GBrain is an open-source AI memory system designed to give autonomous agents persistent, structured, and scalable long-term memory across interactions and workflows. It operates by transforming large collections of markdown documents, personal notes, and external data into a searchable knowledge base backed by PostgreSQL and vector embeddings, enabling both semantic and keyword-based retrieval. The system is tightly integrated with agent frameworks such as OpenClaw and Hermes, allowing AI agents to read from and write to memory continuously, effectively evolving their understanding over time. GBrain introduces a hybrid retrieval model that combines embeddings with ranking strategies to improve relevance when querying large datasets. It also organizes knowledge into structured documents with summaries and timelines, helping agents maintain context and track changes in information.
Features
- Persistent long-term memory for AI agents
- Hybrid search combining vector and keyword retrieval
- Markdown-based knowledge storage with structured timelines
- Integration with OpenClaw and Hermes agents
- Supports local and scalable Postgres deployments
- Continuous read/write memory updates across interactions