Foretellix plans to use the funding to expand its product portfolio, expand to new countries and work with Toyota and Nvidia on Level 4 vehicle automation.
Foretellix, an Israeli startup that provides simulation technology for improving automated-driving systems, raised $43 million in its latest funding round, the company said Tuesday. Participants include some of the biggest companies in the mobility realm.
The Series C round included investments from Nvidia and Woven Capital, an investment arm of Toyota Motor Corp., among others. Foretellix plans to use the funding to expand into new countries and will work with Nvidia, Woven By Toyota Inc., a software-minded subsidiary of Toyota, and the automaker itself on developing its technology.
Woven and Nvidia will take equity stakes in Fortellix, according to Foretellix CEO Ziv Binyamini. Terms of those investments were not disclosed.
“Verification and validation technology plays a critical role in ensuring the safety and performance of innovative autonomous systems that are accelerating the future of mobility,” said George Kellerman, vice president of investments and acquisitions and managing director of Woven Capital.
Israeli venture capital fund 83North led the series C funding round. Other participants include returning investors such as Volvo, Nationwide Insurance and Jump Capital of Chicago.
Foretellix’s technology reduces the time to validate and test autonomous vehicles, Binyamini said.
It could take hundreds of years to test enough unpredictable road scenarios to make these systems safe for deployment using conventional industry practices, he said. Foretellix claims to accomplish that in less than three years, driving down the cost of AV development.
“You need to deal with millions of scenarios,” he said. “We are the solution.”
Binyamini developed Foretellix’s simulation and verification process from methods he used as a former scientist at Intel, where he worked on the company’s Pentium computer chips. Foretellix’s model creates descriptive language and uses supercomputing to test combinations of scenarios that account for weather, topography and unpredictable behavior from other drivers.