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Chaowei Dongli Raises Over 500 Million Yuan in Angel+ Funding Led by Vertex Capital

Chaowei Dongli announced the completion of over 500 million yuan in angel+ series funding, with investors including Vertex Capital, Fangguang Capital, and Wanshi Capital. The funds will be used for foundation model R&D, embodied AI applications, and industry ecosystem expansion. Founded by former Huawei autonomous driving executive Yu Jie, HKU professor Luo Ping, and serial entrepreneur Zheng Cunyuan, the company has launched full-stack products such as the KAI Halo data collection device, KAI World Model, and KAIBot humanoid robot.

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Hyperdimensional Dynamics' 500M+ Angel+ Round: Can a Full-Stack Approach Crack Embodied AI's 'Unconverged' Dilemma?

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At a stage when embodied AI's technical routes have yet to converge, Hyperdimensional Dynamics, with over 500 million RMB in angel+ series funding and a full-stack product matrix, is trying to answer a core question through the co-design of data, body, and model: when the industry is still debating which layer to bet on, is it safer to hold every layer in your own hands?

  • Hyperdimensional Dynamics completed over 500 million RMB in angel+ series funding, with investors including Vertex Capital, Fangguang Capital, and Wanshi Capital; the funds will be used for foundation model R&D, embodied application deployment, and industry ecosystem expansion.
  • The founding team consists of Yu Jie, former Huawei autonomous driving business executive; Luo Ping, professor at the University of Hong Kong; and Zheng Cunyuan, a serial robotics entrepreneur—corresponding respectively to mass-production deployment, model algorithms, and robot body capabilities.
  • The product matrix covers the KAI Halo first-person data collection device, KAI World Model, embodied AI AI Infra, the highly humanoid humanoid robot KAIBot, and the high-DOF dexterous hand KAI Hand; among these, KAI Hand and KAI Halo Lite are already on global sale and have been delivered to industry customers.
Open section navigationFunding and Team: The Starting Point of the Full-Stack Route

Funding and Team: The Starting Point of the Full-Stack Route

Hyperdimensional Dynamics announced the completion of over 500 million RMB in angel+ series funding, with investors including Vertex Capital, Fangguang Capital, and Wanshi Capital. The funds will be used for foundation model R&D, embodied application deployment, and industry ecosystem expansion. The company was founded in July 2025, and its R&D and business already cover multiple links including data, models, bodies, and infrastructure.

The founding team includes Yu Jie, former Huawei autonomous driving business executive; Luo Ping, professor at the University of Hong Kong's School of Computing and Data Science; and Zheng Cunyuan, a serial robotics entrepreneur. The three bring, respectively, complex-system mass-production deployment, model algorithms, and robot body capabilities—this forms the basis for Hyperdimensional Dynamics to advance simultaneously across data, models, and bodies.

Li Wei, executive partner at Vertex Investment, said that the path to realizing embodied AI has still not converged, and when data, models, and bodies are advanced separately, it is difficult to determine which layer the problem lies in; therefore, he values teams capable of defining full-stack standards. Vertex Capital's investment history in robotics includes leading Jizhijia's A+ round in 2017, becoming the sole institutional investor in Unitree Robotics' Pre-A+ round in 2020, and successively investing in companies such as Jingfeng Medical, Songling Robotics, and Songyan Dynamics.

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This article is based on AI Frontline's report on Hyperdimensional Dynamics. The report includes the company's official funding information, founding team backgrounds, product parameters, and technical route descriptions, and cites public statements by Li Wei, executive partner at Vertex Investment, and co-founders Luo Ping, Zheng Cunyuan, and Yu Jie. Core figures such as the funding amount, product parameters, and data collection scale come from company disclosures or media reports and are at the source_claim level; industry background such as real-machine data costs and the Ego Data trend comes from InfoQ's exchanges with industry insiders and is at the source_claim level. This article does not introduce external independent verification information, and all inferences have been marked.

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