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Nvidia has doubled down on the opportunity to build robotics and other industrial AI applications, with the launch of its Omniverse platform, and more recently Megaan Omniverse Blueprint framework to create digital twins to operate these applications. It is also investing in digital twin startups to get the effort off the ground.
Taiwan year has developed a model that can quickly generate “SimReady” digital twins (ready for simulation) using AI and 3D technology, converting CAD files into functional 3D environments in minutes.
Now Nvidia is backing MetAI in its first round of funding, a $4 million seed round that becomes the chip giant’s first investment in a Taiwanese startup. Others in the round are a mix of other strategic and financial investors, including Kenmec Mechanical Engineering, Solomo Technology, SparkLabs Taiwan, Addin Ventures and Upstream Ventures.
The next wave of AI, known as generative physical AI, relies on physically accurate simulated environments to train and validate robots used in autonomous systems, to build operational AI before deployment. MetAI argues that the digital twins it helps create will be central to that effort.
“Digital twins have long been seen as a barrier to entry for physical AI due to the months or even years of effort required for development,” said Daniel Yu, CEO and co-founder of MetAI, in a interview
MetAI focuses on AI-powered digital twins suitable for advanced semiconductor factories, smart warehouses and automation. It also generates synthetic data in AI-enabled digital twin environments.
Renton Hsu, Yu’s co-founder and CTO of MetAI, has a background in 3D engineering and AI, and started working with digital twins while building enterprise AI software applications: they were used as a practical solution in situations where customers were missing. enough data to train their systems. He then realized that he could apply the same to 3D systems, integrating 3D technology with AI to develop synthetic AI and 3D solutions, joining forces with Yu (who comes to the start with experience in digital transformation projects) and a third co-founder , Dave. Liu (COO), to start MetAI.
The breakthrough was enough to win first place in a competition run by Nvidia, making Hsu a “Jetson AI ambassador” for the country.
MetAI’s competitors are the range of large and small businesses that have built digital twin technologies for manufacturing. They include Siemens Digital Industries, Dassault Systemes, Hexagon AB, Duality AI and Intagles. In the synthetic data sector, there are dozens of companies, including Sky Engine and Scale AI.
MetAI believes it has a unique approach compared to all of these.
“Unlike competitors who prioritize operational efficiency or IoT integrations, MetAI leverages AI-driven generative models and layouts to create digital twins designed for physical AI training and deployment in real-world operations,” he said Yu. “This approach not only accelerates the creation of digital twins, but also ensures their direct usability for advanced automation systems such as robotics, bridging the gap between simulation and reality.”
MetAI differentiates itself from artificial data production in its AI-enabled digital twin environments. Yu noted that it allows users to generate customized synthetic data for specific operational requirements, facilitating AI training and validation. “Instead of creating isolated datasets, MetAI builds dynamic virtual worlds (ie, world simulators) — realistic virtual environments that operate exactly like the real world,” he said.
The two-year-old startup — whose products range from vertical AI agents to digital twins — has a handful of customers and is already generating revenue from partnerships with companies in the manufacturing and automation industries, and this year expects to bring $ 3. million from a single project, Yu said. Revenue is derived from project-based income, product subscriptions and license fees from ongoing developments, he added.
“The integration of MetAI with NVIDIA Omniverse represents a transformative step forward for industrial digital twins and physical AI in simulations,” Nico Caprez, director of corporate development at Nvidia, said in a statement. “Its ability to create scalable environments for AI training could set a new standard for industries ranging from manufacturing to robotics.”
In 2023, MetAI collaborated with Kenmec to create digital twins for automated warehouses. MetAI’s technology claims to have drastically reduced the time required for simulating warehouse digital twins from thousands of hours to just 3 minutes, resulting in significant savings in operational and verification tasks.
With the latest funding, MetAI plans to expand its R&D team for faster development and execution of its go-to-market strategies to meet growing demand. In addition to that, the Taiwan-based startup plans to establish a US office and move its headquarters in the second half of 2025, Yu told TechCrunch.
“Taiwan serves as our testing ground, where we collaborate with Taiwanese industry leaders to integrate deep vertical knowledge into our models, ensuring our solutions are robust and scalable,” said Liu. “Given its size and the demand for simulation-driven solutions, we are expanding the US market due to high labor costs and operational complexity. Our expansion strategy focuses on providing point-in-time solutions and end-to-end solutions -to-end, including SaaS offerings and vertical AI agents designed for rapid deployment in real-world scenarios in these industries.
