Nvidia has expanded its opportunities to create robotics and other industrial AI applications with the launch of its Omniverse platform, and more recently Mega, an Omniverse Blueprint framework for creating digital twins to leverage these applications. It is also investing in digital twin startups to launch its efforts.
that of Taiwan MetAI has developed a model capable of rapidly generating “SimReady” digital twins using AI and 3D technology, converting CAD files into functional 3D environments in minutes.
Nvidia is now backing MetAI in its first funding round, a $4 million round that becomes the chip giant’s first investment in a Taiwanese startup. Other participants 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 says the digital twins it is helping to create will be central to this effort.
“Digital twins have long been considered a barrier to entry for physical AI due to the months or even years of effort required to develop,” Daniel Yu, CEO and co-founder of MetAI, said in an 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, co-founder of Yu and CTO of MetAI, has a background in 3D engineering and AI, and he first began working with digital twins when building enterprise AI software applications : They were used as a convenient workaround in situations where customers lacked enough data to train their systems. He then realized he could apply the same thing to 3D systems, integrating 3D technology with AI to develop synthetic AI and 3D solutions, partnering with Yu (who comes to the startup with a experience in digital transformation projects) and a third co-founder, Dave. Liu (COO), to start MetAI.
This breakthrough was enough to win first place in a competition organized by Nvidia, making Hsu a “Jetson AI ambassador” for the country.
MetAI’s competitors are a range of large and small companies that have built digital twin technologies for manufacturing. These include Siemens Digital Industries, Dassault Systèmes, Hexagon AB, Duality AI and Intagles. In the synthetic data space, there are many, many companies, including Sky Engine and Scale AI.
MetAI believes it has a unique approach to all of these.
“Unlike competitors that prioritize operational efficiencies or IoT integrations, MetAI leverages generative models and AI-driven layouts to create digital twins designed for training and implementation. “Physical AI in real operations,” said Yu. “This approach not only accelerates the creation of digital twins, but also ensures their direct use for advanced automation systems like robotics, bridging the gap between simulation and reality.”
MetAI differentiates itself by producing artificial data within its AI-enabled digital twin environments. Yu noted that it allows users to generate personalized synthetic data for specific operational requirements, making AI training and validation easier. “Instead of creating isolated datasets, MetAI builds dynamic virtual worlds (i.e. world simulators) – realistic virtual environments that function 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 by partnering with companies in the manufacturing and automation sectors, and this year she hopes to bring in $3. million for a single project, Yu said. Revenue comes from project-based revenue, product subscriptions and licensing fees related to ongoing developments, he added.
“The integration of MetAI with NVIDIA Omniverse represents a transformative step for industrial digital twins and physical AI in simulations,” Nico Caprez, head of corporate development at Nvidia, said in a statement. “Their ability to create scalable environments for AI training could potentially 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 significantly reduced the time required for digital twin simulations in warehouses, 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 to accelerate the development and execution of its go-to-market strategies to meet growing demand. In addition to this, the Taiwan-based startup intends to establish an office in the United States and relocate its headquarters in the second half of 2025, Yu told TechCrunch.
“Taiwan serves as a testing ground, where we collaborate with Taiwanese industry leaders to integrate deep vertical knowledge into our models, ensuring that our solutions are both robust and scalable,” Liu said. “Given its size and demand for simulation-based solutions, we are expanding the US market due to high labor costs and operational complexities. Our expansion strategy focuses on providing both point solutions and end-to-end solutions, including SaaS offerings and vertical AI agents designed for rapid implementation in real-world scenarios within these sectors.
