SwiftLogix, a mid-size logistics company operating a fleet of 350 delivery trucks across the Midwest, was losing its competitive edge to tech-forward competitors. Their routing was planned manually by 8 dispatchers who relied on experience, static maps, and gut instinct.
The Inefficiency Tax
* Fuel Costs: $8.2M annually—the single largest operational expense. Trucks were driving 15-20% more miles than necessary due to suboptimal routes.
* On-Time Delivery: Only 82% of deliveries arrived within the promised window. Late deliveries meant penalty charges from major retail clients.
* Driver Overtime: Inefficient routes meant drivers regularly exceeded their shift hours, triggering overtime pay and compliance issues with DOT hours-of-service regulations.
The Complexity Problem
Each morning, dispatchers had to plan routes for 350 trucks, 4,000+ stops, across dynamic conditions (traffic, weather, road closures, customer time windows). The mathematical permutations were astronomical—far beyond human cognitive capacity. A dispatcher could create a "good enough" route in 45 minutes per truck, but it was never optimal.
"We were leaving millions of dollars on the road every year," said the VP of Operations. "We knew AI could solve this, but we needed a partner who understood logistics, not just algorithms."
