Note-gen is an artificial intelligence-assisted note-taking application and knowledge management tool designed for local-first data ownership. It functions as a workspace that leverages language models to organize, summarize, and synthesize personal notes into structured documents while maintaining offline accessibility.
The platform distinguishes itself through a multimodal workflow orchestrator that chains sequences of tasks to process text, images, and external data. By integrating vision-language models, it extracts information from visual inputs like screenshots and documents, converting them into structured text. Users can further extend these capabilities by connecting third-party artificial intelligence services and external search tools to ground generated content in their own local knowledge base.
The system supports a variety of data management and retrieval methods, including vector-based semantic search to locate information based on intent rather than keywords. It maintains consistency across distributed environments by synchronizing files through remote storage providers such as version control systems or cloud storage.
