Predictive Maintenance, Workflow Automation, and Chaos Prevention for Hyperscale Data Infrastructure

Data centers lacked predictive signals and automated workflows, leading to slow responses, cascading failures, and high operational risk.

Built IoT telemetry ingestion, anomaly detection models, workflow automation, resilience graph mapping, and digital twin simulations for early failure prediction.

MTTR reduced by 44%, unplanned downtime by 63%, and 87% of failures detected 24–72 hours early.

Automated maintenance. Predictive anomaly detection. Digital twin for upgrade simulation.