Viking Analytics

Predicting failure and maintenance of machines can help asset-heavy industrial companies to potentially save billions annually. Predictive maintenance (PdM), as this paradigm is referred to, is powered by AI and machine learning, and is envisioned to be adopted and deployed by several thousands of asset-heavy industrial companies. However, for implementing PdM successfully, high quality labeled dataset is a pre-requisite. That is, the sensor data should capture all the normal operating modes of the machine, failure modes and anomalies, which are essential for implementing PdM. We have a unique, patent-pending platform that enables asset-heavy companies to be “data-ready”. The platform requires only minimal inputs from the subject matter experts and is anticipated to enable PdM solutions to be reliable by an order of magnitude.