SKAI Intelligence Featured for Its Core Technology in ABB Robotics and NVIDIA Manufacturing AI White Paper
[Asia Economy]
SKAI Intelligence Strengthens Presence in Global Manufacturing AI Ecosystem by Contributing Core Technologies to ABB Robotics–NVIDIA Physical AI White Paper
SKAI Intelligence is expanding its presence in the global manufacturing AI ecosystem by contributing core technologies to a Physical AI white paper jointly published by global industrial robotics leader ABB Robotics and NVIDIA.
According to industry sources on July 21, ABB Robotics released a white paper on July 17 outlining the technologies and implementation methodologies required to realize Physical AI in high-precision manufacturing.
SKAI Intelligence participated as a Main Contributor, alongside AsiaInfo and Deloitte, in the English-language white paper titled "Industrial Physical AI in High-Precision Manufacturing: An Engineering Framework for Robotic Vision Digital Engineering," jointly published by ABB Robotics and NVIDIA.
The white paper summarizes the data infrastructure, validation methodologies, and operational framework necessary for commercializing Physical AI in high-precision manufacturing environments, drawing on the technologies and industrial expertise of each participating organization. It presents an integrated Industrial Physical AI framework that connects digital twins, synthetic data, robotic validation, field feedback, and data governance into a unified engineering workflow.
SKAI Intelligence contributed to the white paper based on its expertise in digital twins and synthetic data developed through NVIDIA's partner and Independent Software Vendor (ISV) ecosystem. The company is also listed on NVIDIA's official Partner and ISV Solutions page. Within the white paper, SKAI Intelligence played a key role in connecting manufacturing data, robotics, and simulation infrastructure.
Each participating organization contributed its area of expertise to establish the core technologies required for the commercialization of Physical AI. ABB Robotics provided the robotic validation framework based on RobotStudio, while NVIDIA contributed simulation and AI infrastructure built on Omniverse.
AsiaInfo presented AI operations platforms and data governance frameworks, while Deloitte contributed business value validation, scalability strategies, and risk management methodologies. SKAI Intelligence participated in building the Real2Sim2Real engineering workflow, leveraging industrial digital twins, task-level synthetic data, automated annotation technologies, and robotic vision data infrastructure to bridge real manufacturing environments with simulation.
In particular, the company developed synthetic datasets that accurately reflect various variables encountered in high-precision manufacturing, including industrial tolerances, reflections, occlusions, pose variations, and assembly deviations. These datasets can be used for both training and validating robotic vision AI systems.
Through these contributions, SKAI Intelligence connected manufacturing field data with ABB Robotics' robotic validation system, NVIDIA's simulation infrastructure, and Deloitte's business expansion strategies. Industry observers note that the company's technical role is explicitly reflected in a white paper jointly developed by global leaders in robotics, AI, and consulting.
As Deployment Readiness—the ability to deploy AI rapidly and reliably in real production environments—emerges as a key competitive factor in manufacturing Physical AI, SKAI Intelligence is recognized for building data infrastructure capabilities that extend beyond synthetic data to digitalize real manufacturing environments and connect AI training, robotic validation, and field feedback into a unified workflow.
In June, SKAI Intelligence signed a Cooperation Framework Agreement with ABB Robotics to jointly advance industrial robotics by integrating ABB Robotics' robotic technologies with SKAI Intelligence's high-precision synthetic data generation capabilities.
Following its Series A investment, the company has also secured additional funding to accelerate technology development and business expansion.
A company representative stated, "Our participation in this white paper is significant because it demonstrates our contribution to defining practical implementation methodologies for Physical AI in high-precision manufacturing together with global industry leaders. Leveraging our digital twin and industrial synthetic data technologies, we will continue expanding our Physical AI infrastructure business in the global manufacturing and robotics markets."