Key Facts
- Field AI is an Irvine-based robotics software company, founded in 2023 by Ali Agha, Shayegan Omidshafiei, and David Fan, that reached a $2 billion valuation in August 2025 after raising $405 million, backed by Jeff Bezos, Bill Gates, and Nvidia.
- Who founded Field AI: Ali Agha, Shayegan Omidshafiei, and David Fan, a team with roots in NASA's BRAILLE planetary exploration project.
- How much has it raised: $405 million across two rounds in 2024 and 2025, reaching a $2 billion valuation, up from $500 million a year earlier.
- Who are its investors: Bezos Expeditions, Gates Frontier, NVentures (Nvidia's venture arm), Intel Capital, Temasek, Khosla Ventures, Canaan Partners, and Samsung, among others.
- What are Field Foundation Models: A new class of AI models built specifically for robots, designed to handle uncertainty and risk in unstructured, real-world environments without needing GPS, maps, or pre-programmed routes.
From Mapping Lava Tubes for NASA to Building a $2 Billion Robotics Company
Field AI's origins trace back further than its official 2023 founding date suggests. According to reporting from Parola Analytics, the company's founding team began developing autonomous systems as far back as 2016, through NASA's BRAILLE project — an effort focused on using robots to map planetary-like lava tubes without satellite data or preloaded maps. That specific problem — getting a robot to navigate and understand an environment with zero prior knowledge and no GPS signal, the exact conditions found on other planets — turned out to be a direct technical precursor to the commercial problem Field AI would eventually build a business around: unstructured, GPS-denied environments on Earth, like construction sites, mines, and disaster zones.
The company was formally founded in Irvine, California, in 2023 by Ali Agha, Shayegan Omidshafiei, and David Fan, who serves as CTO, alongside COO Justin Saeheng. Field AI was previously known as "AI for Humanity" before rebranding. The founding team's stated mission was ambitious from the outset: creating a general-purpose, deployable robotic intelligence — a "universal brain" for machines that could adapt across different robot platforms and physical environments, rather than requiring bespoke software for each new robot or use case.
The Fastest Valuation Jump in Robotics: $500 Million to $2 Billion in a Year
Field AI's rise to unicorn status happened in two distinct funding stages. The Information reported in February 2025 that the company was already in talks with investors to raise money at a $2 billion valuation — but the deal that actually closed and pushed the company across that threshold came later that summer. SiliconANGLE and CNBC reported that Field AI raised $405 million across two rounds: an initial $91 million round in late 2024, followed by a larger $314-315 million round that closed and was announced on August 20, 2025. That combined raise pushed Field AI's valuation to roughly $2 billion — up sharply from a $500 million valuation just a year earlier.
The investor roster reads like a cross-section of the most prominent names in technology and venture capital: Jeff Bezos' family office Bezos Expeditions and Prysm Capital co-led the larger round alongside sovereign wealth fund Temasek. Additional backers included NVentures — Nvidia's corporate venture arm — Intel Capital, Khosla Ventures, Canaan Partners, BHP Ventures (the venture arm of the mining giant, a strategically relevant investor given Field AI's focus on mining applications), and Emerson Collective. Earlier-stage investors included Gates Frontier, the investment vehicle associated with Microsoft co-founder Bill Gates, and Samsung. GeekWire and CNBC both reported that the round was oversubscribed, with far more investor interest than the company needed to fill it.
What Makes Field Foundation Models Different From Retrofitted AI
Field AI's core technical product is what it calls Field Foundation Models, or FFMs — described by the company and by GeekWire's coverage as fundamentally different from conventional vision or language models simply retrofitted for robotics use cases. Instead, FFMs are purpose-built from the ground up to grapple explicitly with uncertainty, physical risk, and the constraints of the real world, allowing robots to safely navigate and operate in dynamic, unstructured environments without prior maps, GPS signals, or predefined paths.
That "uncertainty-aware" framing is the company's central technical differentiator. Parola Analytics' patent analysis describes Field AI's models as embracing uncertainty rather than trying to eliminate it, allowing robots to anticipate multiple possible outcomes and make faster, safer decisions in unfamiliar or hazardous conditions, rather than freezing or failing when they encounter a situation outside their training data. Startup Intros' technical description adds that the platform relies specifically on "Belief World Models" for risk-aware navigation, and works across tracked robots, heavy machinery, and multi-robot coordination scenarios without requiring prior maps or planned routes. Crucially, the platform is described as hardware-agnostic and embodiment-agnostic — meaning the same underlying software "brain" can be attached to humanoid robots, quadrupeds, wheeled robots, drones, rovers, and industrial vehicles, rather than being built for one specific robot form factor.
