AI order extraction: read the order, match it to your products
ManualOut's AI order extraction pulls the products, quantities, units and prices out of the message and matches each line to your product list. Every order gets a confidence score, so the ones it is unsure about get looked at.
Last updated
AI order extraction only works with product matching
Your customers use their words, not your codes
A customer writes "12 ctn still water 500". Your system says "Still Water 500ml — 24pk, code 40182". Closing that gap is most of the work — which is why AI order extraction for distributors has to do more than automate data extraction from a document. It has to resolve each line to your catalogue. It is also why a demo on a clean PDF tells you nothing.
The confidence score is the safety net
No system reads every order perfectly. What matters is whether it knows when it is unsure. Every order carries a confidence score, and lines ManualOut cannot match are flagged rather than guessed.
Being confidently wrong is worse than typing
If nobody is checking, a mistake becomes a delivery. Admitting uncertainty is not a weakness in the product. It is the thing that makes the rest of it safe to trust.
Extraction and matching are one step, not two
Plenty of tools stop at pulling text off a document — order data extraction that hands you fields you still have to reconcile against your catalogue. That leaves the hardest part on your desk. ManualOut's AI order extraction resolves each extracted line to your product code, unit and pack size in the same pass, so the output is an order, not a transcript.
Generic document AI was not built for distribution orders
A general OCR or invoice tool reads a page. A distribution order is not a page — it is a customer's shorthand for products that live in your ERP under different names, units and pack sizes, priced by account. Order extraction software for distributors has to carry that context, which is why a tool trained on generic documents matches the words but not the products.
In the product
Everything listed here exists today.
Line-item extraction
Products, quantities, units and prices pulled out and matched to your catalogue.
Product matching
Customers use their own names for your products. ManualOut maps them to your product codes.
Scanned and handwritten documents
OCR handles scanned POs and photographed order lists.
Confidence scoring
Every order carries an AI confidence score, so low-certainty orders get looked at.
In context
The message on the left, the order lines on the right
Products, quantities, units and prices, each matched to your catalogue — with the line it could not place clearly marked, rather than guessed.
priya@harborlinefoods.example
Order — Thursday delivery
Morning, For Thursday please: 12 ctn still water 500 8 ctn cola 330 6 ctn orange squash 1L 30 pcs salted crackers 10 ctn green tea 48 choc wafers Same delivery address as usual. Thanks, Priya
Same order, three channels, identical result. The original stays attached whichever way it came.
| Product | Unit | Qty | Line |
|---|---|---|---|
| Still Water 500ml — 24pk | CTN | 12 | $100.80 |
| Cola Classic 330ml — 24pk | CTN | 8 | $89.60 |
| Orange Squash 1L — 12pk | CTN | 6 | $87.00 |
| Salted Crackers 200g | PCS | 30 | $49.50 |
| Green Tea 250ml — 12pk | CTN | 10 | $98.00 |
| Chocolate Wafer 45gTwo products match this name — needs a decision | PCS | 48 | $34.56 |
- Order value
- $459.46
- Minimum
- $750.00
- Status
- Under minimum
Six lines, one unmatched, and the order is short of this account's minimum. Both reach the desk as decisions rather than typing.
Order data extraction
What ManualOut extracts from every order
AI order data extraction pulls the fields a sales order actually needs out of the message, and matches each one to your records — not just the text on the page.
Products
Each line matched to your product code, even when the customer uses their own name or shorthand.
Quantities
The amount ordered, read against the unit the customer wrote it in.
Units and pack sizes
Cases, pieces, kilos, trays — resolved to the selling unit your ERP expects.
Prices
Any price the customer states, checked against the price list for that account.
Customer item codes and SKUs
The buyer's own part numbers mapped to yours, using that account's history.
Purchase order number
The customer's PO reference captured and carried through to the order.
Delivery date and instructions
Requested dates, addresses and notes pulled from the body or the attachment.
Special notes
Substitutions, part-deliveries and one-off requests flagged rather than lost.
