meeting-ingestion

To extract action items and decisions from meeting transcripts, the skill automatically parses raw text to identify attendees, key decisions, action items, and topics, structuring them into interconnected knowledge pages.

Building a knowledge graph from meeting notes is achieved through entity propagation, which automatically creates or updates pages for all mentioned people and companies to ensure unified, bidirectional linking across domains.

Yes, you need the gbrain system to sync meeting timelines, as the skill requires integration with gbrain to perform page creation, entity updates, timeline merging, and index synchronization.

Entity extraction for company and people profiles works by parsing raw meeting transcripts, automatically enriching entity profiles, and merging meeting events into the timelines of all participants and companies involved.

You can process raw meeting transcripts provided in the current context without prior formatting, as the skill ingests raw text and automatically parses key outcomes to update the brain accordingly.