A leading GCC energy operator was facing significant financial losses due to unexpected failures across critical industrial assets, including turbines, compressors, and heat exchange systems. Each outage resulted in major operational disruption and substantial revenue impact during production cycles.
Built data lake integrating 15 source systems (SCADA, CMMS, ERP, IoT sensors). Implemented data pipelines for sensor data and batch pipelines for maintenance logs.
Engineered 200+ features from sensor data (temperature, vibration, pressure trends). Trained ML models (Random Forest, XGBoost) to predict failures 48-72 hours in advance.
Production-ready AI models were deployed with real-time inference capabilities, enabling continuous monitoring and early failure detection across critical assets.
Trained maintenance engineers on using predictions for planning. Established feedback loop: engineers validate predictions, improving model accuracy. Continuous model retraining with new data.
Optimized event throughput, reduced API latency, and implemented intelligent traffic routing for scalability and reliability.
Built a unified data platform consolidating 15 disparate source systems into a single centralized repository, supporting both real-time streaming and batch processing pipelines to enable consistent, scalable, and reliable data access across the organization.
ML models predicting equipment failures 48-72 hours in advance with 87% accuracy
Dashboards showing equipment health scores, anomaly detection, and failure predictions
Shift from reactive to predictive maintenance reducing emergency repairs by 35%
Automated detection of unusual sensor patterns indicating potential failures
Training and tools enabling engineers to use AI predictions for maintenance planning
Building real-time data platform processing 2M events/day for operational intelligence
Reducing MTTR from 4 hours to 12 minutes through observability and automation
We've built AI-powered predictive maintenance systems for energy, manufacturing, and utilities across the GCC. Let's discuss how we can help you reduce downtime and optimize maintenance.