Eka Robotics Raises $150M Series A to Scale Vision-Force-Action Model

Eka Robotics said this week that it has raised $150 million in Series A funding. The Cambridge, Mass.-based startup said the new capital will help it scale its technology and customer deployments. Founded in 2024, Eka is developing a vision-force-action (VFA) model that aims to give robots an intuition for physics through reinforcement learning at scale.

Eka says its model can generalize across objects, tasks, and environments. According to the company, robots using its AI can pick a wide variety of objects outside the training distribution at roughly 1,500 operations per hour. Eka also asserted that the same robots can screw in a light bulb and insert wires, examples meant to show progress in dexterous manipulation.

Eka Robotics said it is targeting dexterous manipulation because complicated work requires both versatility and reliable performance. The company argues that robots need to handle changing conditions and deliver useful work every day. It also contends that robots should master physics rather than mimic human data if they are to become truly general-purpose.

In Eka’s view, a robot can build an “intuition” for tasks the way a human does by jointly reasoning about vision and forces. The company uses simulation learning and said its VFA model is demonstrating that the typical sim-to-real barrier is falling. In simulation, Eka can generate thousands of hours of robot experience in minutes while 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,” the company said. The startup’s thesis is that simulation and reinforcement learning can produce both throughput and breadth without relying on large human demonstration datasets.

Andreessen Horowitz (a16z) and F-Prime led the Series A. F-Prime is a venture capital fund affiliated with FMR LLC, the parent company of Fidelity Investments. Raghu Raghuram, a general partner at a16z, said Eka’s VFA model is the first approach he has seen that truly solves manipulation with the generality and throughput needed for deployments.

Raghuram added that the team has the ideal DNA to push the frontier of robotics research while scaling commercial operations. Eka Robotics’ Series A also included continued support from seed-round lead investors Obvious Ventures and E14 Fund. Other participants included MFV Partners, Bison Ventures, Glasswing Ventures, Samsung Next, and several Fortune 500 strategics.

Shyam Kamadolli, a managing director at Fine Structure Ventures, said a robot’s value on the factory floor comes down to two things: its success rate and its speed over thousands of repetitions. He said he recognized early on that current approaches to generalization would not get the industry there. In his view, the next level of performance requires a deep understanding of physics and breaking free from dependence on human demonstrations.

Kamadolli added that Eka’s VFA model, trained through simulation and reinforcement learning, achieves this for dexterous manipulation in a way no other company has. He said he believes Eka’s approach is the only one that will hold up in real-world deployments of complex tasks. The funding will test whether that confidence translates into repeatable customer deployments.

The round reflects broader investor interest in embodied AI and robot foundation models. Eka is among a group of startups betting that physics simulation and reinforcement learning can overcome the data bottleneck that has constrained robotic manipulation. The company said its approach can generalize across objects, tasks, and environments while maintaining high throughput.