Any document is in play
BOL, AWB, packing list, and labels are photographed and read. Confirm the facts. Do not retype the truck’s paperwork.
The Pallet Dimensioner measures paletized cargo. The phone photographs BOL, AWB, packing list, and labels. Together they build a warehouse receipt without typing, and they keep getting smarter from every confirmation on the dock.
BOL, AWB, packing list, labels, or any other document on the load. Wilkins Operator reads the paperwork the truck actually brought, not a form the clerk retypes.
The Pallet Dimensioner returns dimensions, weight, and photos of the paletized cargo from the sensors on the station.
AI pulls shipper, consignee, references, piece counts, and flags from BOL, AWB, packing list, and labels into one record.
The brain builds the warehouse receipt with the fields the client and the WMS already expect.
The system learns from corrections, trains new people, and warns when a receipt or a load looks wrong.
BOL, AWB, packing list, and labels are photographed and read. Confirm the facts. Do not retype the truck’s paperwork.
Dimensions, weight, and pallet photos arrive from the Pallet Dimensioner without walking a tape around stretch wrap.
AI assembles a warehouse receipt with the characteristics each client needs, mapped to the right WMS entities.
Every confirmation and correction trains the model on how this warehouse names shippers, locations, and exceptions.
The app guides the capture. New operators are productive in minutes, not a week of shadowing the fastest clerk.
Suggestions and alerts fire when a receipt looks incomplete, a pallet does not match the documents, or something on the dock needs a second look.
Dangerous goods marks on documents and labels are flagged at capture, before the load is buried in a slot or a trailer.
What the packing list and the sensors can support travels with the record, including wrap, overhang, and mixed SKUs when they are on the paperwork.
Wilkins Operator is not a camera app with a form behind it. The model reads BOL, AWB, packing list, and labels, the station fills measure, and the warehouse receipt is structured. When an operator fixes a name, the next similar document is faster. When a pallet or a receipt looks off, the floor hears about it before billing or the client does.
It is the Sizelabs paletized receiving stack: Wilkins Pallet Dimensioner captures dimensions, weight, and photos of the load, and Wilkins Operator photographs BOL, AWB, packing list, and labels to build the warehouse receipt with AI/OCR. Operators stop typing. The WMS gets structured data.
The system is sold as the pair because the warehouse receipt is only useful when measurement and document data arrive together. Each product still has its own page if you need to evaluate hardware or the app on its own.
BOL, AWB, packing list, and labels. Pallet OCR extracts the facts those documents carry and maps them into the warehouse receipt with the pallet measure from the station.
Yes. The guided capture gets new operators productive quickly. The model learns from confirmations and corrections, and it raises suggestions or alerts when a receipt or a pallet looks wrong.
See the pair on your mix of paletized cargo, documents, and exceptions — not a slide of empty pallets.
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