AI-Powered Route Optimization for Logistics
A logistics operator was losing 30% efficiency due to manual routing and poor fleet visibility across 200+ vehicles.
Team
8 engineers + 2 data scientists
Timeline
14 weeks end-to-end
Client
Logistics Operator (Middle East)
Outcomes Delivered
32%
Delivery Time Reduction
$1.8M
Annual Cost Savings
97.4%
On-time Delivery Rate
How we delivered it
Conducted a 2-week discovery phase mapping all 200+ vehicle routes, depot locations, and historical delivery data to establish a performance baseline.
Trained a custom routing model on 18 months of historical delivery data, incorporating real-time traffic feeds from Google Maps and weather APIs.
Built a dispatcher dashboard with drag-and-drop route override capability, ensuring human control over AI-generated routes.
Integrated with the client's existing TMS via REST API to avoid disrupting existing billing and customer notification workflows.
Deployed on DigitalOcean with auto-scaling to handle peak demand during Ramadan and national holidays.
What we built
Deployed a custom AI routing engine with real-time traffic integration and predictive demand forecasting.
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