The document explains that predictive maintenance enables real-time monitoring of machine health to increase uptime by 10–20% and cut material costs by 5–10%, with one deployment saving a global oil and gas firm about $20M annually. It highlights common challenges such as reactive repairs, manual monitoring, unoptimized resources, and delayed breakdown detection. The platform supports any equipment with time-series data and offers anomaly detection, real-time dashboards, scalability, and secure access control. Page 2 outlines an eight-week POC covering data ingestion, model training, and dashboards, delivering reduced downtime, higher OEE, and high-accuracy predictions.

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