Moxian Technology Highlights Mass-Production Plans for Data-Collection Gloves, Raises Tens of Millions of Yuan in Industrial-Round Financing

leaderobot.com reported on October 10, 2026, that Moxian Technology (Dongguan) Co., Ltd. had completed a new industrial-round financing of tens of millions of yuan. Investors reportedly include two leading embodied AI companies, Songshan Lake Industrial Investment and existing shareholder Qingshuiwan Fund. The report said the funds will be used to upgrade research and development of a new generation of data-collection gloves, optimize the supply chain and prepare for mass production.

The reported use of funds for mass-production preparations as well as research and development could make it easier for embodied-robot developers to secure equipment that can continuously supply training data. The report that Moxian Technology also makes equipment integrating tactile sensing and pose measurement is significant for development teams seeking to avoid fragmented data acquisition.

The issue here appears to be not simply the financing, but that upstream data-acquisition equipment such as data-collection gloves is being evaluated for its capacity for mass production and stable supply. According to leaderobot.com, the investors include two leading embodied AI companies, and the stated uses of the funds include supply-chain optimization and preparations for mass production, in addition to research and development upgrades. This indicates that competition in the embodied AI field is expanding beyond model performance to include the quality of training data and the supply of equipment that can collect it continuously. The focus of this report differs from that of other articles in this newspaper, such as Lexiang Technology unveils compact humanoid robot “Bridge” and Goldman Sachs raises its forecast for humanoid robot shipments in 2035. The first covered the miniaturization of the robot itself, while the second addressed the demand outlook. This report, by contrast, looks at the measurement and collection processes upstream. In other words, securing operational data for input reliably is becoming important in its own right, apart from discussions of the robots themselves. The combination described in supplementary reports—six types of gloves, integration of tactile sensing and pose measurement, and an all-in-one multimodal-fusion system—points toward an approach that sells an integrated package spanning data-acquisition preprocessing through integration, rather than standalone devices. Key questions include how widely the products will be standardized across actual use cases, which products will be central to mass production, and how well data synchronization accuracy and repeatability can be maintained to meet customer requirements. For specific technical specifications and sales details, readers should consult the original report.

For Japan, the competitive picture appears to involve not only robots themselves but also peripheral components and equipment, including tactile sensors, measurement devices and process design for mass production. As this report suggests, stable supplies of data-acquisition equipment are important in embodied AI, creating potential points of contact for Japanese companies with precision sensors and manufacturing equipment.