff capabilities to maintain long-term project context.