CONTENT CREATION

Podcast episode to branded quote cards

When a new episode audio file lands in Drive, transcribe it, pull the five most quotable lines, and generate branded quote-card images ready to post.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew episode audio added to Drive folderGoogle DriveGoogle Drive
  • ActionTranscribe audio with ElevenLabsElevenLabsElevenLabs
  • ActionSelect 5 most quotable lines with OpenAIOpenAI
  • LogicFilter quotes that exceed card length limit
  • ActionRender branded quote-card image per quoteImage generation
  • OutputSave cards to dated Drive subfolderGoogle DriveGoogle Drive

What it does

Turns a finished podcast episode into a set of shareable quote-card images. It transcribes the audio, mines the transcript for the most quotable, self-contained lines, and renders each one as a branded graphic saved back to your library.

When to use it

Run it the moment an episode is mastered and dropped into your shared Drive folder. It is built for shows that want social-ready visuals without a designer touching every episode.

How it works

  1. 1A new audio file appearing in the watched Google Drive folder triggers the run.
  2. 2ElevenLabs transcribes the audio to text with speaker labels.
  3. 3OpenAI scores transcript lines and selects the five most quotable, standalone quotes plus the speaker name.
  4. 4A branch filters out any quote longer than the card's safe character limit so layouts never overflow.
  5. 5The image step renders each surviving quote onto your branded card template.
  6. 6Finished cards are written back to a dated Drive subfolder for review and posting.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect Google DriveDocs, sheets, slides, files.
  2. 2
    Connect ElevenLabsText-to-speech, voice cloning.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect Image generationManaged Nano Banana image renders, metered per image.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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