Case Studies/Quantum Logistics
Logistics

Quantum Logistics

$2.1M saved. 340 routes optimized. Every single day.

quantumlogistics.com/dashboard

$0.0M

Annual Savings

0%

On-Time Delivery

0%

Less Fuel Used

0

Routes Optimized

[ THE PROBLEM ]

What was broken

Quantum Logistics operated 340 daily delivery routes across 8 regions. Route planning was done weekly by 6 dispatchers using static rules. Fuel costs were rising, delivery windows were missed 12% of the time, and last-mile efficiency was hemorrhaging money. They estimated $3M in annual waste from suboptimal routing.

[ THE SOLUTION ]

How we fixed it

We deployed a dynamic route optimization engine that recalculates routes in real-time based on traffic, weather, delivery priority, and vehicle capacity. A demand forecasting model predicts next-day package volumes per region with 94% accuracy, enabling proactive fleet allocation. Drivers receive updated routes via a mobile app with turn-by-turn guidance.

Route Optimization AIDemand ForecastingReal-time GPS IntegrationMobile App (React Native)PythonPostgreSQL

[ THE RESULTS ]

What changed

  • Delivery costs reduced by 31% ($2.1M annual savings)
  • On-time delivery rate improved from 88% to 97%
  • Fuel consumption dropped 23% across the fleet
  • Dispatcher team reduced from 6 to 2 (others promoted to ops management)

We thought we needed more trucks. Turns out we needed smarter routes. GESHER.AI paid for itself in the first quarter.

Marcus Chen

CEO, Quantum Logistics

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