Make
maintenance
predictable.
Detect failures
at the source. Predict them months in advance.
The problem
Why most predictive maintenance still fails.
Today's systems chase symptoms — not causes. By the time a vibration sensor triggers an alert, the damage is already advanced.
Failure starts inside
Structural degradation begins at the micro-level — inside the component, invisible to external sensors placed on the housing.
Vibration is a secondary
measurement
Conventional sensors measure a consequence, not the cause. The signal is noisy, attenuated, and arrives too late.
Early signals are ignored
AI alone is not enough
Feed a predictive model with the wrong signal and you get wrong predictions. Garbage in, false alerts out.
The solution
How it works
Applications
Built for assets where failure is expensive.
Wherever an unplanned stop costs more than prevention, Piemacs is the bright fit.
Railway wayside
Axle & bearing health
Electric motors
Rotor & winding faults

Robotic joints
Precision arm fatigue

Pumps & pipes
Pressure anomalies

Wind turbines

HV transformers
Grid asset protection

Hardware and AI — both sides protected.
Two patented layers. One integrated solution. Designed to work together — impossible to replicate separately.
The system
Hardware
The patented sensor
Thin-film MEMS on metal
Shadow installation
Fully customizable to the asset
Resistant to harsh environments
Wi-Fi enabled, low-power
Software
The embedded AI engine
Physics-grounded AI models
Real-time edge processing
RUL forecasting
Prioritized fault detection
Cloud dashboard + open API
Network
Edge + Cloud connectivity
Edge processing on the asset
Secure cloud synchronization
Cloud dashboard + API access
CMMS integration ready
Scalable across your entire fleet
Our team

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