AI powers predictive CTV maintenance
A new UK Government-backed project is using AI prediction to improve vessel performance and offshore operations while cutting carbon emissions and costs.
The Enhance Vessel AI project, funded by Innovate UK through the UK SHORE programme, will develop an intelligent predictive maintenance tool for Crew Transfer Vessels (CTVs).
Launching in September 2025, the initiative aims to spot early signs of performance degradation using real-time data and maintenance histories.
“This project will transform how operators manage vessel fleets,” said Chris Huxley-Reynard, CEO of AST Reygar.
“By combining AI with proven systems, we’re enabling smarter decisions that support decarbonisation and improve uptime in offshore operations.”
Real-time insights
Led by AST Reygar, the seven-month collaboration brings together CrewSmart, Seacat Services and ORE Catapult.
The system will build on AST Reygar’s BareFLEET platform and CrewSmart’s maintenance tools, delivering real-time insights directly from working vessels.
Enhance Vessel AI will be tested on Seacat Services’ 18-strong fleet of Crew Transfer Vessels operating in the offshore wind sector.
The idea is to ensure robust development tailored to the practical needs of demanding offshore environments.
By catching early signs of performance issues – whether related to engine health, fuel inefficiencies, or fouling – the software aims to support more timely, targeted maintenance. Not only can this help reduce emissions and fuel consumption, but it also extends machinery life, cuts down the costs of spares and consumables.
With applicability across diesel, hybrid and electric systems, it has potential to scale across the marine industry.
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