Teekay LNG Partners has signed a full fleet partnership to enhance the efficiency of its gas vessels using US-based startup Nautilus Labs ’ software solution.

Nautilus Labs’ platform leverages machine learning to optimise the performance of its vessels and unifies all fleet data.

The partnership between Teekay LNG and Nautilus Labs started in February last year with a five-ship pilot.

Teekay LNG Partners fleet performance superintendent Mark Endall said: “Nautilus ties together a number of our performance monitoring systems, providing real-time insights and visibility into the impact of vessel operations and voyage management decisions so that we can continuously optimise our fleet.”

Teekay will leverage Nautilus software solution to reduce operational costs and act on predictive decision support.

The platform unifies various data sets and different systems of the company to give a detailed analysis of fleet performance in real-time and improve collaboration across its organisation.

The companies are collaborating on the product development front and helping Nautilus Labs build software that fulfils other business needs.

“We’re excited to continue working with the Nautilus team to bring advanced fleet solutions to LNG operations.”

With the help of high-frequency data, Nautilus Labs will build machine learning models that support shoreside and on-ship decisionmaking.

Teekay LNG Partners Business Development, Marine and Technical director David McRoberts said: “It’s great to partner with a forward-thinking tech company like Nautilus Labs. We’re excited to continue working with the Nautilus team to bring advanced fleet solutions to LNG operations.”

Using Nautilus technology, shipping companies can reduce fuel consumption, increase operational efficiency, and optimise fleet performance.

Teekay provides LNG and LPG marine transportation services under long-term, fee-based charter contracts through its interests in 49 LNG carriers, 22 mid-sized LPG carriers, seven multigas carriers and three conventional tankers.