SKAI Intelligence Provides Core Technologies for ABB Robotics and NVIDIA’s 'Manufacturing AI White Paper'

SKAI Intelligence is expanding its presence in the global manufacturing AI ecosystem by providing core technologies to the white paper on physical AI in manufacturing, which was jointly published by global industrial robotics company ABB Robotics and NVIDIA.

According to the industry on July 21, ABB Robotics released a white paper on July 17 outlining the technologies and application strategies required to implement physical AI in high-precision manufacturing industries.

SKAI Intelligence participated as a main contributor in the English white paper titled “Industrial Physical AI in High-Precision Manufacturing: Robot Vision Digital Engineering Implementation Framework,” jointly published by ABB Robotics and NVIDIA, alongside AsiaInfo and Deloitte.

The white paper summarizes the data construction, verification, and operational systems necessary to commercialize physical AI in high-precision manufacturing environments, leveraging the technological expertise and industrial field experience of each participating organization. It presents an industrial physical AI framework that connects digital twins, synthetic data, robot validation, field feedback, and data governance into a single system.

SKAI Intelligence contributed to the development of the white paper based on its accumulated expertise in digital twins and synthetic data within the NVIDIA partner and independent software vendor (ISV) ecosystem. The company is also listed on NVIDIA’s partner and ISV solution pages, and in the white paper, it acted as the connector between manufacturing site data, robots, and simulation infrastructure.

Each participating organization contributed its area of expertise to propose core technologies necessary for the commercialization of physical AI. ABB Robotics was responsible for a robot validation system based on “RobotStudio,” and NVIDIA for simulation and AI infrastructure based on “Omniverse.” AsiaInfo focused on data governance and AI operation platforms, while Deloitte presented business value validation, expansion strategies, and risk management frameworks.

SKAI Intelligence participated in building the “Real2Sim2Real” engineering workflow, which connects actual manufacturing environments with simulations, based on industrial digital twins, task-level synthetic data, auto-annotation technology, and robot vision data infrastructure.

In particular, the company built synthetic data reflecting a variety of variables found in high-precision manufacturing, such as industrial tolerances, reflections, occlusions, pose changes, and assembly deviations, enabling these to be used to train and validate robot vision AI. Through this, it bridged manufacturing site data with ABB Robotics’ robot validation system, NVIDIA’s simulation infrastructure, and Deloitte’s business expansion strategies.

Industry sources highlight the significance of SKAI Intelligence’s concrete technical role in a white paper jointly produced by global robotics, AI, and consulting leaders. Especially as “deployment readiness”—how quickly and reliably AI can be applied in actual production environments—emerges as a core competitive edge in manufacturing physical AI, SKAI Intelligence is recognized for advancing beyond synthetic data to digitalize actual manufacturing environments as assets and provide a data infrastructure that connects everything from AI training and robot validation to on-site feedback.

In June of this year, SKAI Intelligence signed a Cooperation Framework Agreement with ABB Robotics and is promoting a partnership that connects ABB’s industrial robotics technology with its own high-precision synthetic data generation capabilities. Following its Series A investment round, the company has continued to attract follow-up investments, further developing its technology and business expansion.

A company representative said, “Our participation in this white paper is significant in that we’ve helped concretize practical methods for implementing physical AI in high-precision manufacturing with global partners. We will continuously expand our physical AI infrastructure business in the global manufacturing and robotics markets, leveraging our digital twin and industrial synthetic data technologies.”

This content was produced with the assistance of AI translation services.