FieldAI is building general robot intelligence for the physical world. FieldAI’s technology enables robots to operate safely and reliably in unstructured environments where most of the world’s work happens, without prior maps, GPS, predefined routes, or supporting infrastructure. Its hardware-agnostic approach works across different robot types, allowing customers to deploy the right form factor for the job. FieldAI robots are deployed globally across hundreds of customer sites on three continents, supporting industries including construction, energy, security, and manufacturing. Founded by veterans of NASA JPL, DARPA, and Google DeepMind, FieldAI is bringing AI off the screen and into the field.
External link for FieldAI
Irvine, CA 92602, US
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🤖 Robots need real-world data to get smarter. But they need to be safe enough to deploy before they can collect it. That’s the Catch-22. FieldAI and Ali Agha using physics to help break the loop, turning every real-world deployment into more data for the next generation of robots. 🔄 #Robotics #PhysicalAI #RobotLearning
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Robot.com has unveiled R-dog, a new quadruped concept for delivery and interactive advertising, powered by FieldAI’s Field Foundation Models. Field Foundation Models (FFMs) serve as an operational AI layer that generalizes across robots and environments and serves three roles: enabling safe and reliable operations in dynamic, real-world spaces without prior information or supporting infrastructure; preventing model hallucinations through physics-grounded AI models; and coordinating multiple robots working together. Learn more about R-dog and the expanded collaboration below.
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For a decade, delivery robots have hit the same problem: the last 100 meters. Stairs. Curbs. Thresholds. Wheeled robots stop. People take over. Today, we’re introducing R-dog. 🐶🤖 A four-legged robot concept designed to go where wheels can’t and grab people's attention when it gets there. 📦 Delivery: Navigate the final stretch with stacked food orders, packages, and autonomous drop-off. 📺 Advertising: Turn that same presence into a real-world brand experience through dual screens, voice, movement, and interaction. But getting a robot into more places requires more than a new form factor. It requires a new approach to autonomy. That’s why, as R-dog moves toward production, we’re expanding our ongoing collaboration with FieldAI. Its Field Foundation Models will serve as R-dog’s autonomy brain, helping it operate safely and reliably in dynamic, unpredictable environments where the map runs out. 👀 R-dog runs on #REMI, the same platform that powers our entire fleet. We’re adding a new form factor to an ecosystem already operating 500+ robots globally. 🎉 Commercial deployments are targeted for 2027. 👉 https://lnkd.in/gCMMBGfK
Shayegan Omidshafiei, FieldAI President and Chief Scientist, gave the keynote “Autonomy in the Wild” at AUTONOMOUS: The Future of Robotics & Physical AI in San Francisco. The premise: what does it take for a robot to arrive at a site it has never seen, with no prior map, no GPS, and no site-specific training—and get to work? FieldAI robots do exactly that across hundreds of deployments in construction, energy, and other complex industrial environments, where conditions are constantly changing and robots must operate safely around people, equipment, and incomplete information. Full keynote linked here: https://lnkd.in/g-qyy7EE
We’re excited to join the 2026 Disney Accelerator cohort. Looking forward to the collaboration, insights, and opportunities ahead.
The Disney Accelerator is excited to welcome FieldAI, Physical Intelligence, Promise, OpenArt AI, and Simile to its 2026 program! Since 2014, the Disney Accelerator has invited visionary founders to contribute to Disney’s long legacy of innovation in service of creativity. This year’s program will culminate with the 2026 Disney Accelerator Demo Day on the Walt Disney Studio Lot in early November. Read the full announcement: http://di.sn/6042BEFvDA
At Automate in Chicago, FieldAI CEO Ali Agha joined Brian Heater for a special live episode of The Automated Podcast at the Humanoid Robot Forum. They discussed why robotics requires models purpose-built for the physical world, rather than shoehorning large language models into robotics. FieldAI’s Field Foundation Models combine data-driven learning with physics-based reasoning and uncertainty awareness, enabling one AI brain to operate across robots, tasks, and environments without prior maps, GPS, or predefined routes. FieldAI already powers robots across three continents, from construction and industrial to critical infrastructure inspection and beyond, with each new workflow expanding the value of robots already in the field. Watch the full podcast here: https://lnkd.in/gwRWsmG9
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Our live Automated with Brian Heater recording with FieldAI's Ali Agha is available now. Great chat, fun episode. I learned a lot. Highly recommend it if you weren't there to see it in person. Live from Automate Show 2026 https://lnkd.in/gEF4andc
FieldAI reposted this
What connects a helicopter flying on Mars, autonomous robots exploring caves with no GPS, and machines navigating active construction sites? Ali Agha's career. The Founder and CEO of FieldAI joined Brian Heater for a live recording of the Automated podcast at Automate 2026, and the conversation went well beyond the usual physical AI talking points. Ali traced the work back to his time at Qualcomm and NASA JPL, including the technology behind the Ingenuity Mars helicopter and projects that sent legged, wheeled, and flying robots into environments with no maps, no roads, and no prior information. Those experiences shaped how Field AI approaches autonomy today. Rather than treating every unexpected condition as an edge case to patch later, Field AI designs its systems with uncertainty, risk, and real-world variation in mind from the beginning. That matters when a robot is operating around dust, fog, changing light, hanging wires, unfinished scaffolding, moving people, or terrain it has never encountered before. Ali also explains why Field AI is not simply trying to recreate the language-model approach for robotics. A wrong word generated by a chatbot can be corrected. A wrong physical action from a robot carries a very different level of risk. Their approach combines learned models with real-time physics and uncertainty measurements, allowing a robot to recognize when a sensor is degrading, when it is encountering something unfamiliar, and when it needs to slow down or gather more information. And all of that processing happens on the robot. No cloud connection, Wi-Fi, or 5G required. Today, Field AI’s software is running across 34 different robot embodiments, from small quadrupeds to multi-ton vehicles, with deployments spanning construction, energy, logistics, manufacturing, and urban environments. Catch the full episode at automated.fm
At MACHINA 2026 in Paris, FieldAI CEO Ali Agha took the stage to discuss what it took to move Physical AI beyond controlled demonstrations and into real-world deployment. In safety-critical environments, intelligence cannot rely on pattern recognition and data scale alone. Language models can hallucinate with limited real-world consequence. In robotics, a hallucination can become an unsafe action around people, heavy machinery, or critical infrastructure, where even a single error can cause physical harm or operational disruption. Ali shared how FieldAI’s architecture-first approach combines data-driven learning with physics-based reasoning, uncertainty awareness, and risk-aware decision-making. The result is robot intelligence designed to operate safely and reliably in unpredictable environments, across different robots, tasks, and industries. Deployment over demos means building for the conditions robots actually face in the field.