Cutting Invoice Processing Time by 85% with AI Document Extraction

The Challenge

A mid-sized logistics company processing 6,000+ freight invoices per month was drowning in manual data entry. Three full-time staff members spent their days keying invoice data into the ERP — line items, weight classes, surcharges, accessorial charges. Error rates hovered around 8%, triggering payment disputes with carriers and delayed reconciliation. The finance team estimated they were leaving $180K per year on the table from overpayments that slipped through manual review.

Our Approach

We built a custom AI extraction pipeline tailored to freight invoice formats. The system uses OCR with layout-aware processing to handle the 47 different carrier invoice templates the company receives. A fine-tuned classification model identifies line item types (base rate, fuel surcharge, detention, lumper fees) and maps them to the correct ERP cost codes automatically. We added a confidence-scored review queue: invoices above 95% confidence post automatically, while flagged items route to a single reviewer with pre-populated corrections. The entire system was built in 10 weeks and integrated directly with their existing Microsoft Dynamics instance via a custom API connector.

The Results