Maritime & Logistics
Top-10 container line - voyage fuel optimization
Predicting fuel consumption across a global fleet under variable weather, cargo, and vessel conditions
The challenge
A major shipping company struggled with unpredictable fuel consumption across their fleet, leading to budget overruns and inefficient route planning. Weather conditions, cargo weight, and vessel performance variations made manual predictions unreliable, and the 68% baseline accuracy left operators unable to commit to bunker decisions or route changes with confidence.
What we built
We developed an AI system that analyzes historical voyage data, weather patterns, vessel specifications, and real-time conditions to predict fuel consumption with 94% accuracy. The system provides actionable recommendations for optimal speed and routing on every leg, integrating with the existing fleet management stack.
What changed
Prediction accuracy
vs 68% manual baseline
Average fuel savings across the fleet
Annual savings
across the entire fleet
Built with
Machine Learning · Weather API Integration · Time Series Forecasting · Vessel IoT Data · Route Optimization
Timeline
6 weeks