Predictive maintenance using time to live based modeling. This model, based on the components age and machine age, predicts when an existing component may fail.

This model identifies impact of external events (such as extreme weather, local incidents) on supply chain operations. It helps the customer to accurately predict the delays in their procurement process.

The predictive maintenance solution is used to predict the likelihood of failure of machine components. The model takes the telemetry and error log records of machine as input and outputs the fault probability in next 24 hours.

Visual defect detection uses computer vision to identify flaws and defects in manufactured items. This model has been trained on metal sheets and plates and can identify flaws, cracks, dents and scratches on sheets and plates.