Every format it reads
One extraction engine for every way an order arrives
Automated order extraction should not care whether the order is typed, attached or photographed. ManualOut reads them all and produces the same structured lines.
Order in the email body
Free-text orders written straight into the message are read and turned into structured lines — no attachment required.
PDF purchase orders
Purchase order extraction from templated and customer-designed PDFs, including the references and layouts each buyer uses.
Excel and CSV
Spreadsheet orders are mapped column by column to the right fields, however the customer lays theirs out.
Scanned, photographed and handwritten
OCR handles images of order sheets, scanned POs and faxes, so the awkward inputs are not left for someone to type.
WhatsApp and messages
Messaged orders — text, forwarded notes and photos — are captured and read the same way as email.
Voice notes
Spoken orders are transcribed and run through the same extraction and matching as everything else.
Accuracy at volume
How it stays reliable when four hundred orders arrive at once
Reading one order is easy. Reading every order, every morning, without quietly making things up, is the actual product.
It matches to your codes, not just the text
A customer writes "orange squash 1L". ManualOut maps it to your SKU — your internal product code — with the right pack size and unit of measure, using that account's own order history to break ties.
Every order carries a confidence score
Low-certainty orders are flagged for a person instead of pushed through. A system knowing when it is unsure is the thing that makes the rest of it safe to trust.
Scanned, faxed and handwritten included
Automated order extraction is not just for clean files. Optical character recognition — turning an image of text into characters — handles purchase order extraction from photographed order lists and scanned POs, so the awkward inputs are not left for someone to type by hand.
Questions
AI extraction, answered
What is AI order extraction?
AI order extraction — also called AI order data extraction, order data extraction or automated order extraction — uses AI to pull the products, quantities, units and prices out of an incoming order and turn them into structured lines. ManualOut goes a step further than plain extraction and matches each line to your product list, so what you get is a usable order rather than loose text.
Does it handle purchase order and sales order extraction?
Yes. Purchase order extraction reads the customer's PO — including scanned and photographed ones — and AI sales order extraction turns those lines into the sales order you create. To ManualOut both are the same job: sales order data extraction that ends in a matched, structured order, not extracted text someone still has to check line by line.
Is AI order extraction the same as OCR?
No. OCR turns an image of text into characters — a useful first step for scanned or photographed orders, but only a first step. AI order extraction goes further: it understands which characters are products, quantities, units and prices, and matches each line to your catalogue. OCR reads the page; extraction and matching produce the order.
What document formats can it extract orders from?
Email bodies, PDF purchase orders, Excel and CSV spreadsheets, scanned and photographed order sheets, WhatsApp messages and voice notes. It is one extraction engine for every channel, so an order does not have to arrive in a fixed format to be automated.
How accurate is the extraction?
We do not publish a single accuracy figure, because it depends on your customers and your catalogue, and any number without that context is marketing. What matters more is that every order carries a confidence score, so the orders it is unsure about are exactly the ones your team sees.
What happens when it cannot match a line?
The line is flagged rather than guessed, and the order goes to a person with the original message attached. A confidently wrong order is worse than one that stops to ask.
Does it learn our customers' names for our products?
Yes. Matching uses each account's ordering history, so the shorthand a customer has used for years resolves to the right product code.
Can it read handwritten or scanned orders?
Yes. OCR handles photographed order lists, scanned purchase orders and faxes, not just clean digital documents.
Use cases
Put this to work
See how this fits into automating a whole order channel, end to end.
The rest of the product
Order capture
Take the order however it arrives
Rules & validation
Your rules, checked on every single order
ERP sync
It only counts once it is in your ERP
Customer management
Set each account up once, then let the good ones run
Analytics
See what you are selling, and how well the AI is doing
Review & exceptions
Uncertain orders reach a person, not the warehouse
Data & security
What it can see, and what it can't
See it run on one of your own orders
Send us a real order — the messiest one you can find. We will run it live and show you what happens when it works, and when it does not.