Embodied AI Physical Data Collection Service

📌 Background

As humanoid robots and autonomous driving enter the large-scale training phase in 2026, embodied AI companies are in urgent need of massive amounts of real-world physical operation data. The collection and annotation segment is poised to achieve profitability earlier than hardware manufacturing. According to a May 2025 investigation by The Paper, the general pricing for embodied AI data ranges from 200-500 RMB/hour, with real-machine data reaching 500-1000 RMB/hour (based on media reports). Meanwhile, the effective hourly wage for home-based data collectors is approximately 17 RMB, indicating a price spread of over 10 times compared to the terminal selling price.

👤 Target Customers

Humanoid robot companies, autonomous driving enterprises, and embodied AI research institutions

💰 Revenue Streams

1) Selling collected and annotated data to embodied AI companies via scenario-based data packages; 2) Charging for customized data collection projects based on man-hours and equipment investment; 3) Subscription or project fees for data sandbox and simulation environment construction.

🧮 Cost Structure

Investment in data collection equipment and sensors, operation of professional collection teams, data cleaning and annotation, storage, and computing power.

🛡️ Moat

Exclusive licenses for real-world scenario operations and data accumulation, teleoperation and multimodal annotation pipelines, and industry-specific data compliance qualifications.

🔑 Keys to Success

• Ability to acquire scarce real-world scenario data
• Efficiency of multimodal data annotation pipelines
• Long-term supply contracts with leading embodied AI enterprises

⚠️ Risks

• Safety incidents and compliance risks in collection scenarios
• Unstable market demand leading to order volatility
• Difficulty in data reuse due to lack of standardization

🏢 Cases

• Ruqi Data (Monetization of Robotaxi mobility scenario data)

📊 SWOT Analysis