Eka Robotics Hits $1.45 Billion Valuation on Force-Sensing AI

Robotics startup Eka Robotics has closed a $150 million Series A at a $1.45 billion post-money valuation, led by a16z and F-Prime, on the strength of a robot that picks up 1,500 objects an hour — roughly 2.5 times the pace of a human worker.

Eka says its system reliably grasps objects more than 95% of the time, handling items weighing up to 1 kg. The company was founded by MIT professor Pulkit Agrawal and former Google DeepMind researcher Tuomas Haarnoja, who first met in graduate school at the University of California, Berkeley.

"They are already exceeding superhuman performance for certain tasks, and so we think over the next few months there will be superhuman performance in many dexterous manipulation tasks," Raghu Raguram, the a16z general partner who co-led the round, told TechCrunch.

Why are veteran roboticists impressed?

The demonstrations have startled experienced robot builders. Kris Hauser, a professor at the University of Illinois Urbana-Champaign, said the Eka robot had a "wow factor" compared with other recent demos and "was able to adapt to a large number of different objects without retraining." He also noted a "humanness, creepy humanness that it would try over and over again if it failed the first time."

Another roboticist, who asked for anonymity because of their work at a frontier lab, compared seeing Eka's robot in action to the moment robots first achieved reliable legged locomotion five to ten years ago. The arm moves fast enough to hurt itself, which suggests confidence in the control software. "They have a lot of trust in their algorithm not breaking the robot. I wonder how many robots they broke along the way?" that observer said.

The same roboticist handed the machine a raspberry — their lab's favorite stress test — and described "a big, heavy robot rushing towards my arm and then slowing down just in time and very gently touching me." That gentleness is the point: the gripper doesn't crush the fruit.

How does the model work?

Eka's core departure is architectural. Instead of the vision-language-action models that dominate generative robotics, Eka built a vision-force-action model that maps the relationship between language, force inputs, and actions. Critics of the current direction, including robotics veteran Rodney Brooks, have argued generative robotics models will fail without representing force and touch. Eka's results give that argument weight.

"Vision is not the primary way in which you close this last millimeter problem," Agrawal told TechCrunch. "Vision tells you roughly where the object is, what the pose is, but the actual grabbing, the actual searching is happening through forces."

To make that work, Eka designed a custom hand with more force sensors and more flexibility than traditional grippers, one that reacts to contact. The founders won't share full details for competitive reasons, but the method involves a physics simulator modeling the multiple forces a robot encounters during a grasp, then converting that into a reinforcement learning environment that runs at scale. The company says it can generate thousands of hours of robot experience in minutes.

"Rather than being limited to the data that you're collecting from, say, human demonstrations, Eka is pushing through reinforcement learning this approach where the robot can surpass any kind of demonstrations that are given to it," Hauser said. "What's really exciting is that they're able to not be limited to the data that is presented to them for training."

What does Eka's bet change?

Agrawal frames the company's contribution as closing a stubborn gap in the field. "What EKA is bridging is the generality-performance gap, which plagues a lot of modern robotics," he said.

Today's most generalizable physical AI models handle many tasks but handle them poorly, while single-task specialists struggle to close a business case. Eka's positioning is complementary: a general model — the source cites an LLM operating a robot in an unfamiliar setting — decides what to do, while Eka's model handles the physical execution, such as picking up a dish without breaking it.

"Most of the field has been focusing on the planning," Haarnoja said. "So they approach from the top: high-level intelligence, pushing that down towards the physical. Whereas we think about it from the bottom up."

What has to happen next?

Commercial proof remains outstanding. Eka is running secretive pilots with industrial customers in pick-and-place and wire manipulation, and the founders themselves concede the leap from lab to production line is large.

"What's going to be a big challenge is when they work with integrators on real assembly lines, and it needs to run without breaking for an entire year," Hauser said. He also flagged generality: "What I've seen is pick and place, but many industry tasks that are value added involve more than pick-and-place."

Hardware durability is the other hurdle. Eka's gripper costs less than $1,000 and is rated for 5 million duty cycles. Agrawal wants to reach the 20 million cycles that standard industrial arms deliver.

"We are starting off being very pragmatic, and saying here are two verticals in pick, arrange, place, and wire handling, let's make them be home runs," Agrawal said. "Once we have made home runs on them, the sky is the limit in how much we can do with the approach we are developing."