/ SMART MANUFACTURING

Predictive maintenance made reliable by AI

One too many false alarms, and your teams stop listening. A real outage then goes unnoticed.

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the problem

AI-based predictive maintenance relies on:

Failure prediction

Visual inspection of equipment

Prediction Models (ML)

Quality Sensors & IoT

But:

Models are mistaken in rare cases

Actual conditions differ from the training data

Models degrade over time without us noticing it

Models are mistaken in rare cases

Actual conditions differ from the training data

Models degrade over time without us noticing it

Result

False alarms: alert fatigue, missed real outages

Highly costly unplanned downtime (up to several thousand euros per minute in the

automotive industry, millions per day in the energy sector

Avoidable part replacement costs

False alarms: alert fatigue, missed real outages

Highly costly unplanned downtime (up to several thousand euros per minute in the

automotive industry, millions per day in the energy sector

Avoidable part replacement costs

The real challenge is no longer average performance.
It is real-time reliability in critical and unexpected cases.

TrustalAI brings a real-time layer of reliability to your predictions. We do not replace your models. We guarantee their level of confidence before action.

TrustalAI brings a real-time layer of reliability to your predictions. We do not replace your models. We guarantee their level of confidence before action.

TrustalAI brings a real-time layer of reliability to your predictions. We do not replace your models. We guarantee their level of confidence before action.

Our solution applied to maintenance

Add a confidence interval to each failure prediction (IIoT sensors + ML)

Detect model drift before they become unreliable

Makes visual inspection of the machine status reliable, image by image

Distinguishes a real alert from a false alarm

Specifically:

Intervention triggered if confidence is high

Human verification if uncertain

Prioritization of truly critical alerts

Intervention triggered if confidence is high

Human verification if uncertain

Prioritization of truly critical alerts

We transform your maintenance models into a controllable, explainable, and certifiable system.

You anticipate breakdowns, while making each alert more reliable.

Fewer unplanned stops

No more alert fatigue

Fewer unplanned stops

No more alert fatigue

Reduced parts costs

Enhanced operator safety

Regulatory compliance

Enhanced operator safety

Regulatory compliance

Reliability of the breakdown prediction

01 No more alert fatigue

02 Anticipated breakdowns before they occur

03 Fewer unplanned stops

04 Reduced part replacement costs

01 Deterioration detected early

02 Reliable inspection without human error

03 Less exposure of operators to hazardous sites

04 Consistent maintenance quality

Visual inspection of equipment

Model drift detection

01 Prediction quality maintained over time

02 Reduced model costs

03 Regulatory compliance

04 Alert before the model becomes unreliable

Switch to reliable predictive maintenance

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