AI Route & Fleet Optimization Engine
A delivery company's drivers followed static routes planned manually each morning, leading to wasted fuel, missed delivery windows, and uneven workload distribution.
- 22%
- Fuel Savings
- 95%
- On-Time Delivery
- 150+
- Vehicles Optimized
- 5 mo
- To Delivery
Route planning was done manually by a dispatcher using printed maps and experience-based judgement. Routes didn't account for real-time traffic, delivery time windows, or vehicle capacity constraints. Drivers in one area would be overloaded while others had idle time.
They needed an AI-powered route optimization engine that could dynamically plan and adjust routes based on delivery windows, traffic conditions, vehicle capacity, and driver availability.
We built an optimization engine that generates optimal routes accounting for time windows, traffic patterns, vehicle capacity, and driver schedules. Routes re-optimize dynamically when new orders arrive or conditions change, and dispatchers can override with manual adjustments.
Fuel costs dropped 22%, on-time delivery rates reached 95%, and 150+ vehicles are now optimally routed daily — turning what was a 2-hour manual planning process into an automated 5-minute operation.
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