SUMMARIZATION

Dropbox Webinar Drop to ReadMe Digest with Archived Transcript

Watches a Dropbox folder for new webinar recordings, transcribes and summarizes each into a TL;DR plus timestamped highlights, posts a ReadMe digest page.

CategorySummarization
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew recording in Dropbox folderDropboxDropbox
  • ActionDownload + transcribe recordingOpenAI
  • ActionWrite TL;DR + timestamped highlightsOpenAI
  • ActionPublish ReadMe digest pageReadMeReadMe
  • OutputArchive transcript back to DropboxDropboxDropbox

What it does

Monitors a shared Dropbox folder where webinar recordings get dropped (from Zoom auto-export or manual upload). For each new file it generates a transcript, writes a TL;DR and a list of timestamped highlights, publishes a digest page to ReadMe, and writes the full transcript back to Dropbox next to the video as a permanent archive.

When to use it

Use this when recordings already land in Dropbox rather than being pulled live from Zoom, or when you need the raw transcript archived alongside the video for compliance and search. Good for teams whose source of record is Dropbox, not Zoom cloud.

How it works

  1. 1A new recording file appearing in the watched Dropbox folder triggers the flow.
  2. 2The file is downloaded and its audio sent to OpenAI for transcription.
  3. 3OpenAI condenses the transcript into a TL;DR and a set of timestamped highlight bullets.
  4. 4The summary is formatted into a ReadMe-ready digest page.
  5. 5The digest is published to ReadMe.
  6. 6The full transcript is written back to the same Dropbox folder as a sidecar text file.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ReadMeAPI docs, changelog, auth.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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