Ravin.AI, an autonomous platform using artificial intelligence to inspect vehicle condition, has completed a $4 million seed round, led by PICO Venture Partners, with participation from Shell Ventures and automotive entrepreneur Adam Draizin, the company announced.

Ravin was founded in 2018 and is based in London and Haifa, Israel. The company has commercial partners across the U.S. and Europe, including Avis’ Heathrow Airport location, and will use the funding to further develop its technology products and to expand its commercial reach across North America, Europe, and Asia.

The investment marks Shell Ventures’ first Israel investment.

Every five seconds, somewhere in the world, a car is damaged, causing over $100 billion in annual losses. Almost $50 billion of these losses are spent by car owners and insurers on processing and overpaying for damages often caused by someone else.

Ravin uses computer vision and machine learning to detect and analyze vehicle damage with standard cameras and without the use of specialized hardware. The company’s patent-pending technology turns off-the-shelf cameras – CCTV types or mobile phone cameras – into advanced inspection tools, detecting more damage than humans can, while significantly reducing inspection costs.

Car rental companies using Ravin can offer their customers a seamless check-in experience through timely, automated damage detection. This gives them the ability to document and charge customers more fairly, minimizing disputes and optimizing their fleet maintenance.

Ravin also helps used car buyers and dealers detect existing damage, enables vehicle manufacturers to identify defects in new cars, and allows insurance companies to process claims faster.

The technology analyzes camera footage acquired through CCTV cameras or by a person scanning the vehicle with a mobile phone. It then creates a holistic 360-degree vehicle view with accurate damage detection. Ravin’s self-learning platform operates like a professional inspector but performs better – analyzing even previously unseen vehicles with increased accuracy.

Unlike many hardware-based solutions, Ravin’s unique technology can be deployed quickly for new vehicle types using minimal training data. It also doesn’t rely on human users to operate the system or ask them to capture specific images, which may be biased and inaccurate.