Aurora Labs raises $8.4 million to bring its self-healing software to cars

Aurora Labs, a company that has created predictive tools that will automatically fix problems with software in cars, has raised $8.4 million in a Series A round of financing led by Fraser McCombs Capital.

Previous investor MizMaa Ventures also joined the round. The Tel Aviv-based company just came out of stealth a few months ago.

Aurora Labs plans to use the additional funds to expand its presence beyond its new offices in Munich, Germany and Tel Aviv headquarters. The company has 17 employees and plans to add a handful more by the end of the year, as well as open sales offices in Detroit and San Francisco, CEO and co-founder of Aurora Labs Zohar Fox told TechCrunch.

Vehicles today have millions of lines of code. As the automotive industry becomes increasingly reliant on software, the risk of glitches impacting the operation of vehicles grows. And it’s already proving to be a costly problem for automakers. Some 15 million vehicles globally were recalled in 2017 for software flaws, according to Aurora Labs.

Aurora Labs developed a platform designed to detect (and even predict) problems and then fix any issues on the fly. It also can provide over-the-air software updates to allow automakers the ability to make swift changes to electronic control unit software.

The company already has a few takers of its tech; Aurora Labs has locked in three unnamed automakers as customers and pilots are underway.

The company’s tech might be useful for today’s connected cars. But Aurora’s co-founders Fox and Ori Lederman see an opportunity with the wave of autonomous vehicles that will be deployed in the future.

“The number of lines of code in vehicles is already roughly 150 million and is only expected to climb,” Fox said, adding that quality assurance misses about 15 percent of the average 15 to 50 errors for every thousand lines of code. This stat highlights the need for solutions that can predict downtime events before they cause safety issues, he added. 

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