IFS.ai Customer Order Automation

IFS.ai Customer Order Automation uses AI to extract data from uploaded customer purchase orders and pre-fill fields in the Scan Customer Order assistant, reducing manual data entry when creating customer orders.

Manually entering order header and line data from emailed or scanned purchase orders is time-consuming and error prone, especially when documents vary in layout, langugage and quality.

In practice, this means you can upload a purchase order document, have the system read and extract customer details, delivery information, and line items, review the results, and create a customer order - instead of typing everything manually.

The feature provides pre-filled order header fields, suggested customer and delivery address matches, and draft order lines based on document content, supporting faster and more accurate order registration. Output quality depends on the quality and legibility of the uploaded document.

Who This Feature is For and Why It Matters

The feature is designed for roles involved in sales order entry and customer order processing, including:

Use this feature when you need to:

By using this feature, you can:

Where to Find it ?

Access this feature from the Scan Customer Order Assistant.

Page: Scan Customer Order

Produc area: Sales Order

Location: Navigator →  Sales Order →  Scan Customer Order

The assistant guides you through these steps:

On the Review Order step, you can view the uploaded document in the image viewer while reviewing extracted fields.

How the Feature Uses Data

When you upload a document and proceed from the Scan Order step, the feature reads the uploaded file and extracts information to populate fields on the Review Order step.

The feature reads from the document:

Line items: part number, description, unit of measure, and line delivery date

It also uses:

When you upload a document and proceed from the Scan Order step, the feature reads the uploaded file and extracts information to populate fields on the Review Order step.

The feature does not use:

How Matching Works

After the document is read, the system tried to match extracted text to existing data in IFS Cloud. Matching runs in a fixed order for header fields; part lines are matched when you reached the review step.

For implementation details, thresholds, and APIs, see Reference Data Matching Logic in the technical documentation.

Customer Matching

The system selects a Customer using the tax ID / association number and customer name from the document.

Step 1 - Association number (tax ID)

Step 2 - Customer name (if Step 1 did not find a customer)

Excluded customers

Customers marked to be excluded from scan order processing are never selected automatically. 

What you see on review 

Situation Customer Field Scanned Customer Name
Confident Match Populated Shows text from document
No confident match Empty - you select customer Shows text from document
Wrond match Correct Manually Shows text from document

What you should do
: If Customer is empty or wrong, select the correct customer. Order type, currency, language, and delivery address defaults are applied after a customer is set.

Delivery Address Matching

Delivery address matching runs only after a customer is known (matched automatically or selected by you on review).
How it works : 
Situation Delivery Address
Strong address match Suggested delivery address from customer setup
Weak or no match Customer's default delivery address
No customer yet Not set until you select a customer
No shipping address on document Customer's default delivery address

What you should do: Always verify Delivery Address against the ship-to address on the purchase order. Change it manually if the suggestion is wrong.  

Sales Part Matching
Part matching runs when order lines are built on the Review Order step. It uses the part number and description read from each document line.
How it works : What you see on review
Situation Catalog No Scanned Part No/ Description
Exact or fuzzy match found Suggested catalog number Values from document
No match Empty-you select catalog Values from document

What you should do: Review every line. Correct Catalog No, quantity, and unit of measure where the suggestion does not match the purchase order.
 

Supported Documents

Supported formats for extraction:

PDF
PNG, JPEG, JPG, HEIF, TIFF
XLSX, DOCX


Quality considerations:

Unsupported or limited scenarios:


Understanding the Output

The feature populates fields based on the content of the uploaded purchase order. Results are presented on the Review Order step for your review before the customer order is created.
For why Customer, Delivery Address, or Catalog No are filled or left empty, see How Matching Works.

Header fields that may be populated:

Field What you see
Scanned Customer Name Customer name as read from the document
Scanned Association No Tax ID or association number from the document
Customer Matched customer, or empty for you to select
Customer PO No Purchase order number from the document
Wanted Delivery Date Delivery date from the document
Delivery Address Matched delivery address or the customer's default
Order Type, Currency From customer defaults when a customer is set

Line fields that may be populated:

Field What you see
Scanned Part No / Description Values read from the document
Catalog No Suggested catalog number when a match is found
Quantity, UoM, Delivery Date Extracted line details

Not all fields may be populated. Results depend on the quality and content of the uploaded document.
 
Example scenarios:

Enabling and Using the Feature


The feature is available when IFS AI services are enabled, the Scan Customer Order assistant is available in your environment, and you have access to create customer orders. 

Prerequisites

IFS AI / ML services must be enabled in the environment


Configuration of AI models and recipes is described in the technical documentation. No additional end-user configuration is required beyond standard Scan Customer Order access.


Upload and Extract


Review and Refine


Apply


Example Actions

Based on extracted results, you may:

Important to Know