Ropedia has raised $30 million across two pre-A funding rounds to expand its data infrastructure platform for robotics and embodied artificial intelligence systems. The Singapore-based company raised $22 million in its latest round after previously securing $8 million in March 2026. The financing included angel investors, long-term financial investors and strategic partners with experience in artificial intelligence, enterprise technology, robotics, mobility and infrastructure.
Ropedia plans to use the capital to expand data collection across Southeast Asia and North America, increase production and deployment of its HOMIE wearable devices, and advance its AI research and data platform. The company also expects to hire additional engineers in the United States.
Physical AI refers to systems that perceive and interact with the real world, including robots, autonomous machines, and other embodied technologies. These systems require training data that connects visual and sensory information with human actions and physical outcomes.
Ropedia’s HOMIE device is a wearable, head-mounted system that records first-person video, audio, depth, hand movements, gaze, body motion and camera position simultaneously. Each data stream is timestamped so developers can understand how perception and movement correspond in real time.
The company said this synchronization is important because robots must learn not only what an action looks like, but also how physical movements, timing and environmental conditions relate to the result.
HOMIE sends the captured information into Ropedia’s processing and annotation platform. The company then structures, synchronizes, and refines the data for use in training robotics and embodied AI models.
Ropedia distinguishes its platform from conventional data-labeling businesses, which generally annotate information that has already been collected. Ropedia generates the underlying real-world data and manages the full process from capture through model-ready delivery.
The platform is also designed as an alternative to teleoperation-based data collection, in which humans remotely control physical robots to generate training information. That approach can be costly and limited by the availability and design of specific robot fleets.
Because HOMIE can be worn by people in different locations and environments, Ropedia said it can scale collection by distributing additional wearable devices rather than purchasing more robots.
The company sells access to its infrastructure through dataset licensing, selected access to HOMIE hardware and research collaborations. Its closed-loop pipeline also includes quality assurance and model-aligned fine-tuning.
Ropedia’s flagship Xperience-10M dataset includes 10 million interaction episodes and more than 10,000 hours of multimodal recordings. It contains billions of synchronized frames spanning video, depth information, motion capture and inertial sensor data.
The company said every additional HOMIE deployment expands the dataset’s coverage of environments, behaviors and interactions. This network effect is intended to improve the dataset’s value for developers training systems to operate across varied real-world conditions.
Ropedia claims its approach can reduce data collection costs by as much as 50 times compared with traditional methods. HOMIE has entered mass production, and the company has served more than a dozen North American businesses working in embodied AI and spatial intelligence.
Ropedia was founded during the second half of 2025 by CEO Zhaoxi Chen, CTO Fangzhou Hong and Chief Scientist Ziwei Liu. The company is headquartered in Singapore and maintains an office in Mountain View, California.
KEY QUOTES:
“A robot can’t play baseball by watching a video any more than you could learn to ride a bike by reading about it. The robot must understand what it’s like to grip a bat and know the timing it takes to hit a ball.”
“Text scraped from the internet was used to train the last generation of AI. Real-world human experience, captured at the same scale, will train physical AI. Physical AI will let us leave the lab and go to work, first in factories, then at home, helping our families.”
Zhaoxi Chen, Co-Founder and CEO of Ropedia
“I backed the Ropedia team early because they had a rare combination of deep technical expertise, speed of execution and a clear vision for where physical AI was heading.”
“Since then, they have built a compelling data infrastructure platform serving leading robotics and foundation-model companies globally. I believe Ropedia is well positioned to become a foundational company in the physical AI ecosystem.”
Ropedia Angel Investor and Amazon Research Scientist
