Order intake · 6,000+ SKUs · ~2,500 retailers
Phone calls, emailed lists, PDF sheets, JotForm sign-ups, they all land in different places, and someone in the office re-keys each one into the OMS before a truck can be loaded. This is a concept for the layer that reads those orders where they arrive and drops them into one clean queue, already matched to SKUs. No new portal for your retailers. No re-typing for your staff.
The intake console
Left is how orders actually arrive today. Hit parse and watch each one land in the queue as a structured order, retailer, SKUs, cases, dollar value, ready to push to the OMS. Sample orders, real flow.
Where the hours leak
01
Phone, email, PDF, JotForm. Each retailer orders the way they've always ordered, and every channel needs a human to translate it into the OMS.
02
"The usual 2%" has to become the right code out of 6,000. Staff know it cold, but it's minutes per order, times thousands of orders a week.
03
A mis-keyed case, a missed line, a wrong truck day. Every one is a credit, a redelivery, or a callback, thin-margin mistakes that add up quietly.
The math, not the buzzwords
You don't need me to tell you AI is a thing. You need to know whether this puts hours and dollars back. So here's the arithmetic, in your numbers, with placeholders you can correct in about a minute of conversation.
The point of the beachhead is small and provable: take one channel, say the emailed and PDF orders, and let the queue do the re-keying. Measure it. If it holds, we widen it.
That's not a knock, it's the opposite. A business this dialed-in on the warehouse and the road is exactly where a quiet operating layer pays for itself. The queue above is a mock built on sample orders. The real version runs on yours.
Watch it parse again