How a regional logistics company optimized 1,200+ vehicle fleet using AI route planning, reducing fuel costs by 28% and delivery times by 35%.
SwiftLogistics is a pan-India logistics company operating 1,200+ vehicles, managing 40,000+ deliveries monthly across 50+ cities. The company faced rising operational costs (fuel, maintenance) and increasing customer pressure for faster deliveries. Route planning was manual — dispatch officers used spreadsheets and gut instinct, leading to inefficiency.
GridMatrix deployed an AI-powered fleet management platform with dynamic route optimization, real-time tracking, predictive maintenance, and driver performance analytics — resulting in 28% fuel savings and 35% faster delivery times.
The platform combines Python-based optimization engines with real-time data processing. Route optimization uses a hybrid genetic algorithm + local search to solve VRP in near-real-time. GPS telematics data streams to cloud in real-time via MQTT protocol. ML models for predictive maintenance are trained on 3+ years of vehicle diagnostic data (fuel consumption, engine hours, parts wear). The dispatch dashboard runs on React with WebSocket for real-time updates. Integration with Google Maps API provides traffic-aware routing. All data is encrypted and stored in India-compliant data centers with 99.9% SLA.
SwiftLogistics achieved 28% fuel cost savings and 35% faster delivery times through AI-powered route optimization and fleet analytics. The platform now processes 40,000+ daily deliveries with dynamic re-routing, predictive maintenance preventing 80% of vehicle breakdowns, and driver performance management improving safety. The company expanded from 1,200 to 1,800 vehicles with improved profitability, making SwiftLogistics the most efficient logistics operator in its region.
