Skild AI rockets to $100 million run rate just 10 months after going live

What happened and why it matters

Skild AI makes software that helps robots learn tasks, and 10 months after starting commercial use it hit a recurring revenue run rate of $100 million. "This is a major milestone for us as it signifies a new chapter for robotics, moving from an era of demos to an era of deployments," co-founder and CEO Deepak Pathak said.

The three-year-old company's technology is in use at over 60 companies and is running on hundreds of robots, up from eight earlier this year. Its clientele includes Japanese cafes as well as US warehouses. Skild did not provide a customer list, though it previously announced a partnership with Nvidia and Foxconn for robotics automation at a Houston chip factory.

Money and momentum are feeding each other. In January, Skild closed a $1.4 billion round that lifted its valuation to $14 billion, more than tripling it from seven months earlier. While other well funded robotics startups are still working out how to turn tech into a business, Pathak said the recent capital let Skild prioritize scaling real-world deployments instead of chasing demos designed to go viral. He referenced the recent humanoid sports competitions held in China as "fun entertainment," but added "that's not the only area where robotics is taking off."

Inside S1: how robots learn by watching

Last month Skild introduced S1, an AI model that lets humanoid robots pick up a fresh skill by observing a human demonstration. The system uses in-context learning so robots can carry out multistep routines that run longer than 10 minutes, learning directly from video, even when they lack prior training data for those exact actions.

Bloomberg reviewed a clip in which a robot, after watching a person, learned to pot a plant. "You can show the robot how to make coffee, and it will make it in exactly the same way that you did," Pathak said. "Learning tasks this long lets S1 automate far more valuable work than any prior model." He also described a demonstration where a robot flipped a pancake after a single example, despite never seeing that task in the training data. "The first time it flipped a pancake, we could not believe it," he said. "The robot learned by looking at the motion of the spatula in the video."

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Skild's broader bet is a generalized AI-powered brain for robots that can adapt across tasks by learning through observation and practice, rather than being tuned for a single job. Its software spans many platforms, including quadrupeds as well as robotic arms and hands.

Where it is used and what comes next

Skild's stack is already running in settings such as coffee shops in Japan and US logistics facilities. It is compatible with deployments in hospitals, homes, warehouses and factories, and is built to aid humanoids in tackling advanced physical tasks - everything from vaulting over obstacles to picking up items for household duties such as loading a dishwasher, cooking, and cleaning up.

Pathak said signing early customers sped up data collection. "It's about establishing a data flywheel," he said. "The more you deploy, the more data you get, which improves the AI brain and leads to even more deployments." For your wallet, the signal is clear enough: real revenue, rapid expansion in live robots, and longer, more useful tasks suggest this is shifting from lab demo to practical utility.

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