Mika AI nears a $500 million valuation as human motion data becomes the most valuable asset for intelligent robots

Mika AI is nearing the close of a new financing round led by Sequoia Capital, lifting its valuation to about $500 million, according to sources familiar with the deal. The move comes just three months after the company announced raising $60 million in a round led by Framework Ventures with participation from Menlo Ventures, SV Angel and Kindred Ventures. Although the final terms and precise size of the round have not yet been determined, the rapid valuation jump clearly shows that venture-capital focus is moving directly toward companies that collect motion data and feed human-like robot models.

The company was founded in 2024 by four entrepreneurs: Canadian Josh Gow and Mojin Cheng, who previously built a fintech company for the restaurant sector; Jason Chong, who moved to the Quince platform after it acquired his cryptocurrency project; and Do Yi Nguyn, the only non-Canadian team member who handles operations.Although the founders do not have academic or professional backgrounds in robotics engineering, they recognized early that the scarcity of real-world interaction data constitutes the primary bottleneck hindering the progress of general robots and human-like devices.

The company derived its name from the fictional term “Meka,” which denotes giant machines operated by humans, and charted a path to emulate what human-data platforms such as Scale AI, Mircor, and Surge have achieved for large language models. The platform pays individuals to record their realistic daily tasks, such as making coffee or fixing cars, using sensors attached to their bodies and smartphones.This approach relies on the user’s first-person perspective alongside remote-control technologies to provide the raw data that AI labs and robot makers need to build their models.Gow told Fortune in early June that the company expects to close 2026 with an annual operating revenue run rate of $100 million.

The market is seeing an escalating race, with XDOF nearing the completion of a $1.2 billion round, while major text-data platforms such as Scale AI and Micro 1 are expanding their activities to push language models into the physical world. Although the company does not disclose its customers, the largest robot manufacturers and AI labs now rely entirely on these motion streams to fill the field-performance gap.

What actually changes for those who lead technology and operations projects in the Gulf, Egypt and the Levant? The ongoing shift carries a highly significant signal for organizations investing in facility automation, smart cities and logistics.The next bottleneck will not be procuring ready-made robot bodies or providing computing power, but owning motion data that fits real-world work environments.Relying on data recorded in Western environments will not give a robot sufficient skill to operate in an industrial warehouse or a regional operational facility. Regional tech teams have a clear first-mover opportunity: instead of buying this data later at monopoly prices, there is a need to establish local pathways that enlist field personnel to collect motion data and train systems on the specific realities and details of local tasks.