- Early StageStartup in initial stages
- Website
- Locations
- Company size
- 11-50 people
- Total raised
- $13M
- Company type
- Enterprise Software CompanyMarine
- Markets
Nautilus Labs careers
Nautilus Labs is advancing the efficiency of ocean commerce through artificial intelligence. With hubs in New York, Paris, and Singapore, the firm is trusted by clients across the globe to help make better, real-time decisions that ultimately unlock transformative outcomes—at sea and on shore. By partnering with Nautilus, ocean shipping leaders can maximize returns for every vessel and voyage while driving cross-team collaboration, greater transparency, and stronger accountability for their companies, shareholders, and the planet we all share.
Ocean shipping consumes over $100 billion dollars of fuel every year, and up to 30% of it can be saved. For owner-operators, reliance on manually collected and analyzed data makes it difficult to optimize fleet performance in real-time. By providing a unified data platform that leverages machine learning, Nautilus helps its clients make better decisions to maximize the return on each ship and every voyage. For our clients, this means they drive closer collaboration, greater transparency, and stronger accountability across their global teams every day.
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Visit our website nautiluslabs.co for more information on our platform.
Ocean shipping consumes over $100 billion dollars of fuel every year, and up to 30% of it can be saved. For owner-operators, reliance on manually collected and analyzed data makes it difficult to optimize fleet performance in real-time. By providing a unified data platform that leverages machine learning, Nautilus helps its clients make better decisions to maximize the return on each ship and every voyage. For our clients, this means they drive closer collaboration, greater transparency, and stronger accountability across their global teams every day.
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Visit our website nautiluslabs.co for more information on our platform.
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Brian O'Clair
Twenty years of software experience from embedded systems, web applications, machine learning, and now managing local and distributed engineering teams.
Total raised
$13M
Funded over
2 rounds
Latest round
Series A (Apr 2019)
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