FastFreight Cuts Operational Costs 28% With AI Route Optimization
Results at a glance
28%
Operational cost reduction
Primarily fuel and overtime savings
$1.18M
Annual fuel savings
From $4.2M to $3.02M
84% → 97%
On-time delivery performance
Exceeds 95% client SLA
2 hrs → 3 min
Daily route planning time
Dispatchers freed for exception management
The Challenge
FastFreight operated a fleet of 180 vehicles across 3 regions. Route planning was done manually by dispatchers — a process that took 2 hours each morning and produced routes that were 15–20% longer than optimal. Fuel costs were the company's second-largest expense at $4.2M annually, and on-time delivery performance was 84% against a client SLA of 95%.
Our Solution
We built an AI dispatch and route optimization system that ingests all delivery orders, vehicle locations, capacity, driver schedules, traffic patterns, and historical delivery time data — and generates optimal routes in under 3 minutes. Dynamic re-routing handles delays in real time.
How We Built It
- 1
Integrated with FastFreight's TMS (Transportation Management System) and GPS fleet tracking
- 2
Built historical data pipeline for traffic patterns, delivery time actuals, and driver performance
- 3
Developed ML model incorporating 40+ variables: distance, traffic, vehicle capacity, time windows, driver hours
- 4
Implemented real-time dynamic re-routing when delays exceed 15 minutes
- 5
Built dispatcher dashboard with drag-and-drop override capability
- 6
Integrated customer notification system for real-time ETA updates
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