SUMMARIZATION
Zoom Recording Auto-Chaptering to Notion Topic Index
When a Zoom cloud recording finishes, transcribe it, detect topic boundaries, and publish a chaptered, timestamped topic index as a searchable Notion page.
How it runs
The automated pipeline, trigger to output.
- TriggerZoom recording completed webhookZoom
- ActionFetch transcript or transcribe audio (ASR)Hugging Face
- ActionSegment transcript into timestamped chaptersHugging Face
- ActionGenerate chapter titles and summariesOpenAI
- OutputPublish searchable topic index to NotionNotion
What it does
Turns a finished Zoom meeting into a navigable Notion page: each chapter has a heading, a one-line summary, and a deep link back to that moment in the recording.
When to use it
For teams that record customer calls, all-hands, or design reviews and want a skimmable, searchable archive instead of an hour-long video nobody rewatches.
How it works
- 1Zoom fires the recording-completed webhook with the meeting ID and recording assets.
- 2The flow pulls the VTT transcript (or sends audio to a Hugging Face ASR model when no transcript exists).
- 3A Hugging Face topic-segmentation model splits the transcript into coherent chapters with start timestamps.
- 4An OpenAI call writes a short title and summary for each chapter.
- 5The flow assembles a Notion page: a chapter list with timestamps that link to `recording_url#t=` jump points, plus full searchable transcript text.
- 6The Notion page URL is the final output, ready to drop into the meeting calendar event or wiki.
Set it up
What you configure once, before turning it on.
- 1Connect ZoomMeetings, recordings, transcripts.
- 2Connect Hugging FaceModels, datasets, spaces — the open-source hub.
- 3Connect OpenAIModels, embeddings, files.
- 4Connect NotionPages, databases, comments.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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