SALES

Send Prospect a Mutual Next-Steps Recap After Each Call

Right after a Zoom sales call, drafts a clear recap email of the mutual commitments both sides made and sends it to the prospect via Gmail with the rep cc'd.

CategorySales
Enginesim
Difficultybeginner
Triggerevent
Steps6
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerZoom recording transcript readyZoomZoom
  • ActionExtract mutual commitments from transcript (OpenAI)OpenAI
  • LogicVerify prospect email and shared next-steps exist
  • ActionDraft mutual next-steps recap (OpenAI)OpenAI
  • ActionSend recap email to prospect via GmailGmailGmail
  • OutputLog recap copy to SlackSlack

What it does

This workflow turns each completed Zoom sales call into a concise recap email listing what the rep committed to and what the prospect agreed to, then sends it to the prospect through Gmail with the rep copied so next-steps are confirmed in writing.

When to use it

Use it when deals stall because no one wrote down who was doing what. It's ideal for AEs who want every call to end with a mutual-action recap in the prospect's inbox within minutes, without manual note-taking.

How it works

  1. 1A Zoom recording-completed event triggers the run.
  2. 2The transcript is fetched and OpenAI extracts mutual commitments, separating the rep's actions from the prospect's, each with a stated timeframe.
  3. 3A logic step verifies a prospect email is available and that at least one shared next-step exists; otherwise the run stops.
  4. 4OpenAI drafts a short, professional recap email organized as "On our side" and "On your side".
  5. 5The email is sent via Gmail to the prospect with the rep cc'd.
  6. 6A copy of the recap is logged to Slack for the rep's records.

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 GmailRead, draft, send, label.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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