Gravis Robotics to scale autonomous heavy equipment globally with $200M funding round

Gravis Robotics has raised $200 million during its Series A funding round backed by SoftBank. The funding will accelerate Gravis's mission in physical AI — scaling autonomous heavy machinery across job sites globally. 

Global infrastructure is in the middle of a massive expansion. Scaling the energy networks and data centres required for the AI economy is driving unprecedented demand, and the need for housing, transit, and climate-resilient infrastructure is equally urgent. Across every sector, construction has become the primary bottleneck, and we cannot reshape the physical world fast enough to keep up with demand. That shortfall stems from a severe labour crisis, but fixing it isn't just about hiring more people — it requires augmenting the workforce through automation. Heavy construction remains one of the least automated major industries in the world, still run largely on machines that operate similarly to how they did 50 years ago.

Building the future requires deep tech to solve a major challenge: translating advanced artificial intelligence into precise, real-world execution. 

How Gravis Robotics' autonomous equipment offers specialized solutions for construction

Most physical AI operates in static worlds. Self-driving cars steer around obstacles on smooth pavement, while humanoids and robotic arms move objects across fixed countertops or warehouse floors — leaving their surroundings completely undisturbed. But heavy equipment operates much differently. It often intentionally crashes into the environment, breaking apart soil with hidden rocks and reshaping the earth. 

AI doesn't just find a clear path through a static world; it actively takes that world apart and puts it back together. Gravis Robotics intends to solve this challenge with models enriched by vast simulated experiences and that efficiently bridge the sim-to-real gap. 

This synthetic training lets Gravis Robotics move billions of cubic yards of virtual earth — from soft clay to rock-filled soil — and enables its software to bring factory-floor precision to historically unpredictable civil jobsites. Rather than simply imitating individual operators, its AI world model incorporates the distinct performance characteristics of a wide range of manufacturers, making it generalizable and adaptable in a way single-machine systems can't match.

Dominic Jud, CTO and co-founder of Gravis Robotics, says that "Skilled operators read the earth through subtle physical feedback — listening to the engine strain, sensing the machine vibration, and reacting to hydraulic resistance. Our AI takes that same physical input and grounds it in machine telemetry, responding to varying subterranean forces and soil mechanics at microsecond speeds. We didn't try to simplify the world for our software; we gave it the physical intuition to handle real job sites with precision that goes beyond what any human can feel from inside the cab"

Mixed fleets can access a uniform system without customization 

The heavy equipment market is highly fragmented, with roughly two-thirds of global demand sitting outside the top-three manufacturers. Contractors choose machinery based on deep regional service relationships and existing fleet investments — they shouldn't be forced into a closed, single-brand ecosystem.

Acting as an operating system for mixed fleets, Gravis Robotics' software runs on the Gravis Rack — the autonomous control kit — which has been installed across a range of machinery brands including Caterpillar, Case, Develon, John Deere, JCB, Hitachi, Sumitomo, Yanmar, Volvo, and more. Gravis Rack transforms conventional machines into fully robotic systems. Because its learning-based models excel at adapting to the nuances of machines, the same core software can drive a compact excavator or a machine five times its size without custom reprogramming.

The Gravis Rack kit can be retrofitted to existing machines

This deep understanding of the nuances of individual machines and how they interact with the ground has allowed us to squeeze productivity from these systems — delivering up to a 30 percent boost in job site productivity compared to peak manual operation, while simultaneously improving overall worksite safety.

Its software stack is built for ultimate operational flexibility, offering a full spectrum between AI-augmented manual control and full autonomy. With Gravis Copilot, operators stay in the cab, utilizing real-time 3D guidance and hazard detection to elevate their daily performance. When full autonomy is engaged, those same operators can step away into safe and social environments to supervise entire robotic fleets at once. Regardless of the mode, every Gravis-equipped machine acts as a continuous site sensor — automating surveying and hazard mapping in the background as the work gets done.

Scaling alongside a changing world 

With systems already deployed alongside global infrastructure leaders across four continents and proven across diverse real-world machinery and sites, we have both the technology and capital to scale rapidly.

This investment powers a global rollout, bringing physical AI directly to construction sites and embedding our autonomous systems into heavy machinery fleets across a trillion-dollar market bottlenecked by labour shortages.

Building on this momentum, Gravis was recently selected to lead an $8 million U.K. government-backed CAM Pathfinder project in partnership with Flannery Plant Hire, a provider of operated heavy-equipment rentals. Together we are retrofitting excavator fleets with the Gravis Rack — giving contractors turnkey, on-demand access to autonomous machinery to help accelerate Britain's $716 billion infrastructure pipeline.

Ryan Luke Johns, CEO and co-founder of Gravis Robotics, shared that "To build the future, we need to change the world, literally. Whether we are building housing, modernizing energy grids, or scaling data centers, every project starts with moving earth. That foundational work has been the bottleneck slowing down the entire built environment. Our machines are built for the messy, unscripted reality of live job sites that breaks traditional automation. With SoftBank's backing, we can hire the best builders and engineers, put Gravis-powered autonomy on every major job site, and scale faster than anyone thought possible"