ML Firm To Expand Talent Pool With $70 Million Funding

The company CEO expects the demand for embedded edge computing devices to rise amid the increasing relevance of AI and ML and the need for low-latency solutions.
Krishna Rangasayee, CEO and Founder,
Krishna Rangasayee, CEO and Founder,, a Machine Learning (ML) company delivering solutions for the embedded edge, on Friday announced $70 million of funding led by Maverick Capital, with participation from Point72 and Jericho. Existing investors including Amplify Partners, Dell Technologies Capital, Fidelity Management and Lip-Bu Tan also participated in the round. will use the funds raised for “faster expansion” by hiring more sales and business development people and helping the company meet its customer demand, the company Sales and Automotive Head Harald Kroeger told Outlook Start-Up. 

He added that finding and hiring the right talent and being fast enough to ramp up its demand-meeting capability is one of the top-most challenges.  

To date, the company has raised a total of $270 million, including the latest round, since its first fundraising in 2020. 

The San Jose-headquartered company, which also has its office in Bengaluru, expects increasing customer demand for its first-generation Machine Learning System-on-Chip (MLSoC) that is capable of processing at the edge.  

Embedded edge means devices that perform data processing and analysis locally at the point where data is generated, instead of sending it to a centralised data processing centre or cloud. Embedded Edge sees vast applications in industrial automation and autonomous vehicles, where real-time processing and low latency are critical. operates in the US, Europe and India servicing clients across smart vision systems, industrial automation, robotics, drones, and automotive. In India, is currently seeing significant traction from smart manufacturing (industry 4.0), smart vision, and smart retail sectors. 

“We are also talking to Indian OEMs,” said Kroeger, adding that the company is seeing interest from them seeking advanced ADAS (Advanced Driver Assistance Systems). However, he clarified that the company doesn’t expect these talks to turn into revenue in the coming year.  

With the domination of AI and ML-based applications in the computing landscape for the past decade, the company’s CEO Krishna Rangasayee expects edge computing to become imperative since industries such as automotive safety systems or robotics demand instantaneous decision-making with low latency.  

“The expensive nature of cloud propositions, coupled with the impending integration of AI and ML into every device globally, propels a substantial portion of computing onto the Edge. I would say at least 10 to 20%,” said Rangasayee.  

Earlier this month, BrightDrive, a leader in autonomous driving technology, announced a partnership with, by using the latter’s MLSoC™ to build an advanced hardware platform to deliver new advancements in self-driving systems.    

The new platform sets a new standard for safety, efficiency, and scalability in autonomous driving and is expected to be delivered by late 2026.   

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