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Fleet operational intelligence

AI-powered operational intelligence for modern fleets.

Detect early machinery degradation, improve fuel efficiency, reduce unplanned downtime, and align maintenance planning with decarbonization targets across your fleet.

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Built from real engine-room and vessel operations experience.

Predictive

Signals for condition-based decisions.

Efficient

Fuel and emissions tuned to targets.

Reliable

Lower risk across critical systems.

A modern cargo vessel at sea overlaid with transparent technical schematics and data lines, conveying AI-driven operational monitoring

Operational confidence

Early warnings + actionable recommendations.

Origin story

A team formed by complementary experience, not convenience

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.

Why FleetMind exists

  • The founders recognized a real industry need: operational signals were available but not actionable for decision-makers.
  • Maritime engineering, enterprise execution, AI research, and risk modeling were all required to solve it properly — and the team had all four.
  • Their shared mission turned complementary strengths into a platform built for real vessels, real crews, and real constraints.

Core capabilities

Operational intelligence for engine room realities

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.

Built for real vessels & crews Decision-ready intelligence Enterprise-grade reliability
Realtime

Engine performance analysis

Live monitoring of main and auxiliary engines reveals deviations early so teams can intervene before risk compounds.

Thermal

Thermal balance monitoring

Detects heat distribution shifts across critical systems to safeguard reliability and prevent energy losses.

Turbo

Turbocharger behavior insights

Tracks boost efficiency, pressure trends, and response curves to keep propulsion optimized.

Efficiency

Fuel efficiency trend tracking

Reveals consumption patterns and drift to reduce fuel burn and support decarbonization goals.

Detect

Anomaly detection

AI models flag deviations from normal operating envelopes to prevent unplanned downtime.

Maintain

Predictive maintenance support

Translates sensor patterns into maintenance windows that minimize disruption and lifecycle cost.

Actionable operational intelligence

Reports and alerts engineered for technical managers, enabling faster decisions with clear operational tradeoffs.

Earlier intervention → Lower risk → Higher reliability

Operational impact

Quantified outcomes for fleet performance

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

Operational intelligence built by people who run ships, scale software, and model reliability

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.

Maritime engineering & operations

Built with the judgment and context of technical managers, chief engineers, and fleet operations teams.

Enterprise software architecture

Secure, scalable infrastructure that integrates with existing fleet systems and reporting stacks.

Predictive intelligence

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

Maritime fleets remain the focus, with a clear path to adjacent asset-heavy sectors.

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

Maritime Fleets

Predictive insights tuned to real vessel conditions—engine room operations, fuel systems, and compliance targets.

  • Reduced unplanned downtime through early anomaly detection.
  • Optimized fuel use and emissions reporting.

Method

Operational Intelligence Stack

Sensor fusion, reliability modeling, and maintenance planning workflows that translate to other high-availability assets.

  • Continuous condition monitoring aligned to engineering thresholds.
  • Decision support that integrates with fleet operations teams.

Future Applicability

Adjacent Industries, Same Standards

FleetMind’s intelligence framework is designed for asset-heavy environments with high reliability requirements. Expansion is deliberate and contingent on maintaining maritime-grade rigor.

Aviation Operations

Predictive maintenance workflows for fleet availability and safety compliance.

Future

Wind Turbine Assets

Condition monitoring to minimize downtime across distributed turbines.

Future
Maritime remains the delivery focus today—future verticals will follow proven results and partner demand.

Try FleetMind software today

Experience live operational intelligence built for real-world fleet decisions.

Explore the FleetMind software environment to see how predictive insights, machinery performance signals, and fuel efficiency drivers appear in practice.

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Leadership

Executive operators and AI architects delivering measurable fleet outcomes.

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 · Enterprise

Purpose-built leadership for operational intelligence — focused on reliability, fuel performance, and predictive maintenance that crews and technical managers can trust on day one.

Ops
AI
Delivery
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Chief Executive

Radoslaw Babicz

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.

Mission: move fleets from reactive maintenance to intelligent, data-driven decisions.
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Commercial Leadership

Tomasz Dziki

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.

Focus: scalable partnerships and proven enterprise delivery.
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AI & Research

Bogumił Kamiński

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.

Expertise: advanced analytics architecture and operational research.
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Risk & Modeling

Daniel Kaszyński

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.

Focus: rigorous model validation and decision-grade insights.

FleetMind FAQ

Practical answers for operational decision-makers

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 FleetMind
What does FleetMind analyze onboard?

FleetMind ingests machinery, performance, and operational data streams to detect anomalies, predict degradation patterns, and surface maintenance priorities for critical systems.

How does it help reduce unplanned downtime?

The platform identifies early indicators of equipment stress and aligns them with failure modes, so crews can act before issues become operationally disruptive.

Who is FleetMind designed for?

It supports shipowners, fleet operators, and technical managers who need clear, auditable intelligence across multiple vessels, not just dashboard noise.

Does it support fuel efficiency and sustainability targets?

Yes. FleetMind highlights fuel performance variances, helps optimize operating profiles, and provides evidence for emissions and decarbonization reporting.

How does it fit into existing vessel operations?

FleetMind works with current sensor, automation, and logbook data sources. Outputs are structured for technical teams and shore-based operations without disrupting workflows.

How do we get started?

Start with a technical discovery session. We align on vessel classes, data availability, and priority outcomes, then design a phased deployment plan.

Contact FleetMind

Deploy predictive operational intelligence across your fleet

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.

Request a fleet intelligence consultation

Tell us about your fleet scale, priorities, and operational challenges. We will respond within one business day.

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