AI AGENTS

Daily support-call pain digest to Confluence

At end of day, an agent reads the day's support call transcripts, ranks the most painful recurring issues.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily end-of-day schedule
  • ActionPull the day's support transcriptsZoomZoom
  • ActionExtract and rank friction pointsOpenAI
  • ActionCompose ranked daily digestOpenAI
  • OutputPublish dated digest page to ConfluenceConfluenceConfluence

What it does

At the end of each business day it reads every support call transcript from that day, identifies the friction points customers hit, ranks them by severity and frequency, and publishes a single digest page to Confluence. Leads get a daily readout of where customers are struggling without listening to a single recording.

When to use it

Use it when support call volume is too high to review manually and you want a recurring written record of the day's top pain points to drive triage and roadmap conversations.

How it works

  1. 1A daily end-of-day schedule triggers the run.
  2. 2The agent pulls all of the day's support call transcripts.
  3. 3It extracts friction points and the emotional intensity behind each one.
  4. 4It ranks issues by a blend of severity and how many calls raised them.
  5. 5It composes a digest: top issues, representative quotes, and affected account count.
  6. 6The digest is published as a dated page under the support space in Confluence.

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.

Run this workflow in your colony.

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