gbrain

What problem does it solve?

It solves the problem of scattered personal and team knowledge by compiling your notes into a searchable knowledge base that combines keyword search and semantic retrieval, so you can answer questions faster with better context.

Core Features & Use Cases

• Hybrid RAG knowledge brain: stores compiled truth and append-only timelines in PostgreSQL to support accurate recall and change history.
• Typed-graph entity linking: connects people, companies, concepts, and meetings with relationship types so queries stay grounded and navigable.
• Operational workflow commands: supports setup, markdown import/sync, hybrid query, ingestion of new signals, and ongoing health/stats checks for continued quality.

Use case: You ingest meeting notes and scattered markdown files, then later ask what is known about a specific company or person and receive fused keyword+vector results grounded in stored pages and timelines.

Quick Start

Use the gbrain skill to query what you know about an entity by running the command: /gbrain query "What do we know about Company X?"