Ropedia raises $22M to scale human-centric data collection for embodied AI
Singapore-based robotics data infrastructure firm Ropedia Pte. Ltd. today announced it raised $22 million in Pre-Series A funding to scale up its collection of real-world, multimodal interaction data to fuel artificial intelligence robotics models developed by technology companies.
Physical AI and embodied AI development is increasingly burdened by a lack of real-world data at a diversity and scale that robot-specific teleoperation struggles to produce. Developers in this field need models that can generalize across robots, objects and environments to scale products. Ropedia’s industry proposition is to gather human experience directly via video and convert it into model-ready multimodal datasets.
Although images and text exist in abundance, and there are many videos online, much of it cannot be readily curated or transformed into robotic trajectories that represent human-like activity. When a robot interacts with the real world, it needs synchronized, annotated, and curated information about movements, geometry and the consequences of those actions. Pictures of objects don’t work for this and unless video is well structured, it’s harder to concentrate into a clean dataset.
