Three Deep-Sea Robot Deals in Three Months: Investors Look Beyond Dive Depth
Deep-sea robotics financing has become unusually dense. Gongzhi Ocean announced nearly 100 million yuan in angel funding, with investors including Zhongxin Zhidi, Lihe Financial, Yinfeng Capital, Xiaojishi Dazhuang VC, and Harbin Engineering University Asset Management. Founded in 2024, the company focuses on high-end underwater propulsion and bionic underwater vehicles. Its core product, Hetu, is positioned as the industry’s first integrated underwater robot for both detection and operation.
A month earlier, on August 13, Deep Sea Sapien completed more than 500 million yuan in Series A funding. Before that, on June 15, Shihang Intelligent completed a Series A round exceeding 1 billion yuan. In three months, three companies raised three different stages of capital.
Shihang Intelligent’s Series A investor list carries two signals. New investors include Moore Threads and Kunlunxin industrial investor Shanghe Momentum Fund, Singapore’s Temasek-backed Vertex Growth, CITIC Group’s largest agricultural industry fund, plus Yuzun Capital and Dayang Motor. Existing shareholders Jinshajiang Venture Capital, Vertex China Fund, Huaying Capital, Changshi Capital, and Shengjing Jiacheng Capital all oversubscribed.
The simultaneous entry of semiconductor industry capital and a sovereign fund suggests the round was not driven only by financial returns but also by supply-chain positioning. Shihang Intelligent covers marine general-purpose robots from R&D to production, sales, and service. Moore Threads and Kunlunxin point to underwater robots’ demand for computing power and chips. Adapting domestic chips to underwater equipment may be one problem this funding aims to solve.
Jiang Han, a senior researcher at Pangoal Institution, explained the capital influx to Securities Times. The stock market is the recurring payment demand from global merchant ship operations, maintenance, and port inspection. The incremental market is domestic marine economy growth, which creates rigid underwater operation demand in hull cleaning, wind power maintenance, and seabed exploration. The third layer is data barriers: most deep-sea areas remain underexplored, and early operators accumulate exclusive data assets that are hard to replicate. Jiang argues such long-term barriers are far better than many AI sub-sectors. Land-based AI models and data can often be publicly obtained or simulated, but deep-sea pressure, corrosion, currents, and visibility can only be accumulated through real sea trials; simulation covers only part of it.
A CICC report breaks down underwater robot systems: ground operation, communication and navigation, motion control, and power propulsion. Each subsystem must be re-engineered and validated under high pressure, corrosion, and low visibility. Industrial underwater robots face harsh environments and diverse tasks, demanding higher technical specifications and barriers. Forward Industry Research Institute data show China’s unmanned underwater vehicle market grew from 3.5 billion yuan in 2022 to 5.16 billion yuan in 2024, an average annual growth rate above 20%. That is not the most exaggerated growth in robotics, but underwater robots are special because customer willingness to pay is directly tied to operation costs.
Jiang sees an inflection point: deep-sea robots are moving from single-point equipment sales to full-scenario service output. Future competition will not be about dive depth but about lowering the cost of hull cleaning, wind power maintenance, and seabed exploration while improving domestic core component autonomy. For a hull-cleaning buyer, whether a robot can dive 6,000 meters or 10,000 meters matters less than how many square meters of hull it can clean per hour.
Gongzhi Ocean’s investors include Harbin Engineering University Asset Management. The university’s strength in ship and marine engineering means the company’s technical route in propulsion equipment and bionic vehicles has academic R&D support. Shihang Intelligent, Deep Sea Sapien, and Gongzhi Ocean all face the same question: how to turn laboratory technical indicators into repeatable, maintainable, and scalable operational capability in real sea conditions. Funding is only the first step. The next money must go to scenario validation and supply-chain refinement. How much work these robots actually do under ships, at wind farms, and along subsea cables will say more than any financing headline.