The biggest threat in the maintenance programs is the lack of alert systems that might predict the potential failures in the maintenance actions. Hence, organizations could not identify the faults and could not detect other support facilities’ maintenance. Therefore, the possible loss in production might happen, and productivity might be impacted negatively.
We develop AI-driven models that might detect and diagnose the root cause of equipment faults, operational inefficiencies, and potential system failures. We utilize a different type of data collecting various sources (E.g., building automation systems, HVAC equipment, sensors, actuators, valves, etc.) to analyze the data and provide prioritized recommendations for maintenance, reducing energy, and ensuring high productivity.