Former Xiaomi executive joins embodied intelligence; Xiaoyu Zhizao secures hundreds of millions in Series B+ financing

Entering 2026, the capital narrative in the embodied intelligence track is experiencing a substantive divergence, shifting from blindly chasing the “humanoid” concept in laboratories to scrutinizing the mass production and delivery capabilities in real industrial scenarios. On May 9th, general embodied intelligence technology company Xiaoyu Zhizao announced the completion of its B+ funding round, raising several hundred million yuan. This round was jointly led by BAIC Capital, Fosun RZ Capital, and C&D Emerging, with existing shareholders Huaye Tiancheng and Guizhou Kechuang Angel Fund following on. Didi and Xiaomi co-founder Li Wanqiang also provided additional investment, with Gengxin Capital acting as the exclusive financial advisor and a participating investor. In 2026, as embodied intelligence accelerates its implementation in real industrial scenarios, this investment list stretching across automotive, consumer electronics, and construction heavy industries releases a clear signal that industrial capital is preemptively positioning itself for large-scale applications. Founded three years ago, Xiaoyu Zhizao’s steady fundraising is closely related to the strong background of its core team, all of whom hail from Xiaomi. Its founder and CEO, Qiao Zhongliang, was formerly the head of MIUI development at Xiaomi; co-founder and CTO Wang Wenlin was formerly the general manager of Xiaomi’s Software System Platform Department; and partner Shi Jiangtong was formerly the head of hardware R&D for Xiaomi’s IoT ecosystem, all possessing experience in system development and hardware mass production for devices with hundreds of millions of users. Unlike the frontier algorithmic school of university AI scholars, Xiaoyu Zhizao exhibits typical engineering features of major tech companies. Its technical approach did not choose to start from scratch to tackle extremely complex general hardware bodies. Instead, it established a “one brain, multiple forms” architecture, investing core resources into embodied intelligence brain development and adapting one underlying system to multiple types of hardware. This type of industrial migration strategy, similar to how the smart phone era saw software defining hardware, offers substantial engineering advantages in cost control and software-hardware decoupling. The three new leading investors in this round—BAIC, Fosun, and C&D—represent vehicle manufacturing, diverse industrial ecosystems, and construction heavy industry, respectively. This deep involvement of industrial capital reflects the core evolution of the current embodied intelligence financing market: shifting from paying for technical concepts to paying for scenario-based efficiency and bulk orders. According to public information, Xiaoyu Zhizao has avoided the intensely competitive C-end or lightweight interaction market, instead entering the challenging deep-water scenario of intelligent welding in heavy industry. In 2024, the company reached a large model robot collaboration with Tangshan Panasonic and received a strategic order for over a hundred units from a leading company in heavy industry. Its first batch of mass production deliveries is now underway. At this juncture, industry giants making heavy investments is essentially an endorsement of Xiaoyu Zhizao’s platform technology and closed commercial loop in heavy industrial scenarios. Investors aim, through their investments, to introduce automated productivity into their own industry chains at optimal cost, seeking efficiency advantages in manufacturing transformation. Since the beginning of this year, the embodied intelligence track has shown polarization between top players attracting capital and others being eliminated. Xiaoyu Zhizao’s completion of its B+ round further secures its position among the industrial embodied intelligence cohort, but severe challenges remain ahead. Foremost among these is the engineering barrier to scaled replication. Heavy industry scenarios demand extremely high fault tolerance and stable continuous operation from equipment under extreme conditions. Scaling up from the preliminary delivery of dozens of units to the mass deployment of thousands or tens of thousands exponentially increases the engineering difficulty. The next challenge is the generalization capability of large models. To enable smooth system migration across industries as different as automotive and shipbuilding, it is necessary to continuously improve basic general reasoning capabilities and accumulate massive amounts of industrial know-how data. As the industry focus shifts from the laboratory to the assembly line, competition in embodied intelligence has evolved from a single contest of algorithms to a comprehensive business race that includes cost structure and yield assurance. Fundraising is only the entry ticket; the real test of mass production is just beginning. Risk Warning and Disclaimer The market involves risks, and investment requires caution. This article does not constitute individual investment advice, nor does it take into account the particular investment objectives, financial situation, or needs of any individual user. Users should consider whether any opinions, views, or conclusions contained in this article are suitable for their specific circumstances. Investing accordingly is at your own risk.