AI Logistics & Fleet Intelligence Platform
Predicts vehicle breakdowns 2 weeks ahead from telematics — eliminating unplanned fleet downtime entirely
Overview
End-to-end fleet intelligence platform for a Pakistan-based logistics operator running international routes. Covers real-time tracking, AI route optimisation, driver performance scoring, and predictive maintenance — replacing a patchwork of 4 separate tools with a single unified system.
The Challenge
The operator was running 200+ vehicles across multiple routes with no unified view. Route planning was done manually every morning — taking 3 hours per dispatcher. Vehicle breakdowns were unpredictable, each one cascading into delayed deliveries across that vehicle's route for 3–5 days. Fuel costs were uncontrolled, with no visibility into driver behaviour contributing to excess consumption.
What We Built
A unified platform with four modules: live fleet map (real-time GPS, geofencing, ETAs), route optimisation engine (AI-planned routes factoring traffic, load, windows, and driver hours), driver performance dashboard (speed, braking, idle time, fuel consumption per driver), and predictive maintenance (telematics analysis with maintenance scheduling).
Tech Stack
Key Outcome
200+ vehicles · 18% fuel reduction · zero unplanned downtime
Live Fleet Map
Real-time GPS tracking across the entire fleet on a dark ops-center map, with live alerts surfaced the moment something needs attention.
- Real-time position tracking with per-vehicle status (active, idle, maintenance)
- Live alerts feed: geofence exits, harsh braking, low fuel, offline vehicles
- Click any vehicle to pan the map and open its live detail popup
- Route history playback — replay a vehicle's last few hours of movement
AI Route Optimisation
Replaces a 3-hour manual planning process with a 4-minute AI-optimised route plan across the entire fleet.
- One-click re-optimisation with live distance, time, and fuel savings
- 18% distance reduction vs. the previous manual routing
- Per-driver route table — click a row to highlight it on the map
- Delivery stop sequence with load and timing per stop
Predictive Maintenance
Flags fault risk up to 14 days before it happens, using live telematics instead of waiting for a breakdown.
- Confidence-scored fault predictions per vehicle with urgency ranking
- Maintenance calendar showing scheduled vs. predicted service dates
- Live telematics signals: engine temp, brake pressure, oil viscosity, vibration
- Click any prediction row to inspect that vehicle's telematics
Driver Performance Scorecard
Turns fuel-cost-driving behavioral data into a scorecard drivers actually want to improve — speed, braking, idle time, and fuel efficiency in one view.
- Composite performance score with a 90-day trend line
- Per-metric scoring: speed, braking, idle time, fuel efficiency
- Gamified fleet leaderboard with earned badges
- Rank shown consistently against the same fleet-wide total everywhere
Fleet Cost Analytics
Cost per kilometer by driver and a full maintenance cost breakdown, so fuel and upkeep spend is visible at a glance, not buried in a spreadsheet.
- 30-day fuel cost trend across the whole fleet
- Cost-per-km ranked by driver, color-coded best to worst
- Maintenance cost breakdown: scheduled vs. predictive vs. reactive
- Savings summary: total savings, fuel reduction, and route optimisation impact
The AI Layer
Two AI systems run in parallel. The route optimisation model solves the vehicle routing problem across 200+ vehicles simultaneously — factoring in live traffic feeds, delivery time windows, vehicle load capacity, driver working hours regulations, and fuel cost per route segment. It produces optimised route plans for the entire fleet in under 4 minutes each morning, replacing the 3-hour manual process. The predictive maintenance model analyses telematics data streams — engine temperature, brake pressure, oil viscosity indicators, vibration patterns — against fault signatures from a training dataset of 3,000+ historical vehicle failures. It flags vehicles showing early fault patterns an average of 14 days before a breakdown would occur, enabling scheduled maintenance during planned downtime rather than emergency repairs on route.
Results
- •200+ vehicles managed in real-time
- •Route planning reduced from 3 hours to 4 minutes daily
- •Fuel consumption reduced 18% through route and behaviour optimisation
- •Zero unplanned vehicle downtime in 8 months since deployment
- •Maintenance cost reduced 31% through predictive scheduling
- •Delivered in 42 days