Presear MaintainIQ uses sensor data and machine learning to predict equipment failures before they happen — generating work orders, spare parts requisitions, and maintenance schedules automatically.
Core Capabilities
AI-native capabilities designed to eliminate manual work and surface intelligence at the right moment.
Connects to vibration, temperature, pressure, and current sensors via IoT gateways — processing thousands of data points per second to detect anomaly signatures.
ML models trained on your equipment's historical failure data predict the remaining useful life of critical components with confidence intervals and recommended action windows.
When failure probability crosses a configurable threshold, MaintainIQ auto-generates a work order, assigns it to the right technician, and reserves necessary spares.
AI recommends optimal spare parts stocking levels based on lead times, criticality, and failure frequency — reducing both stockouts and excess inventory.
Real-World Impact
Outcomes achieved by organisations that deployed Presear MaintainIQ as part of GentrikOS.
Predicted compressor bearing failure 11 days ahead, enabling planned replacement during scheduled downtime — avoiding an estimated ₹1.8Cr unplanned shutdown.
Continuous vibration analysis on 6 turbines reduced unplanned outages by 62% in the first year of deployment.
Predictive alerts for kiln shell temperature anomalies enabled early brick replacement, extending campaign length by 18% and saving ₹3.2Cr annually.
Part of
Presear MaintainIQ is one of the modules inside PresearGentrikOS's Heavy Industry OS. All modules share a unified database — so data flows freely without integration overhead. Explore the full OS →
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