ORLANDO, Fla. — DataDis is announcing the launch of AI Invoice Processing, a new intelligent module within MIR-RT designed to transform how fleets handle supplier invoices.
“This is more than automation,” said Travis Coffman, executive vice president, DataDis. “It is about giving fleets better data, faster. By combining AI with the operational depth of MIR-RT, we are helping maintenance and finance teams reduce administrative burden while gaining clearer insight into their costs.”
AI Powered Module
Unveiled at the Truckload Carriers Association (TCA) annual meeting, the new module uses artificial intelligence to automatically read and process PDF supplier invoices. By eliminating manual data entry and structuring invoice information automatically, fleets can significantly reduce processing time while improving data quality and operational visibility.
“Manual invoice entry can take between 5 and 30 minutes or more per invoice depending on the complexity,” DataDis said. “With AI Invoice Processing, what once required extensive manual input is now handled in seconds.”
The system extracts key invoice data such as supplier details, parts, job line items, labor times taxes and totals. Each invoice appears in MIR-RT as a pre-filled transaction with an AI confidence level, ready for fast validation. Once reviewed, line items are structured and linked to the appropriate external work order to ensure consistent and reliable reporting.
In addition, the module provides:
- Color-coded indicators to highlight items requiring attention.
- A toggle view between the AI-processed version and the original invoice for fast, reliable validation.
“Beyond massive time savings, the module captures richer and more detailed data than traditional manual entry methods, enabling fleets to improve reporting accuracy, cost analysis and trend identification,” DataDis said.
Dana Guthrie is an award-winning journalist who has been featured in multiple newspapers, books and magazines across the globe. She is currently based in the Atlanta, Georgia, area.
