SUMMARIZATION

Cut and file objection audio snippets from Zoom calls into Dropbox folders by type

Takes a finished Zoom recording, identifies each objection moment, trims the audio to just those segments.

CategorySummarization
Enginesim
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording completedZoomZoom
  • ActionDownload call audio and transcriptZoomZoom
  • ActionFind objection segments and categoriesOpenAI
  • ActionTrim audio into per-objection clipsShell
  • OutputUpload clips to Dropbox category foldersDropboxDropbox

What it does

Builds an audio coaching library by slicing raw objection moments out of full call recordings. The workflow reads the Zoom transcript to find where each objection occurs, cuts the audio to those exact segments, and drops each snippet into a category folder in Dropbox (Pricing, Competitor, Timing, Trust). Reps and managers can then listen to real examples without sitting through whole calls.

When to use it

Use this when your coaching happens by ear, not by reading transcripts, and you want short, labeled audio clips your team can scrub through quickly. Great for onboarding new reps with real handling examples.

How it works

  1. 1A Zoom recording-completed event triggers the run.
  2. 2The workflow downloads the call audio and transcript from Zoom.
  3. 3An AI pass returns each objection's start and end timestamps plus a category label.
  4. 4A shell step uses the timestamps to trim the audio into one clip per objection.
  5. 5Each clip uploads to the matching Dropbox category folder, named with the rep, account, and date.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZoomMeetings, recordings, transcripts.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ShellRun sandboxed commands inside the workspace.
  4. 4
    Connect DropboxFiles and folders.
  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.

Run this workflow in your colony.

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