Summary
The cloud-based platform ingested high‑volume train telemetry to monitor fleet performance in real time. It used machine learning and digital twins to predict component failures before they occurred. It shifted maintenance from reactive to condition‑based strategies, reducing unplanned downtime and inspection effort. It improved fleet reliability, availability, and operational efficiency across global rail networks.