Mecka AI Raises $60 Million to Expand Robotics Data and Deployment Infrastructure

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Mecka AI, a New York City-based robotics data and infrastructure company, has raised $60 million in funding to support the development of tools and datasets for physical AI systems.
The funding includes a $25 million Series A round and a $35 million follow-on investment. The round was led by Framework Ventures, with participation from Menlo Ventures, SV Angel, Kindred Ventures, and angel investor Ted Xiao.
Funding to Support Physical AI Development
Mecka AI develops data, evaluation, and deployment infrastructure designed for robotics and embodied AI applications. The company focuses on helping AI-powered systems learn from real-world human activity and operate in practical environments.
Its platform is used by robotics research labs, AI model developers, and enterprises that are working on deploying embodied AI systems. These organizations often require task-specific data, performance evaluation tools, and infrastructure that supports the transition from research to real-world deployment.
Building Data for Real-World Robotics Applications
The company is led by CEO Josh Gao. Its work centers on creating datasets and infrastructure that allow robots to better understand human actions and interactions in physical spaces.
One of Mecka AI’s key products is Egoverse, a large-scale human interaction dataset. The dataset is built using first-person recordings of real-world activities across different environments and tasks.
According to the company, Egoverse is designed to help researchers study how people move, interact with objects, and complete everyday tasks. These insights can be used to improve the training and evaluation of robotics and embodied AI systems.
Growing Demand for Physical AI Infrastructure
As robotics and physical AI applications continue to expand, companies are increasingly seeking access to high-quality real-world data and deployment tools. Mecka AI aims to address this need by providing infrastructure that supports the development, testing, and deployment of embodied AI technologies.












