When it comes to building robotic brains, many companies in the industry focus on putting intelligence directly into their robots.
General Robotics is taking an alternate approach. The Redmond, WA company’s GRID system hosts its robotics intelligence layer in the cloud, allowing it to be delivered and deployed to robots operating remotely.
GRID hosts the models, simulations, robot representations, data and agents through which robotic skills are developed, tested, orchestrated and deployed to robots on site. “Having one layer that looks after 50 to 100 robots is way more important than 50 or 100… robots that operate completely independently,” said General Robotics CEO Ashish Kapoor.
While videos of sprinting robots crashing into pads — or humanoid robots kickboxing and breakdancing – often go viral, General Robotics focuses instead on industrial models. Its GPU-based GRID cloud provides a better base to ingest data and develop skills for specific verticals.
“Our ability to onboard new robots, our ability to take them to deployment with new skills, our ability to connect very complex simulations to the reality is enabled through GRID,” Kapoor said.
The company declined to talk in detail about its customers, but Kapoor offered an example of how the GRID-based system works. In a biolab, for instance, robots pouring liquid from beakers required in their modeling fluid tactile interaction and transparent materials.
“There exists no good way of modeling those kinds of behaviors in software right now because [of]…all of those things,” Kapoor said. “…This is where agents came in.”
AI agents were used to create a “hybrid simulator” that brought the pieces together in the cloud. The robots were then tested against the simulated model.
“The physics of the robot was coming from one simulator and… the calculation of fluid dynamics was actually created by [the] agent itself by looking at the literature,” Kapoor said. What “otherwise would have taken us at least a year to build…was done in minutes.
“GRID allows you to auto engineer those robots, retarget those skills, [and] create appropriate digital representations on its own,” Kapoor said.
Humans are involved in safety checks to make sure robots behave according to specifications.
While humanoid robots are the ones often drawing media attention, “the most value in robots in 18 months to 36 months is going to be realized in heavy industries,” he said. “These are ports, these are your energy infrastructures.”
Although the company’s cloud-based GRID architecture has advantages, the system also faces some challenges — namely, lagging cloud-to-robot communication.
“The round-trip time, the latency is of paramount importance,” Kapoor said. “The robot needs to have two loops.” He described that second loop as an “inner control loop…operating at a millisecond level…that’s on the edge.”
Another issue involves companies that must meet strict regulatory and security requirements. For example, car companies are generally against putting proprietary information —whether that be designs for new fuel injection systems or new battery designs — in the cloud.
Still, General Robotics remains optimistic its system can handle these kinds of issues long term. “Between commercial cloud deployment, between on-prem server deployment and…edge deployment, we do have a way of addressing many of these issues,” Kapoor said.
In addition to continually improving its stack, the company also seeks out partners that can help it resolve challenges, Kapoor said.
That robotics is a growing field seems obvious. Morgan Stanley in a 2025 study predicted the humanoid robot population would touch 1 billion by 2050 and be valued at $5 trillion. And a more recent study from Counterpoint Research estimated that between 50,000 and 85,000 humanoid robots would ship this year alone.
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