Optimizing fuel consumption in maritime logistics with data and AI-powered bunker management system
CIGen partnered with a UK-based client in the transport and logistics industry to develop an innovative solution that helps shipping companies reduce unnecessary bunker costs. The project aimed to create an online platform that allows vessel owners and operators to identify the optimal bunker port when planning voyages. By leveraging real-time data and advanced algorithms, the platform provides vital information such as fuel prices, deviation costs, and weather updates.
Tech stack
Aboutour client
Our client is a leading player in the transport and logistics industry, specializing in shipping operations. They sought a technological solution that would assist vessel owners and operators in optimizing their fuel purchasing decisions by finding the most cost-effective bunker ports during voyage planning.
The challenge
Shipping companies frequently miss cheaper bunker options, which can increase costs by $200 per day across all voyages. The challenge was to develop a solution that would provide shipping companies with real-time data on over 1,000 ports, enabling them to find the most affordable bunker options while considering numerous variables such as port fees, fuel consumption, and weather conditions.
Collaboration goal
To develop an online platform that helps vessel owners and operators find the optimal bunker port during voyage planning, reducing fuel costs and improving operational efficiency.
Services we delivered
Team composition
CIGen filled the talent and knowledge gap in weeks where the company would have needed months to do so. The line-up included:
The result
Reducing bunker costs with real-time data and advanced algorithms
CIGen successfully built an online portal that allows users to enter voyage details and instantly receive critical information such as the distance to the nearest port, ETA, fuel quantity, and the most cost-effective bunker port. The platform considers over 1,000 ports, providing live prices and taking into account deviation costs, consumption, ROB, and various other factors.