Use Case
Maintenance of Heavy Equipments
Executive Summary
Predictive maintenance is reshaping how ports and industries manage their heavy equipment by enabling a shift from time-based maintenance schedules to data-driven, condition-based strategies. Unlike traditional preventive or reactive approaches, predictive maintenance uses real-time insights from telematics and IoT devices to preempt equipment failures and optimize performance.
With tools such as a predictive maintenance, organisations can monitor critical metrics like downtime prediction, equipment health, and utilization rates. These innovations not only ensure operational efficiency but also enhance safety by identifying wear and tear before it poses a risk.
Zeliot’s Condense has helped us accelerate our connected mobility journey by ensuring all vehicle data comes directly to TVS. This innovative platform streamlines data management and provides valuable insights for optimizing operations.
Vikas Marwaha
TVS Motors
Ready to make the switch to Condense?
Switching to Condense means embracing a faster, smarter way to build and scale real-time data pipelines. With fully managed Kafka at its core, Condense eliminates the complexity of managing infrastructure, integrating fragmented tools, or dealing with vendor lock-in.
Designed for industry-specific needs, Condense comes with prebuilt connectors, a low-code logic builder, and support for custom transforms—letting you go from data to decision in minutes. Its BYOC (Bring Your Own Cloud) model ensures full data control, seamless scalability, and compliance with your cloud strategy.