Spartan Radar, an industrial automation startup based in Los Alamitos, has raised $15 million in Series A funding to disrupt the assisted driving sensor market.
The funding round, which was led by Prime Movers Lab with participation from 8VC and Mac VC, brings the total funding raised by the startup to $25 million. This investment will allow Spartan to boost its recruiting and production efforts.
David Siminoff, General Partner at Prime Movers Lab and a new member of Spartan Radars’s Board of Directors, referred to the firm’s participation by stating:
“Spartan Radar has the team and technology to scale in both the growing ADAS and emerging AV markets. Spartan Radar’s innovative systems engineering and edge processing expertise inherently gives the company a strategic advantage. The company is extremely well-positioned to capitalize on the growth of autonomy.” said Grayson Brulte who is an Innovation Strategist and Co-Founder of Brulte & Company.”
Spartan Radar was founded in 2020 with the mission to develop sensor technologies that are not only more accessible but also perform better under all conditions. The startup aims to achieve this by using the latest advancements in machine learning and edge-processing to mimic human perception via its Biomimetic Radar™ solution. Nathan Mintz, Spartan Radar Founder and CEO, said in this regard:
“After billions of dollars in investments and several AV companies going public, the industry is finally ready to move beyond R&D to commercialize at scale in defined use-cases like last mile delivery, trucking, and robo-taxi. OEMs and AV developers need safe, robust sensor solutions that are ready to go to market next year and we’re prepared to meet that need.”
With the number of traffic deaths in the United States being the highest since 2006 according to Reuters, the need for better Advanced Driver Assistance Systems (ADAS) is clearer than ever. Spartan believes its technology can help reduce traffic accidents by providing 3 times the range, 10 times the resolution, and 2 times faster detection when compared with legacy sensing technology.