Israeli startup Hailo, developers of a proprietary processing architecture for deep learning on edge devices, has expanded its Series A funding round to $21 million.
Chinese venture capital firm, Glory Ventures, led the investment-round expansion and was joined by existing and other new investors. The investment will enable the company to expand its target markets into China and Hong Kong, complementing its existing markets in Europe, North America, Japan and Korea.
Hailo is also opening registration for the Hailo-8 Fast Track program to select customers and is offering these customers the opportunity to evaluate the initial samples of its high-performance, low-power and small-size Hailo-8™ deep learning processor.
Program participants from various sectors will also be able to develop and prototype their own deep learning products based on the Hailo-8 processor.
Beyond the value it delivers to its strategic focus, the automotive market, Hailo’s breakthrough processor technology serves deep learning applications in a wide range of other markets including surveillance, smart home, IoT and industrial, as well as robotics, AR/VR platforms and wearables.
“The expansion of our Series A round and the addition of Glory Ventures to our investor roll boosts our ability to bring out innovative, powerful and resilient deep learning processors for edge devices, and helps us target the strategic markets of China and Hong Kong,” said Orr Danon, Hailo CEO and co-founder. “The upcoming samples of our Hailo-8 processor will help players in multiple markets overcome the daunting barriers of sufficiently low power consumption, size and cost which currently prevent them from deploying intense deep learning capabilities in their edge products.”
“We have been following the AI compute global landscape closely and found Hailo’s technology to stand out” said Eric Yang, founding partner at Glory Ventures. “We are impressed with the Hailo team and their ability to execute. We look forward to continuing our relationship with them as AI becomes a ‘must-have’ technology in every camera-enabled device.”
