Manufacturing · Logistics
How to automate order entry from emails and PDFs into your ERP
If your team spends hours a day retyping purchase orders from emails and PDFs into your ERP, that work can now be automated reliably, even when every customer sends orders in a different format. This guide explains how it works, where it goes wrong, and how to try it without betting the business on it.
Why order entry is still done by hand
Most manufacturers and distributors have an ERP that can do a great deal once an order is in it. The problem is getting it in. Orders still arrive the way each customer prefers to send them: a PDF purchase order exported from their system, a line or two in the body of an email, a spreadsheet, a scanned document, sometimes a photo taken on a phone.
Each of those has to become the same thing in your ERP: the right customer account, delivery address, your part numbers rather than theirs, quantities in the right units, prices, and a requested date. So someone opens the email, reads the attachment and keys it in. It's slow, it's repetitive, and mistakes made here (a wrong quantity, the wrong delivery address) are expensive by the time they reach the warehouse or the shop floor.
Traditional automation never handled this well because it relied on templates: you told the software exactly where the PO number sits on customer A's form. That breaks as soon as a customer changes their layout, and it never covered the long tail of customers who send a handful of orders a year.
What has changed
Modern AI models read documents much as a person does. They can find the order number, the lines and the delivery address on a layout they have never seen before, and understand an order written in plain sentences in an email body. That removes the template problem, which was the main reason order entry stayed manual.
What AI does not remove is the need for checks. A reliable order entry automation is a pipeline, not just a model: reading the order is one step, and most of the value comes from validating it against your own data before anything touches the ERP.
How automated order entry works, step by step
- Capture. The automation watches the inbox orders arrive in (for example orders@yourcompany.co.uk) and picks up each email with its attachments.
- Classify. Not every email is a new order. It decides whether this is a new order, an amendment, a cancellation, a chaser or something else, and routes it accordingly.
- Extract. An AI model pulls out the header (customer, PO number, delivery address, requested date) and every order line (their part number, description, quantity, unit, price).
- Match and validate. This is where most of the work is. The customer is matched to their account, their part numbers are mapped to your SKUs, prices are compared with the agreed price list, units are converted, and duplicate PO numbers are caught.
- Review exceptions. Anything uncertain, such as an unknown part number, a price that doesn't match or a low-confidence read, goes to a person in a simple review screen with the original document alongside. Everything else goes straight through.
- Post to the ERP. The order is created through the ERP's API, its import function or, for older systems, an automated user. See the section on ERPs below.
- Confirm. Optionally, an order acknowledgement goes back to the customer, and every step is logged so you can see exactly what was read and why.
A worked example
To make this concrete, here is an illustrative example. The numbers are made up, but typical of the businesses this suits; yours will differ.
Will it work with our ERP?
Almost certainly, but how depends on the system. There are three ways to get an order into an ERP, from best to last resort:
- An API. Most current cloud ERPs, such as Microsoft Dynamics 365 Business Central, NetSuite and Sage Intacct, let other systems create sales orders directly. This is the cleanest option.
- A file import. Many older or on-premise systems can import orders from a CSV or XML file on a schedule. Less elegant, but reliable.
- An automated user. If a system has neither, the automation can enter orders through the same screens a person would. It works, but it needs more care because screen changes can break it.
Our team has built high-volume document and email automation in heavily regulated environments, including integrations with legacy systems that had no modern API. The lesson that carries over: the integration is rarely the hard part. Getting the matching rules right (which customer is this, which of our parts do they mean) is what decides whether the automation is trusted.
Where it goes wrong, and how to avoid it
- Part numbers. Customers use their own codes and descriptions. Start from your existing cross-reference data, and let the review screen learn new mappings as your team confirms them.
- Units. "10" might be ten units, ten boxes or ten pallets. Validate quantities against each product's normal pack sizes and flag outliers.
- Amendments and duplicates. A revised PO with the same number shouldn't become a second order. Check PO numbers against open orders before posting.
- Prices. Decide in advance what happens when a customer's price doesn't match yours: flag it, accept within a tolerance, or always use your price list.
- Trust. Keep an audit trail showing the original document next to what was entered. It makes errors easy to trace, and it is what lets your team stop double-checking everything.
How to start without a big project
You don't need to automate every customer at once. A sensible first step is a short pilot:
- Pick the 10 to 20 customers who send the most orders.
- Collect a few hundred of their recent orders together with what was actually entered into the ERP. That becomes your answer sheet.
- Run the automation on them and measure accuracy field by field before anything goes live.
- Go live in shadow mode: the automation prepares each order and a person approves it with one click.
- As accuracy is proven on each customer, let their orders go straight through, and add the next group of customers.
Done this way, you know the accuracy and the time saved from your own data before you rely on it, and your team stays in control throughout.
Frequently asked questions
How accurate is AI at reading purchase orders?
On clear, digitally generated PDFs and emails, modern models read header fields and order lines very accurately. Scanned or handwritten documents are harder. The more important number is how many orders can go straight through after validation, which you should measure on your own orders during a pilot rather than take on trust.
Do we need to replace our ERP?
No. The automation sits in front of your existing ERP and creates orders through its API, its import function or, for older systems, through the same screens your team uses.
Can it handle scanned or handwritten orders?
Scanned typed documents usually work well. Handwriting and poor-quality photos are less reliable, so those are typically routed to the review screen rather than posted automatically.
Is our customer data safe?
It can be. Enterprise AI services can be set up so that your data is not used to train models and is processed in UK or EU regions, and the automation itself can run in your own cloud account. Access controls and an audit trail of every order should be part of the design.
How long does it take to set up?
A focused pilot covering your highest-volume customers can typically be running in a few weeks. Most of that time goes on matching rules and testing against real orders, not on the AI itself.
What happens when the AI gets something wrong?
Validation catches most problems before they reach the ERP: unknown part numbers, price mismatches, unusual quantities and duplicate PO numbers are flagged for a person to check. Anything the model is unsure about goes to review instead of being posted.