Tal MorCase study
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Fashion ecommercePrint on demandOrder operations

Every morning, the orders process themselves.

A print-on-demand fashion brand where every order needs the right print file, front and back, in the factory's hands before anything gets made. That used to be a manual morning. Now an AI run does it and sends me a summary.

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Built for a brand I run. Runs every morning.
Tal Mor, Print-on-Demand Order Automation Case Study
The morning run
New ordersPrint filesStatusesTracking
Every morningnew paid orders reach the factory sheet with print files attached
1 full-timeorder processing role no longer needed
Built and running. Happy to show it on a call.
1 full-time
Order processing role replaced
Front + back
Print file resolved for every item
4K
Minimum for AI-made print files

The business

A fashion brand selling all-over-print apparel by independent artists. Each design prints edge to edge, so the factory needs a full-resolution file for the front and often a different one for the back.

The files are spread across years of artist folders and archives, under names that rarely match the product title. And the factory works from a shared spreadsheet: once a row lands, production starts.

IndustryPrint-on-demand fashion
Store platformWooCommerce
Factory handoffA shared Google Sheet the factory works from
Design filesDropbox and Google Drive archives
Built withClaude scheduled agents, WooCommerce API, Google Sheets, Supabase, AI image models
StatusRunning every morning

The problem

  1. Every order needed a file hunt. The right print file could sit in any of dozens of artist folders, under a different name.
  2. Back prints were easy to miss. The product photo shows the front, and a missed back print means a garment made wrong.
  3. Some designs had no file at all. The original was lost, so the only option was to rebuild it.
  4. The factory sheet is live. A duplicate or wrong row gets made into a real garment.
  5. Tracking lived in three places: the factory's dispatch, the shipping hub and the store.

What I built

  1. New order pickup. Every morning it pulls paid orders newer than the last one sent and writes one row per item to the factory sheet: customer, size, product, photos and print files.
  2. Print file search. It searches every folder and archive, then checks each candidate against the live product photo by pixels, not by filename, and stages the right one.
  3. Back print check. It finds the back product photo and decides whether the back needs its own file or is covered by the front.
  4. Rebuild or generate. If the original design elements exist, it rebuilds the file from them. If nothing exists, it generates a 4K print file with an AI image model and checks it against the photo.
  5. Cut and sew check. When the sleeves are a different color from the body, it builds a layout sheet with separate panels instead of one print.
  6. Status and tracking sync. It advances order statuses, copies hub tracking back to the store and marks orders shipped once the shipping window has passed.
  7. Guard rails. It never re-sends an order that is already in the sheet, reads every row back after writing, and flags anything odd to me instead of guessing.

How it runs

StepWhat happens
01. Pull ordersNew paid orders since the last run, nothing older.
02. Write rowsOne row per item in the factory sheet, checked after writing.
03. Find filesFront and back files found and matched by pixels.
04. Fill gapsMissing files rebuilt from elements or generated at 4K.
05. SyncStatuses, tracking and shipped dates updated.
06. SummaryI get a short list: new orders, files found, files generated, anything flagged.

What changed

  1. Order management was a full-time job for one person. Now it runs on its own and I read a summary.
  2. Every order reaches the factory with its front and back file, or a clear flag saying why not.
  3. Lost designs get rebuilt instead of turning into refunds.
  4. Every mistake becomes a rule. When something went wrong once, the fix was written into the run so it can't happen again.

How an AI project with me runs

01

Free call

Sixty minutes on your business. I tell you what I would automate first and what I would leave alone.

02

Map the work

I learn how your business actually runs, then rank what to automate by hours saved and risk.

03

Build one thing

We start with the system that saves the most time, with a person approving anything that touches money.

04

Hand over or run it

You get documentation and training, or I keep running and improving it monthly.

Tal Mor
Order processing used to be my morning. Now it's a summary I read with coffee.

I run my own ecommerce brands, so every system I build has to hold up on a busy Monday, not just in a demo. I build the same kind of system for other businesses: I learn how yours works, decide what to automate, and build it.

20 years operatingAI architect for ecommerceUpwork Top Rated · 100% JSS

Questions about automating print-on-demand orders

Straight answers, from a system that runs every day.

Can you automate print-on-demand order processing?

Yes. Orders, print files, the factory handoff and tracking can all run on their own. The hard part is matching the right file to each order, and that's where most of the work in this build went.

Does this make sense if I use Printful or Printify?

Those already automate the handoff. This build is for brands working with their own factory or a supplier that works from a spreadsheet or email, which is where the manual work lives.

What happens when the AI isn't sure?

It flags the order instead of guessing. Anything uncertain lands in the summary for a person to check.

Can AI create a missing print file?

Yes, at full print resolution and checked against the product photo. It's the last resort, after searching for the original and rebuilding from source elements.

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Want a system like this in your business?

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