FieldAI Accelerates Industrial Customers’ Adoption of AI in Collaboration with NVIDIA
Extended use of NVIDIA Omniverse libraries amplifies FieldAI’s real-world operations flywheel, enriching every customer deployment’s value in realizing the benefits of Physical AI adoption
FieldAI, the leader in deploying general-purpose robots in unstructured environments, announced further collaboration with NVIDIA, deepening its use of NVIDIA Omniverse libraries to accelerate the industry’s most extensive real-world data flywheel operating on industrial customer sites across the globe. What used to take customers months of manual effort can now happen in hours as a natural byproduct of robots doing their jobs. As customers move to adopt Physical AI across their operations, FieldAI’s rapidly growing fleet is proving that every deployment delivers compounding value as robots get smarter with each mission and site intelligence grows richer over time.
The expanded collaboration reflects a broader inflection point in robotics, where advances in foundation models, simulation, and hardware are converging to enable robots to learn faster and better augment human efforts in the real world. FieldAI is integrating NVIDIA Omniverse libraries in its development pipeline to deliver demonstrable customer value in environments once thought to be too unpredictable for robots – from active construction sites where conditions change hourly to mining and energy operations with extreme conditions, limited access, and complex infrastructure. With customers expanding across North America, Europe, and Asia, FieldAI’s rapidly growing fleet feeds a corpus of real-world data into workflows built on NVIDIA open libraries and frameworks, providing customers with capabilities such as three-dimensional reconstruction of high-fidelity digital twins to support critical resource allocation decisions including asset maintenance, on time delivery, and site safety.
“With existing deployments across the globe and growing demand from industrial customers to bring AI into physical operations, we are accelerating our operations flywheel by combining FieldAI’s real-world robotic deployments and on-edge models with NVIDIA’s powerful simulation technologies and AI infrastructure,” said Ali Agha, CEO of FieldAI. “The result radically lowers costs for our customers and enables near-instant deployment in the field, enabling customers to scale Physical AI across complex environments where traditional automation has struggled. Recently, a senior executive at a global industrial manufacturing company noted that what once took three and a half months for them now takes just twelve hours with FieldAI’s technology, over 200 times faster than manual methods.”
Historically, one of customers’ most pressing challenges has been gaining visibility into their facilities and operations through digital twins for planning, analysis, and optimization. Customers repeatedly cite these reconstructions as resource-intensive and of little value given the time lag between images captured and reconstruction complete. FieldAI’s collaboration with NVIDIA will drastically reduce the customer’s effort by using NVIDIA Omniverse NuRec, a 3D reconstruction technology that transforms raw sensor data into interactive digital environments.
FieldAI’s customer deployments capture this data daily, powering the evolution of the reconstruction and producing simulation-ready environments in NVIDIA Isaac Sim and Isaac Lab open simulation frameworks, where robot policies are trained and validated to expand the scale of deployments. FieldAI is also adopting the NVIDIA Physical AI Data Factory Blueprint via the Microsoft Azure toolchain to streamline their synthetic data pipeline and robot training using NVIDIA Cosmos open world foundation models and NVIDIA OSMO.
“Building robust autonomy requires systems that can learn directly from real-world operations,” said Shayegan Omidshafiei, President and CSO of FieldAI. “At FieldAI, our robots operate across diverse environments and generate rich signals that allow us to improve perception, reasoning, and decision-making over time. By integrating this capability with NVIDIA Omniverse libraries, we can transform those deployments into continuously evolving digital twins that support both operational insight and more capable robotic systems.”
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“Transforming industrial sectors requires scaling physical AI to handle the sheer unpredictability of the real world,” said Amit Goel, head of robotics ecosystem at NVIDIA. “By leveraging the NVIDIA physical AI stack, FieldAI is delivering the general-purpose intelligence needed for robots to navigate and reason through complex environments, turning challenging worksites into hubs of autonomous productivity.”
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