Your storefront is clean. Your wholesale business is not, because wholesale does not arrive through a cart. It arrives as an email at 6:40 in the morning listing twelve items in a buyer's own shorthand, half of it abbreviated, some of it a product you renamed last spring. Somebody on your team reads it, finds each item in the catalog, and keys it in. That person is the bottleneck, and every mistake they make ships.
Your Shopify catalog: products, variants, identifiers, and the naming as it actually exists in the store, synced into an internal product index built for matching rather than for browsing. That index is the reference every inbound order is checked against.
On the other side, the order text itself — the email, the transcribed call, the message a buyer sends the same way every week — broken into lines, because an order is not one thing to match. It is twelve small matching problems in a row.
First the catalog sync populates the index. This runs on a schedule, so products added or renamed in Shopify are reflected without anyone maintaining a second list. A stale product list is the most common reason matching systems produce nonsense.
Then inbound order text is matched line by line against that index. Each line is resolved to a real product in your catalog — not a guess at a category, not a fuzzy suggestion box, an actual product a warehouse can pick. Lines that cannot be resolved with confidence are marked as such rather than forced into the nearest option.
Every matched order goes to a human review step before anything is committed. Your team sees each line, the product it was matched to, and what was uncertain. They confirm, correct, or reject. This step is not a limitation we are apologizing for; it is the control that makes the automation safe to run against real customers.
The corrections are the asset. When a reviewer fixes a line, that correction feeds a learning loop, so the next time that phrasing arrives it resolves correctly. The system gets more accurate because your staff did their job, not because anyone sat down to train it. Over months, the review step stops being data entry and becomes a spot check.
API access to your Shopify store with read permission on products and the scopes required for the order workflow you want, authorized by a store owner or a staff account with the rights to grant it. Credentials are stored as secrets, never in code.
We also need access to where the orders arrive — the shared inbox or channel — and time with the person who currently keys them. They know which buyers write what, and that knowledge is what the first version of the matching is built on.
Not without a person. Matching is automated; committing is not. Every inbound order goes through a human review step where your team confirms the matched lines before anything is created. We are deliberate about this because a wrong line on a wholesale order is a wrong pallet on a truck.
It lives in a store in your accounts, under your access controls. We index your catalog and the inbound order text needed for matching. Shopify remains the system of record for products, orders, and customers.
That is the case this is built for. Matching is line by line against your real catalog, and when a reviewer corrects a match, the correction is captured. The learning loop means the shorthand a particular buyer has used for six years stops being a daily problem after your team has corrected it a few times.
You own it — a custom build in your accounts with a named owner on your staff. The catalog index is populated from Shopify through a sync layer, so moving to another commerce platform means replacing that sync rather than rebuilding the matching, review, and learning behavior above it.
Shopify versions its API and deprecates old versions on a published schedule, so this is a maintenance item rather than a surprise. The sync is the only component that talks to Shopify; when a version is retired we update that component. Failed syncs surface as errors, so a stale catalog is visible instead of silently producing bad matches.
Start with a complimentary industry analysis. You leave with the one project worth deploying first.
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