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1. Start from Real Inputs
We begin with real-world inputs—CAD, BIM, layouts, and equipment specifications—grounded in operational constraints.
We don’t model one system at a time. We build a foundation that turns industrial environments into continuously evolving data engines.
OUR APPROACH
Simulation. Data. Physical AI—Built the Right Way.
At MetAI, simulation is not a final step—it’s the starting point. Every asset, environment, and system connection is designed to generate data, support iteration, and scale across industries.
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2. Generate SimReady Assets and Environments
Using MetAI’s AI & 3D integrated generative technology, MetAI creates unified, industrial-grade SimReady assets and environments that are configurable and scalable.
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3. Structure Everything for Data Generation
Assets are built with parameters, behaviors, and logic—not static geometry—so every simulation run produces structured, usable data.
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4. Connect Control Logic
By connecting PLCs, ROS, WMS, scripts, or control policies, simulations reflect how systems actually operate—enabling validation, robotic training, and optimization.
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5. Run, Vary, and Learn at Scale
Scenarios are randomizable and configurable, enabling large-scale experimentation across layouts, conditions, and strategies—without rebuilding models.
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6. Close the Intelligence Loop
Simulation outputs generate insights, synthetic data, and trained policies that feed back into design, operations, and AI systems.
Our Technical Foundation
MetAI is built on OpenUSD for scalable scene composition and integrates with NVIDIA platforms for physics, rendering, and accelerated compute-ensuring industrial-grade performance and interoperability.
DATA PIPELINE
How MetAI Builds a Simulation-Driven Data Pipeline
BENEFITS
What This Enables
Faster validation before build or deployment
Lower risk and cost through simulation-first decisions
Realistic environments for robotic and system-level AI training
A scalable data engine for Industrial & Physical AI
INDUSTRY
Built for Complex Industrial Systems
1Warehouse
Simulate layouts, automation, dispatch strategies, and robotic workflows to optimize throughput, train AI, and reduce operational risk before deployment.
2Advanced Manufacturing
Model construction layouts, production lines, equipment interactions, and robotic operations to validate designs, train autonomous systems, and accelerate ramp-up.
3Data Center
Simulate infrastructure layouts, piping, and operational scenarios to support resilient design and AI-driven optimization.
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