RoboForce’s fresh capital will be used to advance its next-generation robotics platform. Commercial deployment will be expanded across demanding industrial environments as a solution to labor and safety challenges.
The Milpitas, California-based company’s oversubscribed round brings its total funding to $67 million.
The new capital was led by YZi Labs, a $10 billion fund. Participation also included Jerry Yang, co-founder and former CEO of Yahoo. Existing investors also joined, including Nobel Laureate economist Myron Scholes, Gary Rieschel of Qiming Ventures, and Carnegie Mellon University.
The funding comes at a time when industrial sectors across the United States and globally are facing persistent labor shortages, rising operating costs, and mounting safety concerns.
RoboForce is aiming to address those pressures with what it calls “Robo-Labor”. That is a category of Physical AI robots designed to take on physically demanding, repetitive, and hazardous work in industrial settings.
RoboForce founder and CEO Leo Ma said the company’s goal is to move human workers into safer, higher-value roles while robots handle the most demanding industrial jobs.
What RoboForce Does
RoboForce is building general-purpose robots powered by Physical AI. These artificial intelligence systems will operate in the real world through machines that sense, learn, and take action in dynamic environments.
The company’s robots are being developed for industries where labor is often difficult to recruit, retain, and protect. Those sectors include utility-scale solar, data centers, mining, shipping, manufacturing, and logistics.
What these environments have in common is that they are often dull, dirty, dangerous, or highly repetitive, making them prime candidates for robotics deployment.
How the $52 Million Funding Will Be Used
RoboForce said the new capital will support three major priorities as the company transitions from research and development to scaled deployments.
The first priority is advancing its robot foundation model and Physical AI learning system. The company is building a data flywheel that combines real-world fleet data with high-fidelity simulation. This creates a closed-loop learning environment where robots continuously improve performance based on deployment feedback and synthetic training scenarios.
The second priority is to scale manufacturing and strengthen the Physical AI robot platform for commercial readiness. Increasing production capacity and improving supply chain operations are key. Robots can then be deployed reliably in harsh and unpredictable industrial environments.
The third focus is commercialization and revenue growth. RoboForce plans to move active pilot programs into production-scale deployments while building recurring revenue relationships across critical industries.
This combination of AI model development, robotics manufacturing, and commercial deployment reflects a broader shift in the robotics market.
Investors are increasingly looking for companies that can move beyond prototypes. They are seeking demonstration of real-world adoption, repeatable deployment, and revenue potential.
RoboForce and NVIDIA Collaboration
A key part of RoboForce’s strategy is its collaboration with NVIDIA, whose technologies are serving as the backbone of the company’s AI and simulation infrastructure.
RoboForce said it is using NVIDIA Jetson Thor at the edge, along with NVIDIA Isaac Sim and NVIDIA Isaac Lab open frameworks for simulation and robot learning. The company is also leveraging NVIDIA Cosmos for synthetic data generation and NVIDIA OSMO for cloud-to-edge orchestration.
Together, these technologies help create a continuous data flywheel that can accelerate robot policy learning and improve reliability in complex industrial settings.
In practical terms, that means RoboForce is trying to make its robots more adaptable and more scalable. Moving from pilot testing into real-world operations is critical.
This use of simulation, synthetic data, and edge computing is becoming increasingly important in the Physical AI market.
Industrial robots must perform reliably in less-controlled environments than factory assembly lines. Companies that can train robots effectively for those conditions may gain a major competitive advantage.
Why Physical AI and Robo-Labor Matter
RoboForce’s funding round highlights the rising momentum behind Physical AI and industrial robotics. While public conversation around AI focuses on chatbots and software platforms, the application of AI in the physical world is a major frontier.
Sectors such as logistics, manufacturing, construction, energy, and mining are prime targets.
The Future
Experts from Carnegie Mellon University, the University of Michigan, Amazon Robotics, Google, Waymo, Cruise, Tesla Robotics, ABB, and Apple helped found the company in 2023.
They created a deep bench of experience across robotics, autonomous systems, and advanced engineering. With their involvement the company is positioned for ,the next wave of industrial automation.
RoboForce is betting that Robo-Labor will become an increasingly important part of the future workforce.
