A top-tier global chain of coffeehouses wanted predictive maintenance to improve uptime and enhance customer experience. The volume and complexity of IoT data from thousands of stores with different type and age of equipment rendered predictive maintenance insights nearly unattainable. The client also wanted to explore new use cases with IOT data that could enhance their business operations and create new monetization avenues.

The solution leveraged historical log and issue data to predict maintenance issues and prevent unexpected service interruptions. The solution helped the client to analyze IoT data for new anomalies and issues, some potentially due to operator errors, thus mitigating expensive repairs or replacements. The solution will support new equipment and emerging use cases, and offers the flexibility of deploying on-premises or via the cloud.