Ropedia Raises $30 Million Pre-A to Build Data Infrastructure for Physical AI

Ropedia Secures $30 Million in Pre-A Funding

Singapore-based AI infrastructure startup Ropedia has raised $30 million in Pre-A funding to accelerate the development of data infrastructure for physical AI and robotics.

The fundraising was completed across two rounds, backed by individual angel investors. The latest round raised $22 million, following an earlier $8 million round announced in March 2026.

Led by Zahoxi Chen, Fangzhou Hong, and Ziwei Liu, Ropedia is building data infrastructure designed to train and support robotics and embodied AI systems.

Developing Data Infrastructure for Physical AI

Ropedia's platform combines HOMIE hardware, a proprietary data processing engine, and structured multimodal datasets to capture and organize real-world human experiences for AI training.

Its flagship dataset, Xperience-10M, is designed to provide robotics and embodied AI systems with structured data for simulation, learning, and real-world deployment.

The company's infrastructure supports the growing demand for high-quality data used to train physical AI applications.

Expanding Global Operations

The newly raised funding will be used to expand data collection across Southeast Asia and North America, increase deployment of HOMIE devices, advance AI research, and strengthen engineering teams in the United States.

The investment will also support continued development of Ropedia's data platform for robotics and embodied AI technologies.