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AI agent for packaging engineers

Transit Damage Root Cause Agent

Transit damage traced to a cause with a tested fix

Transit Damage Root Cause Agent: what goes in, what the agent does and what you get

What it does

Damage claims get paid, but nobody traces them back to the pack design, the lane or the handling. Each week this agent gathers claims, photos, carrier, lane and pack type. It groups claims by product, pack and damage type, and compares rates with volume shipped, not raw counts. For the top group it tests which factor explains most of the damage: a lane, a carrier, a pallet pattern or the pack itself. If no single factor stands out, it adds more data such as weather, warehouse or season and tests again. A spike from one bad truck load is noted but not treated as a design problem. It drafts a finding and a suggested test, such as a compression test at a new load. The packaging engineer approves any design change.

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, continueApprovedNo 1 STARTS WHEN Weekly claims data arrives 2 USES A TOOL Group claims by product, pack and damage type 3 USES A TOOL Calculate damage rates against volume shipped 4 DOES Compare rates across lane, carrier and palletpattern 5 CHECKS THE RESULT Does one factor explain most of the excess? If not: add warehouse, weather or load data and compareagain. Back to step 4. 6 DOES Draft finding and suggested test 7 YOU APPROVE Engineer approves test or design change 8 RESULT Damage finding with action
Read the steps as a list
  1. Weekly claims data arrives
  2. Group claims by product, pack and damage type
  3. Calculate damage rates against volume shipped
  4. Compare rates across lane, carrier and pallet pattern
  5. Does one factor explain most of the excess?If not: add warehouse, weather or load data and compare again. Back to step 4.
  6. Draft finding and suggested test
  7. Engineer approves test or design changeThe agent waits here for your OK.
  8. Damage finding with action

How it decides

It ranks damage groups by rate per thousand shipped and looks for the factor that explains most of the excess.

  • Single-load events are noted, not designed for
  • Compare against volume, not raw claim counts
  • Rank by cost of claims

Make it yours

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

  • Damage rate that triggers review
  • Data fields to group by
  • Weekly or monthly
  • Cost threshold

What keeps you in control

It always asks you first

  • Changing a pack design
  • Changing a pallet pattern

Hard limits

  • Never contacts carriers about claims
  • Never changes specs directly

It stops when

  • Done: finding logged with action
  • Stop: claim data lacks pack type; ask for it

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 happensCrushed corners on 24-count cases ran at 9 per thousand. The first factor check found no clear cause by carrier. The agent added lane data and found one lane at 9 per thousand versus 2 elsewhere, and that lane used double stacking. It proposed a compression test at the double-stack load. The test failed, and the engineer approved a stronger corner board.

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