Momenta's new round of strategic financing introduces new investors with an overall valuation of more than $1 billion

Momenta, an autopilot company, recently announced that it has completed a new round of financing. This round of strategic investors includes Tencent and many other institutions and ushered in China Merchants Venture Capital, Shanghai Guozi Management Co., Ltd. Guoxin Capital, Suzhou Yuanhe Capital, and CCB International. A number of state-owned background investors, as well as shareholders Weilai Capital, up to the capital, etc.,  continue to follow.

Since its inception in 2016, Momenta has accumulated more than $200 million in funding, with an overall valuation of more than $1 billion, making it the highest-value start-up for the domestic autopilot industry. The company's previous investors include Daimler Group (Mercedes-Benz parent company), Kaihui Sino-French Innovation Fund, GGV Jiyuan Capital, Weilai Capital, Shunwei Capital, Innovation Workshop, Blue Lake Capital, Zhenge Fund, Jiuhe Venture Capital. With the resource blessings brought by the above-mentioned employers, the company that has just turned 2 years old has reached a cooperation intention with multinational car manufacturers and Tier 1 suppliers and simultaneously launched an overseas business.

In response to this financing, Momenta CEO Xudong Cao said: "This round of financing is a very important strategic financing round for the company. Momenta will cooperate with partners in the fields of pre-installation, after-loading, travel, logistics, and big data. Further, promote the safe landing of autonomous driving technology."

It is understood that Momenta's core technologies include environment-aware, high-precision maps and path planning algorithms based on deep learning to better understand and predict the motion trajectory of humans/objects. Mainly to provide customers with different levels of autonomous driving solutions and its derivative big data services and products, covering real-time lane line/roadside detection, driving area detection, 3D vehicle detection human feature point detection and other SDKs.

With the ultimate goal of “building an autonomous brain”, the company has completed three phases of construction: the first phase is the construction of the underlying infrastructure platform; the second phase is based on the underlying platform to establish environmental awareness, high-precision maps, and positioning. A series of software algorithms, such as driving decision planning; the third stage is to form autonomous driving solutions for different scenarios and different levels such as autonomous parking, highways, and urban loops, and urban roads.

In order to show off a muscle, in September 2017, Momenta became one of the first partners of the Baidu autonomous driving platform Apollo 1.5; then in April this year, signed a strategic cooperation agreement with Suzhou, plans to establish a large-scale test fleet in Suzhou In order to promote the automatic driving of the L4 level, it will help Suzhou's smart city construction.

More importantly, on October 16, the company announced that it had obtained the road test license for self-driving vehicles issued by the Shanghai Municipal Government, becoming the first self-driving passenger car startup company to receive this qualification in Shanghai. It can be seen that now, with the support of state-owned background investors, the next step is to focus on the unexploded operation of the relevant regions.

As for the reason why Momenta can obtain large-scale financing in a short period of time, I am afraid it is mainly due to its team background: in the auto-driving field where the competition is almost fierce in the past two years, the startup company is overvalued at this stage, which is the scarcity of talents performed.

Specifically, in addition to Xudong Cao’s previous experience as executive research and development director of Shangtang Technology, the official introduction said that Momenta’s R&D personnel accounted for more than 80% of the team size and had many of the world’s top deep learning experts, including R&D director Shaoqing Ren. He is the author of the framework of the widely used image recognition field, faster-CNN and ResNet, and a number of professional competition champions.

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