HR & RECRUITING

Exit-Interview Quote Bank with Theme Tags

Transcribes each exit-interview Zoom recording, pulls verbatim anonymized quotes mapped to attrition themes.

CategoryHR & Recruiting
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerExit-interview Zoom recording completesZoomZoom
  • ActionRetrieve recording transcriptZoomZoom
  • ActionExtract and anonymize theme-tagged quotesOpenAI
  • LogicFilter out low-signal quote sets
  • OutputAppend quotes to Confluence quote bankConfluenceConfluence

What it does

Beyond counts, leadership often wants the actual voice of departing employees. This workflow harvests representative anonymized quotes from each exit interview, tags them by attrition theme, and files them in a Confluence quote bank so HR can cite real evidence when proposing retention changes.

When to use it

Use it when numbers alone don't move stakeholders and you need quotable, theme-tagged employee statements to support attrition narratives and policy proposals.

How it works

  1. 1A completed exit-interview Zoom recording triggers the workflow.
  2. 2The workflow retrieves the recording transcript from Zoom.
  3. 3An OpenAI model selects the most representative quotes, strips identifying details, and tags each with one attrition theme.
  4. 4A logic step filters out low-signal or empty quote sets so only meaningful entries proceed.
  5. 5The tagged, anonymized quotes are appended to the Confluence quote-bank page under their theme headings.

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 ConfluenceSpaces, pages, blueprints.
  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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