GreenSteam updates its fuel saving tool

Malcolm Latarche

Malcolm Latarche · 28 November 2018


Marine software specialist GreenSteam, which is majority owned by BP/Castrol, has launched the next generation of its fuelsaving platform GreenSteam Manager (GSM).

Using unique machine learning technology and an intuitive new user interface the platform provides accurate and clear fuel-saving advice. In a statement the company said that operators will be faced with increased fuel bills after 2020 and need to get the most out of their fuel to stay competitive. Machine learning holds the key to this by being able to build a precise vessel performance baseline.


GreenSteam has been developing machine learning technologies specifically for the shipping industry for over a decade. GSM uses this machine learning technology as its backbone but now offers the output from it as advice through a clear dashboard where a user can clearly see the amount of fuel wasted and, importantly, where it was wasted.

GSM offers different services that lead the user through the discovery of fuel wastage, and the cost of this, through to analysing specific problem areas, such as hull fouling and trim. Beyond fuel savings, the platform also offers the ability to act as a new technology analyser by enabling the assessment of new technologies through identifying and plotting changes in performance.

Daniel Jacobsen, GreenSteam CTO and co-founder commented: “The new GreenSteam Manager is more of a revolution than evolution. By applying our machine learning technology to vessel data enriched with MetOcean and other data, we can provide much more accurate performance baselines than those offered by traditional approaches. However, we wanted to go beyond that; accuracy is a great starting point, but our goal is to make it as easy as possible for users make better operational decisions. Through a user-centric design philosophy and by involving customers in the design, GSM now offers a highly intuitive user experience. You can quickly see the true performance of any vessel, highlight problem areas and make the best decisions to save fuel.”

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