14 January 2026

 

For decades, the maritime industry has invested heavily in safety management systems, layering procedures, audits and compliance frameworks onto increasingly complex vessel operations. Yet despite major advances in ship design, navigation technology and automation, incident investigations continue to point to the same underlying causes: communication breakdowns, decision-making under pressure, fatigue and degraded situational awareness on board.

Against this backdrop, the newly announced collaboration between lomarlabs and Signal Fusion suggests a meaningful shift in how safety and operational performance may be understood and managed in shipping — not by adding another compliance layer, but by embedding contextual, human-centred intelligence directly into day-to-day decision-making.

On 14 January 2026, lomarlabs, the venture catalyst advancing deep-tech solutions for maritime, and human-performance intelligence company Signal Fusion announced a strategic collaboration to deploy a next-generation predictive behavioural intelligence system. A pilot planned for 2026 within Lomar Shipping’s operations will test how “human-readiness intelligence can be embedded into day-to-day operational decision-making to strengthen safety before risk escalates.”

While artificial intelligence is now firmly established in areas such as route optimisation, fuel efficiency and predictive maintenance, this initiative stands out for its focus on the human element of maritime operations — and for its emphasis on transparency, accountability and operational relevance.

The persistent challenge of human factors at sea

The role of human factors in maritime incidents is well documented. Studies by the International Maritime Organization (IMO), classification societies and marine insurers have consistently shown that the majority of accidents involve some form of human contribution, whether through miscommunication, fatigue, poor decision-making or inadequate teamwork. While the exact percentages vary across studies, the pattern is clear: technology alone does not prevent incidents when human performance degrades under pressure.

Yet the tools traditionally used to manage this risk remain blunt. Audits and inspections provide snapshots in time. Incident investigations are, by definition, retrospective. Even near-miss reporting, while valuable, often surfaces risks only after conditions have already deteriorated — and relies heavily on voluntary reporting.

Signal Fusion positions its Readiness, Resilience & Risk Intelligence Platform as addressing this long-standing gap. As described in the press release, the platform “translates concise narrative assessments into decision-ready insights for staffing, training focus and safety actions.” Rather than treating human performance as an abstract or subjective concept, the system seeks to measure how crews communicate, decide and recover during real operational tasks — and how those patterns evolve over time and across conditions.

This approach reflects practices already embedded in other safety-critical sectors. Aviation, rail and road transport have long used structured behavioural observation, crew resource management frameworks and data-driven performance monitoring to reduce operational risk. In aviation, for example, flight data monitoring is complemented by systematic analysis of crew behaviour during normal operations. Maritime, by contrast, has struggled to adopt comparable methods at scale, in part due to the diversity of vessels, trades and operating environments.

From hindsight to operational foresight

The collaboration between lomarlabs and Signal Fusion explicitly reframes safety intelligence as a forward-looking capability. Shipping today operates under tighter schedules, leaner crewing models and increasing regulatory expectations, particularly around safety, environmental performance and reporting. In this context, subtle changes in human behaviour — accumulating fatigue, communication friction, or degraded decision-making — can significantly increase risk long before an incident occurs.

“Traditional checks capture only snapshots; they often miss early indicators that develop long before an incident actually takes place,” the press release states. Signal Fusion’s platform is presented as adding “the missing layer of operational foresight,” measuring how human performance shifts “over time and in context.”

Central to this proposition is explainability. Each insight includes “a clear evidence trace and human-in-the-loop review,” while alerts explain “what changed and why.” This focus on transparency addresses one of the most significant barriers to AI adoption in safety-critical industries: trust. Black-box risk scores that cannot be interrogated or audited are difficult to reconcile with formal safety management systems, regulatory oversight and incident investigation processes.

By grounding insights in narrative assessments and audible snippets, Signal Fusion aligns with the growing emphasis on explainable AI seen across regulated sectors such as healthcare, finance and aviation. For maritime operators, this approach resonates with long-established requirements for traceability, documentation and accountability.

Human-centred AI in a regulated ecosystem

Shipping operates within a uniquely complex regulatory landscape, shaped by international conventions, flag state requirements, port state control, classification society rules and charterer expectations. Any technology that influences operational decisions must integrate with this ecosystem rather than operate alongside it.

The collaboration explicitly addresses this reality. Insights are described as “policy-mapped recommendations,” enabling actions that align with existing safety management systems. Records are positioned as privacy-respecting and audit-ready, designed to support — rather than complicate — compliance obligations.

Maria Kolitsida, Founder & CEO of Signal Fusion, underscores this human-centred and contextual approach: “Human performance is the strongest predictor of operational risk — but only when measured in context. Our AI analyses how teams communicate, decide, and recover during real tasks, grounding every insight in an audible snippet.”

From lomarlabs’ perspective, the initiative reflects a broader ambition to address systemic challenges in maritime operations. Managing Director Stylianos Papageorgiou frames the issue in cultural and operational terms: “The shipping industry is rich with stories of how seafaring once felt glamorous and rewarding, yet today it’s often associated with stress, procedural paperwork, and compliance checklists, leaving many onboard feeling disconnected from their managers ashore.”

That sense of disconnection is widely documented in seafarer welfare research. Longer contracts, reduced shore leave, administrative overload and constant digital reporting have reshaped life at sea. Any technology promising to close the gap between ship and shore must therefore balance insight with trust — enhancing support without increasing surveillance or operational burden.

Testing behavioural intelligence in real operations

The planned 2026 pilot with Lomar Shipping provides a practical proving ground. Operating a diverse fleet across multiple segments, Lomar offers a realistic environment in which to test whether behavioural intelligence can be embedded into everyday operations at scale.

Nicholas Georgiou, CEO of Lomar Shipping, positions the technology as an enhancement rather than a disruption: “This technology offers a valuable and innovative AI platform to enhance our safety management system and support our seafarers in daily operations by removing unnecessary stresses that can lead to simple and, potentially, costly mistakes.”

The emphasis on integration is significant. Historically, safety innovations in shipping gain traction not through wholesale replacement of existing systems, but through pilots that demonstrate alignment with frameworks such as the International Safety Management (ISM) Code and deliver measurable operational value.

Sustainability, workforce resilience and future readiness

While safety is the immediate focus, the implications of the lomarlabs–Signal Fusion collaboration extend further. Decarbonisation, alternative fuels and increasing automation are adding new layers of complexity to ship operations. These changes raise the cognitive and organisational demands placed on crews, introducing risks that cannot be mitigated through hardware alone.

In this context, human-readiness intelligence becomes part of a broader sustainability and resilience agenda. Fewer incidents reduce environmental risk. Better support for crews contributes to retention in an industry facing persistent shortages of qualified officers. And data-driven, auditable safety systems align with the expectations of regulators, insurers and financiers increasingly focused on operational resilience and governance.

The collaboration does not claim to offer a universal solution. Instead, it reflects a maturation in how AI is being applied in maritime: moving beyond asset optimisation towards a deeper understanding of how people operate within complex socio-technical systems.

For an industry that has long acknowledged the importance of the human factor but struggled to operationalise it effectively, the 2026 pilot will be closely watched. If behavioural intelligence can indeed be translated into decision-ready, explainable insights without adding burden or eroding trust, it may mark a meaningful step towards a more anticipatory, human-centred model of maritime safety.

 

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