NdotLight Unveils TRINIX at NVIDIA GTC 2025

NdotLight is proud to announce its participation in the NVIDIA GTC 2025, where it will showcase its groundbreaking TRINIX technology. TRINIX, a proprietary solution that generates high-quality synthetic data through advanced 3D modeling and physics simulation, is set to revolutionize how we digitize the three-dimensional world we live in.

"The future of AI-driven manufacturing requires both high-quality training data" said Jay Park, CEO of NdotLight. "By Trinix's synthetic data capabilities, we're creating a comprehensive solution for the next generation of intelligent manufacturing."

Introduction: TRINIX – The Future of AI-Driven Manufacturing & 3D Design

NdotLight’s TRINIX technology provides the capability to produce massive-scale, ultra-realistic 3D synthetic data. Together, these solutions create an ecosystem that seamlessly integrates with NVIDIA Omniverse platform’s OpenUSD data interoperability, driving unprecedented improvements in AI model training and physical simulation.

Addressing Critical Challenges

Current AI models are hampered by a scarcity of realistic 3D data, limiting the effectiveness of physical simulations and learning outcomes. The challenge results in high data generation costs and slower innovation cycles. The TRINIX solution directly addresses these pain points by:

• Generating Extensive 3D Learning Data: TRINIX enables the creation of billions of high-quality 3D models, simulating real-world physical properties.

• Creating a Synergistic Ecosystem: Integration with NVIDIA Omniverse platform AI learning efficiency and paves the way for advanced manufacturing automation.

Expanding Industry Applications Through Strategic PoCs

NdotLight, in collaboration with AiV, a deep learning machine vision solution and industrial MLOps provider, is actively engaging in proof-of-concept (PoC) projects to explore the application of TRINIX-generated synthetic data in industrial automation. Companies such as CTR, an affiliate company of LX group, and Rich Korea are among the first to evaluate this technology for inspection and robotics use cases.

Why Now? A Confluence of Market Forces

The rapid expansion of autonomous driving, robotics, and industrial AI has catalyzed a demand for more sophisticated digital twin technologies and manufacturing data. AI-based manufacturing innovation is constrained by the scarcity of high-quality real training data. The fundamental challenge lies in generating diverse, physics-based 3D data for AI training. Trinix addresses this need with its advanced 3D modeling and physics engine, creating high-quality synthetic data to power the next generation of AI-driven manufacturing.

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