At the Mifengpai global launch event, Yao Maoqing, Chairman and CEO of Mifeng Technology, unveiled "Mifengpai," the first full-category high-quality physical AI data crowdsourcing service platform.

He announced that physical AI data collection tasks would be opened to the public, allowing ordinary users to claim data collection assignments through the Mifengpai App.

By wearing MEgo devices, users can complete designated operations in real-world scenarios such as retail, warehousing, manufacturing, and households, earning corresponding compensation based on the duration of validated effective data, thereby becoming a "robot trainer."

Turning Everyday Experience into Trainable Data

"The best teacher for physical AI is every person who lives their life earnestly," Yao Maoqing stated.

He expressed that Mifengpai aims to transform the real operational experience scattered across daily life and various industries into data that robots can learn from, train on, and reuse.

The launch of Mifengpai converts professional data collection into standardized tasks that ordinary users can execute, allowing users to record real operations in conjunction with their work and daily life without spending extra time.

This signifies that physical AI data production is moving from centralized collection toward broader distributed, socialized collaboration, forming a new production system around task organization, data engineering, quality control, and closed-loop operations.

Dual Networks Support the Platform

It is reported that Mifengpai is jointly supported by a "scenario network" and a "crowd network."

The scenario network connects real working environments such as hotels, catering, supermarkets, logistics, factories, healthcare, households, elderly care, and intangible cultural heritage, providing a continuous and rich source of tasks for data collection.

The crowd network connects participants from different industries and regions, enabling real operational experience to be recorded at scale.

Currently, Mifengpai has covered 22 major categories of scenarios, over 5,000 tasks, and more than 50,000 real-world environments.

These scenarios include not only general operations such as picking and placing, organizing, and transporting, but also professional tasks such as assembly, inspection and repair, and caregiving, providing data for robot training in dynamic environment understanding, fine motor control, continuous process execution, risk assessment, and safe interaction capabilities.

Complete Service System

On this foundation, Mifengpai has formed a complete service system of "collectable, accessible, and usable" through its self-developed MEgo data collection device, the Mifengpai App, and the data governance engine MEgo Engine.

The MEgo device is designed according to consumer-grade hardware standards, recording first-person video, millimeter-level pose, and multimodal information such as touch and force perception.

The Mifengpai App simplifies the user-side process into four steps: order acceptance, collection, verification, and settlement, with zero barrier to entry.

The MEgo Engine handles data processing, annotation, quality assessment, and delivery, transforming real operations into data that models can train on and evaluate with.