Engine performance analysis
Live monitoring of main and auxiliary engines reveals deviations early so teams can intervene before risk compounds.
Origin story
FleetMind came together when Radoslaw Babicz and Tomasz Dziki connected their maritime engineering background with enterprise business building and saw a shared gap in how fleets use operational data. As they sought to solve it, Bogumił Kamiński added AI research depth, and Daniel Kaszyński brought data science, predictive modeling, and operational risk expertise grounded in real-world decision environments.
This combination of shipboard reality and advanced analytics made it possible to build state-of-the-art AI algorithms that are proven against operational conditions — not abstract lab assumptions. The team aligned around a single mission: create intelligence that technical managers can trust to reduce unplanned downtime, optimize maintenance, and support decarbonization goals.
Core capabilities
FleetMind combines real vessel data with AI-driven models to surface actionable insights for shipowners and operators. The result is earlier intervention, lower operational risk, and higher reliability across fleets.
Live monitoring of main and auxiliary engines reveals deviations early so teams can intervene before risk compounds.
Detects heat distribution shifts across critical systems to safeguard reliability and prevent energy losses.
Tracks boost efficiency, pressure trends, and response curves to keep propulsion optimized.
Reveals consumption patterns and drift to reduce fuel burn and support decarbonization goals.
AI models flag deviations from normal operating envelopes to prevent unplanned downtime.
Translates sensor patterns into maintenance windows that minimize disruption and lifecycle cost.
Reports and alerts engineered for technical managers, enabling faster decisions with clear operational tradeoffs.
Operational impact
Each pillar represents a measurable business outcome that FleetMind is designed to deliver across modern maritime operations.
Reduced unplanned downtime
Early detection and condition analytics prevent off-hire events and stabilize schedules.
Optimized fuel consumption
AI-driven insights identify inefficiencies and align operations with fuel-saving best practices.
Extended equipment lifecycle
Condition-based maintenance reduces wear and protects mission-critical machinery.
Improved maintenance planning
Forecasting tools align spares, labor, and drydock windows with real asset needs.
Lower operational risk
Visibility into asset health supports safe operations and better decision-making.
Decarbonization support
Operational intelligence aligns fleets with emissions targets and reporting standards.
Why FleetMind
FleetMind combines three disciplines that rarely sit at the same table: maritime engineering and vessel operations, enterprise-grade software architecture, and AI-driven predictive analytics. That cross-disciplinary foundation lets us translate engine room realities into data models that actually fit operational workflows.
The result is a practical bridge between ship operations and artificial intelligence — a platform designed for maintenance planning, fuel optimization, and reliability decisions that matter on board and on shore.
Built with the judgment and context of technical managers, chief engineers, and fleet operations teams.
Secure, scalable infrastructure that integrates with existing fleet systems and reporting stacks.
AI models tuned for machinery reliability, fuel efficiency, and decarbonization targets.
We are not building AI for presentations — we are building operational intelligence for real vessels, real crews, and real-world conditions.
That focus keeps FleetMind grounded in safety, uptime, and the operational constraints that define modern maritime performance.
FUTURE INDUSTRIES
FleetMind is built for shipowners, technical managers, and operators who need measurable improvements in machinery reliability, fuel efficiency, and maintenance planning. The same operational intelligence principles can extend to other complex asset environments, but maritime performance and trust remain the primary delivery today.
Primary Market
Predictive insights tuned to real vessel conditions—engine room operations, fuel systems, and compliance targets.
Method
Sensor fusion, reliability modeling, and maintenance planning workflows that translate to other high-availability assets.
Future Applicability
FleetMind’s intelligence framework is designed for asset-heavy environments with high reliability requirements. Expansion is deliberate and contingent on maintaining maritime-grade rigor.
Predictive maintenance workflows for fleet availability and safety compliance.
Condition monitoring to minimize downtime across distributed turbines.
Operational intelligence for modern fleets
Try FleetMind software today
Explore the FleetMind software environment to see how predictive insights, machinery performance signals, and fuel efficiency drivers appear in practice.
Leadership
FleetMind combines deep maritime operations, enterprise delivery, and advanced analytics leadership. Our team has led engine room performance programs, large-scale enterprise deployments, and AI research agendas — translating complex data into reliable, real-world decisions for fleets.
Combined expertise
Maritime · AI · EnterprisePurpose-built leadership for operational intelligence — focused on reliability, fuel performance, and predictive maintenance that crews and technical managers can trust on day one.
Chief Executive
CEO · Chief Engineer
An Engineer with over a decade in maritime operations, including Staff Chief Engineer and Dry Dock Project Supervisor roles. Led engineering programs for National Geographic-Lindblad Expeditions and Carnival UK with deep expertise in propulsion systems, reliability engineering, and fleet performance optimization.
Commercial Leadership
VP, Business Development & AI Engineering
Entrepreneur with 25+ years in technology and business, and co-owner of Britenet, one of Central Europe’s leading IT services firms. Drives commercial validation, partnerships, financing strategy, and coordinated execution across the founding team.
AI & Research
VP, Data & AI Engineering
Director of the AI Lab at SGH Warsaw School of Economics and Chairman of the Statistics and Econometrics Committee at the Polish Academy of Sciences. Internationally recognized in AI and operations research with 25+ years delivering enterprise analytics programs.
Risk & Modeling
VP, Data & AI Engineering
General Director of DS360, a data science company, and an analytical modeling consultant with 10+ years guiding major global banks through advanced algorithm and risk model implementations. Lecturer at SGH specializing in quantitative modeling, data analytics, and operational risk assessment.
FleetMind FAQ
Built from real engine-room experience, FleetMind focuses on measurable operational outcomes: reliability, fuel performance, and risk reduction.
Need a technical walkthrough?
We can map FleetMind to your vessel types, data sources, and maintenance cadence.
Contact FleetMindContact FleetMind
Speak directly with FleetMind engineers about reliability targets, fuel efficiency gains, maintenance planning, and decarbonization priorities. We tailor deployments to real vessel conditions, machinery constraints, and crew workflows.
Operational focus
Reduce unplanned downtime and stabilize machinery performance with actionable predictive signals.
Efficiency gains
Optimize fuel consumption, plan maintenance windows, and extend equipment lifecycle.
Decarbonization ready
Support emissions reduction targets with verified operational insights and reporting.
Future-ready platform
Built for maritime fleets today, adaptable to aviation and wind operations tomorrow.
Tell us about your fleet scale, priorities, and operational challenges. We will respond within one business day.