Daimler, Uptake Partner to Enhance Predictive Maintenance Tech
Through DTNA’s data-as-a-service model, customers will have access to Uptake’s data-driven insights to help reduce unplanned fleet downtime and maintenance costs.

Uptake Fleet will deploy 65 data-science models to help DTNA customers save money by minimizing their number of unplanned maintenance events.
Photo: Vesna Brajkovic
Analytics software-as-a-service (SaaS) provider Uptake has entered into a commercial agreement with Daimler Truck North America (DTNA), enabling the use of innovative data-as-a-service (DaaS) technology to power Uptake Fleet, the company’s comprehensive predictive maintenance and work order analytics technology for the transportation industry.
Through the DaaS agreement, and upon customer consent, DTNA will facilitate streaming of the necessary data to power Uptake Fleet. Uptake will administer the technology to help fleets optimize vehicle lifecycles and reduce repair costs using predictive vehicle maintenance.
By analyzing information from subsystem sensors and work orders, Uptake can predict vehicle problems in advance of a fault code and recommend corrective actions before they lead to costly repairs, delays, or roadside breakdowns.
Uptake will deploy 65 data-science models to help DTNA customers save money by minimizing their number of unplanned maintenance events. Uptake Fleet also offers real-time intelligence on the performance of individual vehicle parts and subsystems. Using predictive maintenance, operators buy only the parts they need when they need them, and tailor repair schedules to individual vehicles based on their actual usage.
DTNA customers will be able to utilize Uptake’s recently announced new capabilities in Uptake Fleet, effective immediately. Leading the additions is an expanded capability that enables users to predict vehicle failures down to the component level for more detailed and accurate decision-making. Also included in Uptake Fleet’s enhancements is support for a number of popular sensor analytics endpoints, which fleets can leverage to optimize their maintenance scheduling and further reduce vehicle breakdowns.
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