CONTENT CREATION
Auto-Generate Pull-Quote Graphics from Webinar Transcript
Extracts the most quotable lines from a webinar transcript and renders branded pull-quote graphics.
How it runs
The automated pipeline, trigger to output.
- TriggerNew transcript file added to Drive folderGoogle Drive
- ActionExtract top quotable lines with scoresOpenAI
- LogicKeep quotes above threshold, cap at five
- ActionRender branded pull-quote graphicsImage generation
- OutputFile graphics + captions in Notion (Ready for Social)Notion
What it does
Reads a webinar transcript, mines it for the three to five most shareable quotes, and turns each into a branded pull-quote graphic. The rendered images plus suggested captions are dropped into your editorial queue so the social team has scroll-stopping assets ready before the recap blog even publishes.
When to use it
Use it after a webinar when you want visual social assets without a designer manually combing the transcript and laying out cards. Ideal for content and social teams that publish quote graphics alongside recap posts.
How it works
- 1A new transcript file lands in the watched Google Drive folder and triggers the flow.
- 2An LLM extracts the top quotable lines with speaker attribution and a punchiness score.
- 3A logic step keeps only quotes above the score threshold and caps the count at five.
- 4For each surviving quote, an image step renders a branded pull-quote graphic.
- 5The graphics and their draft captions are posted into the Notion editorial queue tagged Ready for Social.
Set it up
What you configure once, before turning it on.
- 1Connect Google DriveDocs, sheets, slides, files.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect Image generationManaged Nano Banana image renders, metered per image.
- 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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