Guide
Purchase order tools compared for B2B wholesalers who receive POs rather than send them. Ranked, with a criteria grid.
01
A customer emails a purchase order. LevelOps reads it whatever the layout, matches each line against your Shopify catalog, applies the pricing that account was promised, and writes a Shopify draft order.
02
Nothing ships without a person. Every order lands as a draft with the source file attached, so the last word stays with your team.
03
Processing goes from about six minutes an order to about one. The measured error rate is 0.5% against 3% for manual entry, which is 6x fewer, and a human still signs off. An erroneous order costs about $250 to unwind.
FAQ
Most of it is built for sending. Procurement teams raise a PO, route it for approval and send it to a supplier. Wholesalers have the opposite problem: POs arrive from customers, in the customer's own layout, and someone has to turn each one into an order.
Because a tool built for raising POs has no reason to read one. If you are on the receiving side, the features that matter are document reading, line item matching against your catalog and applying the price the account was promised.
No. Requiring a template moves the work to your customer and it rarely sticks. Orders are read whatever the layout, whether the PO is a PDF attachment, a spreadsheet or text in the email body.
Line item matching resolves the line to your catalog using the description as well as any identifier, which is what makes it work when the customer wrote their own part number. Anything uncertain surfaces in the draft for a person to confirm.
About $250 to unwind, once you count the pick, the shipping, the credit note and the call. That is the number worth holding against any tool's price.
Yes. The free plan covers the first five successful orders with no expiry, which is enough to run your real POs through and judge accuracy on your own files rather than a demo.
Book a short demo. Bring a real purchase order and we will run it live, so you judge the match and the pricing on your own data.
