
The technology improves safety and vehicle availability by detecting maintenance issues with speed and precision.
Rental gar giant Hertz will upgrade its vehicle maintenance process by partnering with UVeye, a provider of AI-driven vehicle inspection systems, to introduce advanced AI inspection to its U.S. operations.
With more than 500,000 vehicles worldwide, Hertz wants to ensure high maintenance standards for its fleet before, during, and after rentals.
Vehicle assessments in the rental industry have always relied heavily on manual inspections conducted in varying conditions. By implementing UVeye’s advanced AI-driven inspection technology, Hertz can improve the frequency, accuracy, and efficiency of its vehicle repairs, making its rental cars more reliable and available faster to its customers.
“With millions of customers and over 100 years of service around the world, we’re focused on transforming every aspect of our company, including how we maintain our vehicles,” said Mike Moore, EVP Technical Operations at Hertz, in an April 16 news release.
UVeye’s AI-powered camera systems and machine learning algorithms enable real-time, automated inspections of a vehicle’s body, glass, tires, and undercarriage. The technology improves safety and vehicle availability by detecting maintenance issues with speed and precision.
UVeye’s tire treadwear system captures high-resolution images that are instantly analyzed to determine whether a tire needs replacement, reducing the need for manual checks. By complementing manual checks with UVeye’s technology, customers will see more automated checks when picking up and dropping off their vehicles.
Amir Hever, CEO and Co-Founder of UVeye, added, “Our AI-driven inspection systems complement manual checks with consistent, data-backed assessments completed in seconds.”
Starting with Atlanta’s Hartsfield-Jackson International Airport, the first to be equipped with UVeye systems, Hertz and UVeye are rolling out installations across major U.S. airport locations, with full deployment expected by the end of the year.