AI Route Optimisation Platform
Case Study

The challenge

A regional logistics company operating 85 vehicles across multiple depots was using basic GPS navigation and manual route planning. Dispatchers spent 2 hours each morning manually planning routes, and fuel costs were increasing year-on-year despite no volume growth.

What we built

• Multi-constraint route optimisation incorporating delivery windows, vehicle capacity, driver hours, fuel costs, and traffic patterns
• Real-time dynamic re-routing when exceptions occur (delays, failed deliveries, new urgent orders)
• TMS API integration for seamless dispatch workflow — no manual data entry for drivers
• Automated ETD prediction with customer notification on exceptions
• Driver performance analytics and coaching insights dashboard

The results

The solution delivered measurable results within weeks of go-live. The client achieved 22% Fuel cost reduction and 95% On-time delivery, with full ROI achieved within 3 months Break-even achieved.