Launching AI/ML Capabilities for Enhanced Order Management

The Challenge:

Order management was still weighed down by manual steps. Each purchase order had to be read, keyed in, and checked, which slowed down processing and limited scalability. In markets where online business was already difficult due to government requirements or limited digital infrastructure, these inefficiencies became even more pronounced.

The Turning Point:

Artificial Intelligence and Machine Learning offered a way forward. Instead of treating orders as paperwork to be handled one by one, we could train models to process, check, and improve the workflow at scale. The opportunity was clear, and we started with the North American market.

Our Approach:

• PO Assist development: Built the first AI/ML tool for purchase order assistance in Canada and the United States. The tool parsed purchase order PDFs, captured and filled required fields into the internal order management system, and ran initial quality checks.

• Yield improvement: Prioritized success rates for automated order processing in the first scoped phase.

• Scalability planning: Designed the model as a foundation for rollout in other regions once early success was proven.

The Results:

• Achieved yield success rates more than 80% above the original goal.

• Reduced manual intervention in order processing, with models improving through continuous training.

• Established a framework that could be replicated and scaled globally.

The Impact:

Orders were processed faster, with fewer errors and higher customer satisfaction. Teams were able to step away from repetitive data entry and focus on tasks that required judgment and strategy.