The project involves reading PDF packing lists stored in Google Drive, extracting structured data (order number, product names, and quantities), detecting pen color in checkboxes to assign packer identity (with a predefined mapping), and updating a Google Sheet with the results. The workflow should be automated, low-maintenance once set up, and ideally completed under a $1000 budget.
Industry: Fresh & packaged foods
Order Volume: ≈ 1 700 orders per week ( ≈ 6 800 per month )
Current Assets: PDF packing lists in Google Drive, a shared Google Sheet for fulfilment metrics
The fulfillment team hand-checks every PDF packing list, then re-keys order numbers, SKUs, and quantities into a Google Sheet. With nearly 7 000 orders a month, this manual transcription is slow, error-prone, and offers no clear audit trail of which packer prepared each order.
1. Design and implement a hands-off, low-maintenance workflow that
Reads PDFs directly from Google Drive as soon as they land in the folder.
Extracts structured data — order number, product name, and quantity — with high accuracy.
Identifies the packer automatically by detecting the ink colour used to tick check-boxes (e.g., blue = Alicia, black = Ravi, red = Moana).
2. Writes the parsed data into the master Google Sheet in real time, appending a timestamp and packer name for traceability.
3. All configuration, authentication, and error-handling should run in the background with minimal future upke
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