Case study:
The customer
Maran Tankers Management: A ‘Safety First’ crude shipping company
Maran Tankers Management Inc. (MTM) is the crude oil transportation arm of veteran group shipping corporation. Angelicoussis Group, which operates nearly 150 wholly owned vessels. As a leading operator, MTM provides services for some of the world’s largest oil producers. The company is known for its emphasis on service, safety, operational excellence, minimal environmental impact, and highly cost-effective management. The company’s mission and strategic goals include “zero accidents, oil spills, loss of process, or lapses in security.”
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51
Total vessels installed (2024)
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3.6M+
Nautical miles sailed (2024)
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20.1K
GB collected data (2024)
The challenge
Always on the lookout for safety innovation
Maran Tankers Management has long been committed to building a strong safety culture both on board and ashore. As fleet operations expanded and navigational environments became more complex, the company set out to further strengthen situational awareness, decision-making confidence, and consistency across its global fleet.
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Supporting officers in demanding conditions
MTM wanted to give bridge teams clearer, real-time awareness during night operations, low visibility, and congested waters, enabling officers to identify developing situations earlier and maintain safe margins with confidence.
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Managing complexity in high-traffic environments
Operating across busy ports and trading routes, often alongside small vessels without AIS, required additional visual clarity to support safe navigation and proactive decision-making.
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Reinforcing consistent standards fleet-wide
MTM sought a way to extend its safety culture beyond individual vessels by giving shore teams visibility into real navigational behavior and enabling continuous learning and alignment across the fleet.
Maritime crude oil transport is inherently complex. MTM’s safety-first culture and openness to innovation led the company to adopt Orca AI, giving fleet crews an advanced navigational platform that supports real-time, data-driven decision-making.
The solution
Real-time awareness on ship and shore
Maritime crude oil transport is inherently complex. MTM’s safety-first culture and openness to innovation led the company to adopt Orca AI, giving fleet crews an advanced navigational platform that supports real-time, data-driven decision-making.
Onboard
Real-time awareness on the bridge
MTM uses Orca AI’s SeaPod to give bridge crews an enhanced, real-time understanding of the vessel’s surroundings throughout voyages, regardless of weather or time of day. Using day and thermal cameras integrated with AIS and GPS, SeaPod consolidates visual and sensor data into a single bridge display, helping officers identify potential hazards early, including vessels without AIS, and navigate safely in congested waters and low-visibility conditions where radar performance may be limited.
Orca AI helps the crew get a better understanding of the situation around them so they can make more informed decisions from minute to minute.
For the office
Full visibility into fleet operations
Through the FleetView dashboard, MTM’s shore teams gain visibility into safety trends, manoeuvring behaviour, and close encounters across the fleet. This shared view allows the office to move beyond isolated incidents, reinforce common navigational standards, and support crews through review, guidance, and follow-up. The result is consistent decision-making and a safety culture grounded in real operational behaviour.
The results
74% fewer close encounters across the MTM fleet
A fleet-wide analysis from Q1 2023 to Q2 2024 shows sustained improvement in navigational safety following the deployment of the Orca AI platform. Based on these data insights, Maran Tankers Management adjusted its open-water SMS minimum passing distance thresholds from 2 NM to 1.4–1.6 NM, reflecting increased confidence in observed navigational performance and enabling data-driven refinement of safety policy at the fleet level.
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74%
Reduction in close-encounter events
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22%
Increase in average minimum passing distance
See how these results were achieved.
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