NdotLight Invited as a Promising Korean AI Startup to Showcase Deformable-Asset Simulation at NVIDIA GTC Taiwan

NdotLight, a 3D AI company led by CEO Jinyoung Park, will participate in NVIDIA GTC Taiwan, one of the world's largest AI conferences, in Taipei from June 1 to 4 and showcase its proprietary Physical AI asset-generation and simulation technology. NdotLight was invited to the event as a promising AI startup representing Korea, bringing Korean deep-tech capabilities to a global audience.
At the event, NdotLight will move beyond its established generation of complex articulated objects and unveil high-difficulty deformable-asset generation and simulation technology for the first time. Its booth will feature parametric modeling and AI-based generation, together with live demonstrations in NVIDIA Isaac Sim. The demonstrations will reproduce difficult manufacturing and automation tasks, including power- and LAN-cable connections and the real-time physical deformation of rigid and soft bodies, showing how the time required to construct complex physical-environment assets can be significantly reduced.
NdotLight will also advance its global partnership strategy. During GTC, the company will sign a memorandum of understanding with Taiwanese industrial digital-twin startup MetAI to establish a collaboration framework for the global simulation market. On May 31, CTO Suntae Kim will speak at MetAI's global networking event, Physical AI: Builders Night, and present a vision for manufacturing and simulation innovation based on SimReady assets. CEO Jinyoung Park will also introduce the company's technology and growth roadmap in an investor-relations pitch for global investors and corporate representatives during the event.
“NVIDIA GTC Taiwan will be an opportunity to demonstrate NdotLight's differentiated technology to the global market as we expand from rigid-body simulation into deformable assets,” said CEO Jinyoung Park. “By showcasing our technology within the NVIDIA ecosystem, we aim to help global manufacturers build Physical AI environments faster and with greater precision.”


