meeting-ingestion

Automating meeting transcript ingestion requires parsing text data to extract attendees, topics, and action items, then creating structured brain pages with links to mentioned entities. This Skill handles the entire process from transcript parsing to brain page updates.

Entity propagation works by linking every company and project mentioned in a meeting transcript to the brain page, then merging meeting events into the timelines of all mentioned entities to ensure structured content is automatically updated.

Yes, you can use this to extract action items and decisions from meeting notes. The transcript ingestion process parses text data to identify attendees, dates, topics, decisions, and action items, enriching them with attendee details before brain page creation.

The best way to merge meeting events into entity timelines is through automated transcript processing that identifies mentioned companies and projects, then propagates those entities and merges the meeting events directly into their respective timelines.

No manual formatting is required before ingestion. The Skill automates parsing of text data from raw meeting transcripts, extracting necessary information like attendees and topics, and handling the creation of structured content and external entity links automatically.

Limitations depend on the transcript text data quality, as the Skill requires parsing text to identify companies and projects for entity propagation. If external entities are not clearly mentioned in the meeting notes, they will not be linked or updated in the brain page.