In April 2026, Shanghai Meifeng Body-Aware Intelligence Technology Co., Ltd. launched the MEgo series of bodyless wearable data collection devices and the accompanying data governance service platform, MEgo Engine. Yao Maoying, the company’s founder and CEO, took office in February 2026, aiming to bridge the gap between the industry’s effective data volume (about hundreds of thousands of hours) and human-like capabilities required (100 million hours) through independent operations. Meifeng plans to reach ten million hours of production capacity by 2026 and ten billion hours by 2030. It will use crowdsourcing and franchise models to recruit data collectors, nearly doubling the efficiency of individual labor output with bodyless devices, and automate data processing. The company aims to build a physical AI data infrastructure to support research and development in high-quality data-serving robots, body-aware intelligence, and large models.
In April 2026, Meifeng Technology released the MEgo series of wearable devices for data collection and the MEgo Engine platform for data governance services. Yao Maoying, 39 years old, became the chairman and CEO of the newly established Shanghai Meifeng Embodied Intelligence Technology Co., Ltd. in February of the same year, aiming to break through the data bottleneck in embodied intelligence through independent operations. Currently, the amount of valid data in the industry is only several hundred thousand hours, while achieving human-like capabilities requires one hundred million hours. Meifeng plans to reach ten million hours by 2026 and ten billion hours by 2030. To achieve this, Meifeng has built a physical AI data infrastructure, using crowdsourcing and加盟 models to recruit data collectors. It has increased the efficiency of individual labor output nearly twice using devices without a physical body and has equipped them with automated pipelines for data processing. Its goal is to make high-quality physical AI data readily available like water and electricity, serving research and development teams such as service robots, embodied intelligence, and large models.