Transport Industry Service
Provider Reduces Invoicing
Processing Time By 50%


Travel & Transportation



Process Automated

Invoice processing


Processing Time







Client Profile

Founded in 1976, the customer is the leading global provider of technology products and services to the travel and transport industry. It provides the mission-critical solutions that account for and manage more than 5 billion financial transactions and 75 million tons of cargo annually. The customer serves as a strategic partner to more than 400 airlines, travel agents and shippers worldwide.


While all invoices include similar fields, they’re sent to accounts payable operations in hundreds, sometimes thousands, of different formats and languages from airline crews across the globe. Invoices were submitted in English, German, French, Italian, Dutch, Polish, Czech and Spanish. The work of manually extracting data from each invoice and entering it into their ERP platform was repetitive and prone to errors. The variety of the formats makes it very difficult for the customer’s existing OCR platform to capture data.


CMR’s  combination of AI, cognitive technology, Machine Learning and pattern recognition, captures invoices from a shared folder. Its method emulates human information processing and extracts key data elements and automatically categorises invoices. CMR has built-in capabilities such as Natural Language Modelling, Data Contextualisation and Data Enrichment providing curated data for downstream systems. CMR automatically flags missing or unreadable information as exceptions and routes tasks to the right people. Each manual intervention improves the accuracy and confidence of CMR’s Machine Learning models and multiple reports are available for further analysis.


CMR delivered a cost-effective invoice processing solution. This streamlined automation choice helped our client achieve a 50% reduction in processing time, with zero errors while ensuring 100% regulatory compliance. CMR saved our client thousands of hours leading to a redeployment of resources to other functions, leading to direct bottom-line savings.