Ropedia’s HOMIE is a lightweight device that includes four cameras and a swappable battery module. | Source: Ropedia
Ropedia, which is building data infrastructure for physical AI, today said it has raised $22 million in pre-Series A funding. Combined with the company’s seed round, it has raised $30 million.
The company plans to use the funding to scale HOMIE, its wearable, head-mounted device. HOMIE captures first-person human movement, object interaction, and spatial context and then feeds that data into Ropedia’s processing and annotation models.
“For this round of fundraising, we’re actively expanding our business and technical networks in the sense that we want to build up our teams in hardware, software, data infrastructure, and model development,” Zhaoxi Chen, co-founder and CEO of Ropedia, told The Robot Report. “The second usage is really going to be expanding our business to North America, especially in the United States, because the majority of our existing clients and customers are based there.”
Ropedia also plans to build out its data platform, adding annotation tooling, quality analytics and compliance infrastructure, and to grow its AI research team’s work on data, foundation models, and world models. Founded in 2025, the company has offices in Singapore and Mountain View, Calif.
The robotics industry needs data infrastructure
The data pipeline that starts with HOMIE runs end to end, from capture to model-aligned fine-tuning. This creates data that Ropedia generates and structures itself rather than the client-owned data that most data-labeling providers annotate. That full-stack approach also sets it apart from teleoperation-based capture, which requires physical robot hardware and is typically limited to specific robot embodiments.
Chen asserted that Ropedia is building the data infrastructure the robotics industry needs if it wants to scale.
“Infrastructure means you’re going to be able to process massive scale of data in a short time,” he said. “Delivering 1,000 hours of data is a totally different thing compared with delivering 1 million hours of data, because you need to make sure that everything is industry level of standards.”
What is HOMIE?
HOMIE is a data-collection device equipped with 360º camera view. Ropedia aims to build human-level intelligence in robotics, and to do this, Chen claimed that the best place to start is with copying human behavior.
“You’re going to mimic human-level intelligence by going back to the way humans learn new skill sets,” he said. “We learn in the physical world through our vision, through our interaction from a first-person perspective. We learn from a first-person view. We learn all physical skills or high-level reasoning semantic skill sets from this perspective. So, that’s why we believe in the power of egocentric data.”
HOMIE includes other sensing modalities in addition to vision. “We also have an audio sensor where you can reconstruct the source and direction of an audio signal in the environment,” Chen said. “We also have a motion unit on the headset where you can track how you move.”
Part of what helps Ropedia stand apart, Chen said, is that the company developed much of HOMIE in-house. This custom hardware results in better data.
“We’re not a completely full-stack company, but the majority of the hardware we’re developing purely on our own,” he noted. “We do not develop CMOS sensors, resistors, and those kinds of off-stream components. But the overall structures, the PCBA, and the hardware synchronization of different sensors, we’re developing on our own.”
Ropedia said its approach cuts data-collection costs by up to 50 times compared with traditional methods. | Source: Ropedia
What tasks is Ropedia targeting?
In the long term, Ropedia is targeting a wide range of tasks for its datasets. “Ideally, we want to capture all of the tasks, but we need to do things step by step. We’re starting with capture in a casual environment in the sense that we capture the data in the home,” Chen said.
So far, the company has been focusing on tasks like housekeeping, cleaning, and even interior design.
“Ideally, we want to capture all of the tasks, but we need to do things step by step. We’re starting with capture in a casual environment in the sense that we capture the data in the home,” Chen said. “We also have a pickleball club where we require all the members to wear our headsets and do the recording during their practice.”
Right now, Ropedia collects around 1,000 hours of data per week, with 100,000 total hours gathered. The company said it is already providing value to its early customers.
“What we have been doing is providing two types of services. One is OTS or off-the-shelf datasets. We’re directly licensing our existing data in the database, and they will use our data on demand to fulfill their research and foundational consumption,” Chen said. “The second type of service for our customers is we acquire the high-quality data.”
Save the date for RoboBusiness 2026What are Ropedia’s next steps?
Ropedia intends to continue expanding data collection in Southeast Asia and North America, growing its U.S. team, and increasing manufacturing of HOMIE. The company also plans to collaborate with upstream and downstream partners and is interested in working with industry, academia, and even robotics hobbyists.
Looking ahead, Ropedia plans to create more wearable data capture hardware, said Chen.
“There’s a crazy plan in the future of Ropedia where a human being is going to serve as a socket, in the sense that we want to put as many devices on top,” he said. This could include the headset as well as devices on the hands or legs to capture more data.
“We have been developing the next step of the product line. So, one is going to be a hand device where you’re accurately tracking the hand pulses and tactile interaction,” Chen said. “At the same time, it’s going to synchronize with our HOMIE devices, so you can have synchronized data streams.”
Ropedia also has plans for other less conventional devices, including shoes that would sense how feet interact with the ground to help train humanoid robots.
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