WebSentinel Predict continuously monitors devices, performing advanced population-based analytics in the Cloud, and delivering actionable insights to browser-based dashboards.
Typically, customers use rules to determine maintenance intervals and the need for repair. This can lead to maintenance actions before they are needed in the case of lightly-used assets and costly repairs if heavily-used assets are not maintained with sufficient frequency. Both increase customer repair bills, reducing return on investment.
By contrast, WebSentinel Predict analyzes key data points continuously extracted from devices, and uses machine learning to determine the need for maintenance and repair based on actual customer use across the population. The result is more-appropriate maintenance schedules based on the customer’s needs, reduced maintenance costs, fewer failures, and higher uptime.
