MetAI Integrates NVIDIA USD Search to Accelerate Warehouse Digital Twin Creation
- MetAI is adding NVIDIA Omniverse technologies, including USD Search, to its MetGen platform to turn 2D CAD blueprints into searchable, 3D SimReady warehouse models.
- The upgrade enables quick retrieval of SimReady assets from libraries, cutting build time for AI training and robotics testing.
MetAI, a Taiwan-based member of NVIDIA’s Inception program, is integrating NVIDIA Omniverse technologies into its MetGen digital twin engine. This includes USD Search microservices, which help transform standardized 2D CAD files and structured data into high-fidelity SimReady environments, standardized, ready-to-use digital twins for AI training, robotics testing, and automation.
USD Search lets users instantly locate and pull matching SimReady assets from connected libraries. Missing assets can be generated through MetGen’s pipeline. The system also converts CAD layout blocks into searchable metadata, making builds faster and easier to scale.
"From layout blueprints to SimReady assets, we're building the infrastructure needed to train the next generation of industrial and physical AI," said Daniel Yu, Co-founder and CEO of MetAI, in an official press release. "By integrating NVIDIA USD Search, we're enabling a closed-loop workflow—where users can generate assets with MetGen, build their own searchable libraries, and dynamically retrieve components to streamline simulation creation. This shortens setup cycles and unlocks scalable, intelligent environment generation."
The integration is in pilot use, starting with warehouse automation. MetAI plans to expand to other industries, including data centers, manufacturing, and robotics, with a beta release of MetGen coming in August.
Source: YouTube / MetaAI
🌀 Tom’s Take:
NVIDIA Omniverse and USD are redefining how 3D environments are built and connected. MetAI’s integration shows how a standardized, searchable 3D asset framework can move from CAD files to AI-ready digital twins without slowing down production.
Source: PR Newswire / MetaAI
