Addverb, a global robotics and warehouse automation company, has expanded its end-to-end robotics development workflow using NVIDIA AI, simulation and edge computing platforms. The enhanced workflow is being deployed across Addverb’s Trakr quadruped robot and Elixis-W wheeled humanoid, enabling faster design, training, testing and large-scale deployment of next-generation industrial robots.

As part of this initiative, Addverb is leveraging NVIDIA Omniverse libraries and open NVIDIA Cosmos World Foundation Models to build high-fidelity digital twins of real-world warehouses and industrial environments. These physically based virtual environments enable large-scale testing and optimisation using synthetic data, helping validate robot behaviour earlier in the development cycle and reducing time to deployment.

Commenting on the expansion, Sangeet Kumar, Co-founder & CEO, Addverb, said, “By combining digital twins, NVIDIA GPU-accelerated robot learning, and edge AI through our collaboration with NVIDIA, we are strengthening our ability to validate robotic systems faster, improve sim-to-real confidence, and reliably scale deployments across diverse industrial environments. This collaboration has been instrumental in accelerating innovation while ensuring our robots perform consistently and safely in real-world shopfloor conditions.”

To strengthen sim-to-real transfer, Addverb is adopting NVIDIA Isaac Lab, a GPU-accelerated, open-source robot learning framework built on NVIDIA Isaac Sim. Isaac Lab enables scalable training and evaluation of robot policies while supporting reinforcement learning workflows within a unified development stack.

Addverb is also evaluating simulation workflows enabled by Newton, an open-source physics engine co-developed by NVIDIA, Google DeepMind and Disney Research, and managed by the Linux Foundation. Additionally, Addverb is exploring server learning and edge deployment on NVIDIA Jetson Thor for Vision Language Action (VLA) models.

For industrial deployment, Addverb’s robots are powered by NVIDIA Jetson Orin NX, with NVIDIA TensorRT enabling low-latency, high-performance inference at the edge. This supports real-time perception, navigation and decision-making across complex warehouse and industrial operations.

“Advances in robotics require seamless integration of AI, simulation and edge computing,” said Amit Goel, Head of Strategic Robotics Partnerships at NVIDIA. “Our collaboration with Addverb reflects NVIDIA’s commitment to empowering partners with the tools and platforms needed to accelerate innovation, improve reliability, and bring scalable automation to industrial environments worldwide.”

This expanded workflow reinforces Addverb’s focus on building production-grade Physical AI systems that deliver intelligent, scalable automation for warehouses and industrial facilities worldwide.

Addverb’s Physical AI robots, powered by this NVIDIA-enabled workflow, are on display until 20 February 2026 at Bharat Mandapam, New Delhi, as part of the India Impact AI Summit 2026, demonstrating production-ready automation for real-world industrial environments.