Designed to Run on the Edge, Not in the Cloud
A specific technical detail that distinguishes Field AI's approach from many AI systems built around large, cloud-hosted models: the company designed its "universal brain" to run entirely on the edge, directly on the robot itself, reducing dependence on heavy cloud infrastructure and enabling rapid deployment even in environments with poor or nonexistent connectivity — a practical necessity for robots operating in remote construction sites, mines, or disaster response scenarios where reliable network access can't be assumed. That edge-first design reflects the same underlying philosophy as the company's uncertainty-aware modeling: build for the messiest possible real-world conditions from day one, rather than assuming an idealized operating environment and hoping it holds.
A Team Built From the Biggest Names in Robotics and Autonomy
Field AI's workforce draws heavily from some of the most prominent research organizations and companies in robotics, autonomous systems, and AI. Parola Analytics' reporting describes a team including veterans of NASA JPL, DARPA, DeepMind, Google Brain, Nvidia, Qualcomm, Tesla, Zoox, Cruise, Toyota Research Institute, SpaceX, Boston Dynamics, Amazon, and Microsoft — an unusually dense concentration of frontier robotics and autonomy talent for a company only a few years old. A separate federal-focused subsidiary, FieldAI Federal, specifically markets itself around this pedigree, describing "unparalleled edge autonomy for federal applications" built by veterans from DeepMind, NASA JPL, Tesla, Nvidia, and Amazon — signaling a deliberate push into defense and government contracting as a distinct business line alongside Field AI's commercial industrial applications.
Commercial Applications: From Construction Sites to the Battlefield
Field AI's commercial focus spans construction, oil and gas, mining, utilities, and manufacturing, powering humanoid, quadruped, wheeled, and heavy machinery platforms for tasks including site mapping, material handling, equipment inspection, and coordinating multiple robots working together. GeekWire's reporting adds urban delivery and inspection to that list, describing the company's technology as attachable to third-party robot hardware across all of these use cases. The dedicated FieldAI Federal subsidiary extends that reach into defense and government applications specifically, placing Field AI alongside companies like Anduril Industries and Palantir Technologies as part of a broader wave of venture-backed startups building AI-powered autonomy for military and federal use cases.
By late 2025, Parola Analytics reported that Field AI was scaling operations not just domestically but across the United States, Japan, and Europe, with its Field Foundation Models already being actively deployed across customer sites worldwide — evidence that the company's technology has moved past pilot-stage testing into genuine multi-region commercial deployment.
Why Investors Are Betting Billions on Uncertainty-Aware Robotics
Field AI's rapid valuation growth reflects a broader thesis gaining traction across the venture capital and robotics industry in 2025: that the biggest remaining barrier to widespread robot deployment isn't better actuators, sensors, or physical hardware — all of which have matured substantially over the past decade — but software intelligent enough to handle the sheer unpredictability of real-world environments outside of tightly controlled labs or warehouses. GeekWire's reporting draws a direct parallel to Physical Intelligence, another Bezos-backed robotics startup that raised $400 million around the same period, suggesting Bezos Expeditions is making a broader, multi-company bet on the "software brain" layer of robotics becoming the most valuable and defensible part of the entire robotics value chain, rather than the hardware itself.
Field AI's specific bet — that a single embodiment-agnostic model, designed from the ground up around uncertainty and risk rather than assuming clean, mapped, GPS-enabled conditions — can become the default intelligence layer running underneath a huge range of otherwise unrelated robot hardware platforms, is what has attracted such a concentrated roster of strategic investors spanning big tech (Nvidia, Intel, Samsung), sovereign capital (Temasek), and prominent individual technologists (Gates, Bezos) within just two years of the company's founding.
FAQ
Who founded Field AI? Ali Agha, Shayegan Omidshafiei, and David Fan, a team with roots in NASA's BRAILLE planetary exploration project.
How much has it raised? $405 million across two rounds in 2024 and 2025, reaching a $2 billion valuation, up from $500 million a year earlier.
Who are its investors? Bezos Expeditions, Gates Frontier, NVentures (Nvidia's venture arm), Intel Capital, Temasek, Khosla Ventures, Canaan Partners, and Samsung, among others.
What are Field Foundation Models? A new class of AI models built specifically for robots, designed to handle uncertainty and risk in unstructured, real-world environments without needing GPS, maps, or pre-programmed routes.
What industries does Field AI serve? Construction, energy, mining, utilities, manufacturing, urban operations, and federal/defense applications.
Source: CrackTheDeck Research.