Enterprise Manufacturing Company – Machine Learning and Iot
Business Challenge
A global manufacturer of connected devices lacked real-time visibility into the performance and health of its products in the field. Maintenance was primarily reactive, resulting in unexpected downtime, higher service costs, and reduced customer satisfaction.
Strategic Solution
BroadPoint designed and implemented a cloud-connected system that enabled continuous monitoring and predictive maintenance. Telemetry data from devices was ingested through Azure IoT Hub and enriched with machine learning models to detect anomalies, predict component failures, and recommend proactive service actions. By embedding ML into the workflow, the organization shifted from reactive to predictive operations, significantly improving reliability and customer experience.
Business Impact
Improved product availability through predictive maintenance
Reduced downtime and service costs by anticipating failures before they occurred
Enhanced customer satisfaction with proactive, data-driven support
Continuous learning loop where ML models improved over time with new telemetry data
Tech Stack
Azure IoT Hub, Azure ML, Azure Device Provisioning Service, Web App, Python