Industry: Food Distribution
Solution: AI-powered order intake and item matching
Validation scope: Multiple real PO formats and a 546-SKU item master
The Challenge: AI Order Processing Across Different PO Formats
A regional food-distribution company receives customer purchase orders by email in many different layouts. Each order has to be opened, interpreted and matched against the item master before it can move into the order-processing system.
The difficulty was not simply extracting text from a document. Customers described products differently, used different units of measure and sometimes included information in the email / message body or as handwriting on the order. Attachments could also include signature images, spreadsheets or ZIP files that were not valid purchase orders.
At a volume of hundreds of daily orders, repeatedly reading, interpreting and re-keying this information slowed customer confirmation and created opportunities for missed attachments, incorrect quantities and mismatched products.
What Procism Changed
Procism built an AI-powered Order Intake Engine connecting Microsoft Outlook, WhatsApp, Online portal with a ERP matching process. The solution was tested against multiple distinct, real purchase-order formats rather than being trained around one convenient template.
When an order arrives, the workflow identifies the relevant document, extracts the order information and interprets content even when the format varies between customers. It can capture information from the message body and recognize handwritten details where they appear.
The extracted products are then compared with the item master. Procism also introduced fuzzy matching so that products could still be identified when the customer’s description differed from the name recorded in the ERP.
Business rules were built into the flow rather than left for employees to remember manually. Files that could not be processed safely, including Excel or ZIP attachments, were clearly flagged for review instead of being silently ignored or incorrectly interpreted.
Delivery Outcome
During testing, the solution converted varied purchase orders into structured, ERP-ready information while keeping uncertain matches visible for human review. An order confirmation was produced in approximately 60 seconds during the demonstration.
The delivered solution demonstrated more than faster data entry. It established a controlled order-intake process that can handle customer variation, apply operational rules consistently and give employees clear ownership of genuine exceptions.
The Procism Difference
Procism maps the real workflow, removes avoidable complexity, defines controls and exception ownership, and only then applies automation and AI. The result is technology that fits the operation, supports the people using it and remains accountable when the unusual case arrives.
Let’s identify what should be simplified, controlled and automated.
