Client Deliverable Repurposing Workflow (Delivery)

Client Deliverable Repurposing Workflow (Delivery)

1. 01

   Define the deliverable set for each client meeting type

   Map recurring meetings (status, discovery, QBR) to standard outputs: summary, action items, follow-up email, and optionally a compliance log. This prevents ad-hoc formatting and sets expectations for the client.

2. 02

   Configure the meeting assistant to auto-join and capture

   Ensure the tool is connected to the calendar and joins the correct video platform. For example, Fireflies can join Zoom, Teams, and Google Meet, while Otter integrates with similar platforms. Verify permissions and recording consent align with client agreements.

3. 03

   Generate the raw transcript and AI summary immediately after the call

   Most assistants produce a transcript and summary within minutes. Fathom offers free unlimited transcription for small teams, making it a low-cost option for high-volume capture. Review the summary for obvious errors before sharing.

4. 04

   Extract and verify action items against the transcript

   AI-generated action items can miss nuance. Cross-check each item against the transcript to confirm the assignee, deadline, and exact ask. Circleback automatically assigns action items to participants, but human verification is still required for accuracy.

5. 05

   Repurpose the summary into client-facing deliverables

   Transform the AI summary into a polished follow-up email, meeting notes for the project management tool, and a slide for the QBR deck. This is where the leverage lies: one capture feeds multiple outputs, saving hours per week.

6. 06

   Store the transcript and deliverables in a searchable archive

   Maintain a central repository (e.g., Notion, CRM, or the assistant's own archive) so any team member can retrieve past decisions. Tools like Fireflies and Circleback offer searchable archives, which support client audits and dispute resolution.

7. 07

   Run a human review gate before sending anything to the client

   AI accuracy is not guaranteed for sensitive client conversations. Have a team member read the final deliverables, correct any misinterpretations, and confirm that all client commitments are captured. This reduces miscommunication risk and protects the agency's reputation.