AI case study

MolslinjenDynamic pricing

Manual plans couldn't optimize variable vehicle sizes. AI now predicts deck usage, guiding loading to add $2.6M in annual revenue.

Published|1 year ago

Key results

Additional Annual Revenue
$2.6M-3.2M
Fuel Consumption Reduction
3%
Emissions Reduction
~5,000 tons

Result highlights

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The story

Context

Denmark’s largest domestic ferry service transports 15 million annual guests using a fleet of 21 ships, including some of the world’s largest catamarans.

Challenge

Unlike airlines with fixed seats, ferries sell deck space where vehicle sizes vary from three to six meters, making precise capacity planning...

Solution
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Quotes

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The company

Molslinjen logo

Molslinjen

molslinjen.com

Ferry operator for passenger and vehicle transport across Danish domestic routes.

IndustryTravel & Tourism
LocationAarhus, Denmark
Employees1K-5K
Founded1963

The AI provider

Enterprise software, cloud infrastructure, and consumer electronics platform.

IndustrySoftware & Platforms
LocationRedmond, WA, USA
Employees100K+
Founded1975

The implementation partner

Halfspace logo

Halfspace

halfspace.ai

Helped Molslinjen create an AI analytics toolbox and dynamic pricing models via Azure Databricks.

IndustryTechnology
LocationCopenhagen, Denmark
Employees11-50
Founded2020

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