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AI agent for process improvement analysts

Repeat Issue Problem Record Agent

Recurring issues turned into owned problem records with a tested cause and a confirmed fix

AnalysisIT and developmentOperationsCustomer support
See how it worksGet access
Repeat Issue Problem Record Agent: what goes in, what the agent does and what you get

What it does

The same issue gets fixed ticket by ticket and nobody owns the root cause. Each week this agent groups tickets by symptom, device model, location and software version. It looks for clusters above a count you set and, for each one, opens a draft problem record with the evidence. It tests possible causes, such as a recent update, against the data to see which one fits. After a fix is applied, it watches for new tickets in the cluster and checks whether they drop. The lead approves the problem record and the fix. Edge case: a cluster only appears on one floor, so the agent tests network and power causes first.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Weekly ticket review 2 USES A TOOL Read recent tickets and group by symptom, device,location and version 3 DOES Find clusters above the count threshold 4 DOES Draft a problem record with evidence for eachcluster 5 USES A TOOL Compare cluster dates with the change log and sharedattributes 6 CHECKS THE RESULT Does a likely cause fit the timing and attributes? If not: test the next possible cause and widen the datawindow. Back to step 5. 7 YOU APPROVE Lead approves the problem record and the proposedfix 8 USES A TOOL After the fix, count new tickets in the cluster 9 CHECKS THE RESULT Did new tickets drop below the threshold? If not: reopen the record and test the next cause. Backto step 5. 10 RESULT Problem record closed with the confirmed cause
Read the steps as a list
  1. Weekly ticket review
  2. Read recent tickets and group by symptom, device, location and version
  3. Find clusters above the count threshold
  4. Draft a problem record with evidence for each cluster
  5. Compare cluster dates with the change log and shared attributes
  6. Does a likely cause fit the timing and attributes?If not: test the next possible cause and widen the data window. Back to step 5.
  7. Lead approves the problem record and the proposed fixThe agent waits here for your OK.
  8. After the fix, count new tickets in the cluster
  9. Did new tickets drop below the threshold?If not: reopen the record and test the next cause. Back to step 5.
  10. Problem record closed with the confirmed cause

How it decides

A cluster is a problem when the count passes the threshold within the window. A cause is supported when ticket timing matches a change or shared attribute.

  • Open a record when a cluster passes the count threshold
  • Check recent changes before other causes
  • Close a record only after tickets stay low for two weeks
  • Merge clusters that share a cause

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Cluster threshold (default: 5 tickets in 7 days)
  • Grouping fields
  • Review day
  • Stability period before closing (default: 2 weeks)

What keeps you in control

It always asks you first

  • Lead approves the problem record and the fix

Hard limits

  • Never applies fixes
  • Never closes a problem record without the lead

It stops when

  • Done: the cluster stays below the threshold for two weeks
  • Stop: no cluster passes the threshold

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn one week, 14 tickets reported Wi-Fi dropping on a laptop model after an April driver update. The agent opened a problem record and matched the drop to the update date. The lead approved a rollback of the driver. The check a week later showed 9 new tickets, so the agent reopened the record and found the BIOS version also mattered.

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