MetAI<\/a> has developed a model that can quickly generate \u201cSimReady\u201d (simulation-ready) digital twins using AI and 3D technology, by converting CAD files into functional 3D environments within minutes. <\/p>\nNow Nvidia is backing MetAI in its first round of funding, a $4 million seed round that becomes the chip giant\u2019s first investment into 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.\u00a0<\/p>\n
The next wave of AI,\u00a0known as\u00a0generative physical AI, relies on physically accurate simulated environments to train and validate robots used in autonomous systems, to build operational AI before deployment. MetAI contends that the digital twins that it helps create will be central to that effort. <\/p>\n
\u201cDigital 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,\u201d said Daniel Yu, CEO and co-founder of MetAI, in an interview.<\/p>\n
MetAI focuses on AI-powered digital twins tailored to advanced semiconductor fabs, smart warehouses\u00a0and automation. It also generates synthetic data within AI-enabled digital twin environments.\u00a0<\/p>\n
Renton Hsu, Yu\u2019s co-founder and the CTO of MetAI, has a background in 3D engineering and AI, and he first got to working with digital twins while building enterprise AI software applications: they were used as a practical workaround in situations where clients lacked enough data to train their systems. He then realised 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 startup with experience in digital transformation projects) and a third co-founder, Dave Liu (COO), to start MetAI. <\/p>\n
The breakthrough was enough to win first place in a a competition run by Nvidia, making Hsu a \u201cJetson AI ambassador\u201d for the country. <\/p>\n
MetAI\u2019s competitors are the range of large and small companies 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 scores of companies, including Sky Engine and Scale AI.\u00a0<\/p>\n
MetAI believes that it has a unique approach compared to all of these. <\/p>\n
\u201cUnlike competitors\u00a0that prioritize\u00a0operational efficiencies or IoT integrations, MetAI leverages generative models and AI-driven layouts to create digital twins designed for physical AI training and implementation in real-world operations,\u201d Yu said. \u201cThis approach not only accelerates the creation of digital twins but also ensures their direct usability for advanced automation systems like robotics, bridging the gap between simulation and reality.\u201d<\/p>\n
MetAI differentiates itself by producing artificial data within its AI-enabled digital twin environments. Yu noted that it enables users to generate synthetic data customized for specific operational requirements, facilitating AI training and validation. \u201cInstead of creating isolated datasets, MetAI builds dynamic virtual worlds (i.e., world simulators) \u2014 realistic virtual environments that operate exactly like the real world,\u201d he said.<\/p>\n
The two-year-old startup \u2014 whose products range from vertical AI agents through to digital twins \u2014 has a handful of customers and is already generating revenues by partnering with enterprises in the manufacturing and automation industries, and this year it expects to bring in $3 million from a single project, Yu said.\u00a0Revenue\u00a0is derived\u00a0from project-based income, product subscriptions, and licensing fees from ongoing developments, he added.<\/p>\n
\u201cMetAI\u2019s integration with NVIDIA Omniverse represents a transformative step forward for industrial digital twins and physical AI in simulations,\u201d\u00a0Nico Caprez, corporate development manager at Nvidia, said in a statement. \u201cTheir ability to create scalable environments for AI training will potentially set a new standard for industries ranging from manufacturing to robotics.\u201d\u00a0<\/p>\n
In 2023, MetAI collaborated with Kenmec to create digital twins for automated warehouses. MetAI\u2019s technology claims to have drastically reduced the time needed for warehouse digital twin simulations from thousands of hours to just 3 minutes, resulting in significant savings in operational and verification tasks.\u00a0<\/p>\n
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. On top of that, the Taiwan-based startup intends to establish a U.S. office and relocate its headquarters in the second half of 2025, Yu told TechCrunch.\u00a0<\/p>\n
\u201cTaiwan serves as our testing ground, where we collaborate with Taiwanese industry leaders to integrate deep vertical knowledge into our models, ensuring our solutions are both robust and scalable,\u201d Liu said.\u00a0\u201cGiven its size and the demand for simulation-driven solutions, we are expanding the U.S. market due to high labor costs and operational complexities. Our expansion strategy focuses on providing both point\u00a0solutions\u00a0and end-to-end solutions, including SaaS offerings and vertical AI agents designed for rapid implementation in real-world scenarios within these industries.\u201d\u00a0<\/p>\n<\/div>\n
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