Eka says its model can generalize across objects, tasks, and environments. | Source: Eka Robotics

Eka Robotics this week said it has raised $150 million in Series A funding. The startup said the new funding will help it scale its technology and customer deployments.

Founded in 2024, Eka is building a vision-force-action (VFA) model to develop an intuition of physics through reinforcement learning at scale. The Cambridge, Mass.-based company said that robots using its AI can pick a wide variety of objects outside the training distribution at a speed of roughly 1,500 operations per hour.

The same robots can screw in a light bulb and insert wires, Eka asserted.

Eka Robotics said it is targeting dexterous manipulation. The company said that for robots to handle complicated work, they need the versatility to handle changing conditions and the performance to deliver useful work every day.

Eka also said it believes that robots should master physics, not mimic human data, to be truly general-purpose. This would allow the robot to build “intuition” for tasks the same way a human can by jointly reasoning about vision and forces.

The company uses simulation learning, and it said its VFA model is demonstrating that the typical sim-to-real barrier is falling. In simulation, the company can generate thousands of hours of robot experience in minutes, varying objects, environments, and physical conditions.

Eka claimed that transferring this learning to the real world unlocks a scalable, performant, and capital-efficient path to a foundation model for manipulation. “Reinforcement learning at scale buys performance, and breadth of experience buys generality,” it said.

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