We do AI-based predictive maintenance for machine-driven industries.

machine monitoring

data collection

AI analysis & modeling

assesment & forecast

Our sensor & data AI processing solution allows organizations to base service and replacement decisions on real-time equipment condition rather than rigid schedules or intuition.

This data-driven approach delivers measurable gains across core operational metrics:

Reduced downtime: Early detection enables proactive planning and intervention.
Lower maintenance costs: Unnecessary preventive tasks are eliminated, and emergency repairs are reduced.
Extended asset lifespan: Minor faults are addressed before they escalate into costly failures.
Improved safety: The likelihood of hazardous breakdowns in critical systems is significantly reduced.
Higher productivity: Assets operate more reliably, with fewer disruptions to operations.

As a result, predictive maintenance has become essential across industries such as manufacturing, logistics, oil and gas, food and beverage, mining, and utilities. It stands out as one of the most practical and proven entry points for digital transformation.

HOW WE DO PREDICTIVE MAINTENANCE?

At the heart of our predictive maintenance solution is our proprietary sensor technology. We develop custom sensors tailored to each type of machinery – capturing vibrations, acoustic signatures, temperature fluctuations, electrical currents, magnetic fields and many other.

Once collected, these raw signals are transmitted wirelessly* to our AI-powered platform, where advanced algorithms analyze patterns, detect anomalies, and predict potential failures before they occur. By combining specialized hardware with intelligent data processing, we deliver actionable insights that minimize downtime, extend equipment life, and optimize maintenance schedules. Our approach transforms complex machine behavior into clear, predictive intelligence – ensuring reliability, efficiency, and operational safety across every system we monitor.

* using your company wireless infrastructure or with our own LTE / LoRa connection.

high resolution sensors

Connected by wire to the central unit – sensors deliver continuous, full-spectrum insight into machine healt – capturing vibration, temperature, and other critical signals in real time. Designed for harsh industrial environments, the system provides scalable, always-on condition monitoring with clarity and reliability, without adding operational burden.

data acquisition & processing gateway

LTE or LoRa gateway provides a seamless link between your sensors and the cloud, enabling fast, straightforward deployment without the burden of complex IT integration. By removing the need to configure on-site infrastructure, it accelerates installation and simplifies scalability across facilities.

ai powered cloud platform

Intuitive, web-based software that streamlines system configuration, delivers continuous machine monitoring, and enables advanced data analysis with flexible, customisable alerting. Data transmission is encrypted, AWS-managed database, disaster recovery, and customer data ownership.

WHAT DO WE USE?

for high quality data collection we generally use:

high frequency microphone

High-frequency microphones capture the acoustic signature of operating machines. Subtle changes in sound patterns reveal friction, imbalance, wear, or emerging faults long before failure occurs.

accelerometer

Accelerometers and vibration sensors monitor a machine’s movements in real time, detecting subtle oscillations, imbalances, and abnormal patterns. These signals reveal early signs of wear, misalignment, or component fatigue.

humidity sensor

Humidity sensors monitor moisture levels in and around machinery, detecting condensation, leaks, or environmental changes that can affect performance and accelerate wear.

proximity sensor

Proximity sensors detect the presence, position, or movement of machine components without contact. By continuously monitoring gaps, alignment, and relative motion, they reveal misalignments, wear, or mechanical deviations early.

thermometer

Thermometers (temperature sensors) continuously monitor machine heat levels, detecting overheating, abnormal friction, or cooling system inefficiencies. Sudden or gradual temperature changes signal potential failures or component stress.

electrical sensor

Electrical current sensors monitor the flow of electricity through machines, detecting anomalies such as overloads, short circuits, or inefficient operation. Variations in current patterns reveal motor strain, faulty components, or energy losses.

hall sensor

Hall sensors detect the presence, position, or movement of magnetic fields in machines, monitoring rotational speed, shaft position, or alignment. Variations in magnetic signals reveal wear, misalignment, or abnormal operation.

custom sensor

We can design data acquisition sensors of your choice and tailored to your machines, capturing relevant signals, integrating seamlessly with existing systems, and enabling accurate monitoring, diagnostics, and predictive maintenance insights.

DEVICES WE MEASURE

Industries benefit from our sensors by gaining real-time insights into the health and performance of their equipment. Continuous monitoring enables early detection of wear or faults, reduces unplanned downtime, lowers maintenance costs, extends machinery lifespan, and ensures smoother, more efficient operations - transforming data into actionable reliability and productivity gains.

electric & combustion motors

Continuously monitoring vibrations, temperature, and operational signals. Early deviations in these patterns can indicate bearing wear, misfires, imbalance, or overheating. By detecting issues before they escalate, the system enables timely maintenance, reduces downtime, and extends motor lifespan.

gearboxes & bearings

A sensor mounted on a gearbox continuously measures vibration, temperature, and acoustic signals. Subtle changes in these patterns reveal early signs of wear, misalignment, or lubrication issues. By detecting anomalies long before failure, the system enables timely maintenance and prevents costly unplanned downtime.

conveyors

Monitoring vibrations, speed variations, and motor current in real time. Deviations from normal patterns indicate belt wear, misalignment, or mechanical stress. Early detection of these anomalies allows proactive maintenance, reducing unexpected breakdowns, extending equipment life, and ensuring smooth, uninterrupted conveyor operation.

pump stations

Tracking vibration, pressure, flow, and temperature. Changes in these signals can reveal early signs of cavitation, seal leaks, impeller wear, or misalignment. Detecting these issues in real time allows proactive maintenance, preventing unexpected failures and ensuring reliable, efficient pump operation.

hvac devices

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IT WORKS!

science & evidence driven

We’ve proved our point – we know how to develop and implement predictive maintenance solutions – we harness the power of AI to turn sensor data into actionable insights, enabling smarter, proactive equipment management.

Piotr Kmita

Mechanical engineer passionate about artificial intelligence and its applications in predictive maintenance – broadly defined as predicting machine service needs before a failure occurs. piotrkm@gmail.com

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discover the benefits

Lower Operating Expenditure

Condition-based maintenance eliminates guesswork and avoids unnecessary service activities. By addressing issues only when indicators show real degradation, organizations reduce unplanned interventions and significantly limit high-cost emergency repairs.

Higher Equipment Availability

Early detection of wear and failure patterns prevents sudden stoppages and cascading disruptions across production. This is particularly valuable in high-throughput operations where even short outages have disproportionate impact.

Extended Asset Value

Continuous monitoring helps machinery operate within optimal parameters, slowing degradation and delaying capital replacement. Assets deliver more productive hours over their full lifecycle.

Smarter Use of Maintenance Resources

Maintenance teams move away from constant reactive response toward planned, evidence-based actions. This improves workload predictability, reduces pressure on staff, and supports more efficient workforce allocation.

Safer and More Compliant Operations

Equipment maintained based on real condition data is inherently safer to operate and more likely to remain within regulatory limits, particularly in environments governed by strict safety and quality standards.

Easy Expansion Across Operations

Predictive maintenance platforms are designed to grow with the organization. They can start with a limited deployment and scale across multiple sites without requiring major changes to existing infrastructure.

Operational Confidence

Continuous insight into machine health removes uncertainty. With potential issues identified well in advance, teams gain confidence that assets are under control, reducing the risk of after-hours emergencies and unplanned interventions.

Insight-Led Strategic Decisions

Rich operational data enables deeper analysis of failure mechanisms, refinement of maintenance strategies, improved investment planning, and objective performance comparison across assets and sites.