Vision-Language-Action Robotics

Robots that read the scene. Then act.

EmbodyX deploys VLA model inference on industrial robot arms so they handle unscripted tasks without reprogramming. Manufacturing and logistics, out of the box.

Capture Scene perception 3D point cloud + RGB VLA Model Language instruction Action token output Act Joint trajectory Task complete
97% first-attempt grasp success on unscripted parts, based on internal benchmarks across 3 pilot facilities
<4hrs time-to-task deployment per new robot arm, measured across early-access integrations
3x throughput versus scripted baseline, across 6-week pilot evaluations

How VLA inference works

Three steps from raw scene to executed motion, all on your local network.

Perceive

Cameras and depth sensors capture the scene in real time. EmbodyX builds a spatial scene graph from every object in the workspace.

Reason

The VLA model processes the scene graph against your natural-language task instruction and outputs a grounded action plan for the robot arm.

Act

Joint trajectories are sent directly to your robot arm controller. EmbodyX supports UR, KUKA, and Fanuc out of the box with no custom code.

Where it deploys

EmbodyX targets the two highest-value unscripted manipulation environments in industry.

Industrial robot arm above a factory assembly line with varied parts on a conveyor belt
Manufacturing

Assembly line bin-picking and placement

Factory lines with varied part geometries and mixed SKUs stop production when robots encounter an unrecognized configuration. EmbodyX reads the scene and continues without intervention.

Avg. 3x throughput vs. scripted workflows
Warehouse robot arm sorting mixed packages on a conveyor system
Logistics

Mixed-SKU warehouse sortation

Fulfillment centers with high mix inbound flows can't pre-program every box shape. EmbodyX enables arms to identify, grasp, and route any package without a library of object models.

Sub-4-hour deployment per arm

We ran a 30-day pilot on two UR10e lines. Scrap from part-handling errors dropped noticeably and we hit 97% first-attempt success on a mix we had never seen before. The integration team had us running in three hours, not three weeks.

Automation Lead, Tier-1 automotive supplier, early-access pilot program
62% reduction in unplanned stops during 30-day pilot
97% first-attempt success rate on novel part geometry
3hrs from SDK install to first autonomous pick-and-place

Built by robotics engineers

The EmbodyX founding team brings together backgrounds in perception systems, deep learning, and industrial automation integration.

Chen Wei, CEO and Co-Founder of EmbodyX
Chen Wei CEO & Co-Founder

Built perception systems for industrial automation, tracking how the gap between scripted robot capabilities and real factory conditions compounds across every product cycle. Co-founded EmbodyX to close that gap.

Priya Mehta, CTO and Co-Founder of EmbodyX
Priya Mehta CTO & Co-Founder

Background building ML inference systems for high-throughput logistics, working on the parts of the stack that have to keep up with conveyor speed and arm cycle time. At EmbodyX, focused on getting VLA inference under the latency ceiling that production arms require.

Lars Eriksson, Head of Robotics Integration at EmbodyX
Lars Eriksson Head of Robotics Integration

Career in robotics integration: commissioning FANUC, KUKA, and UR arms across automotive and industrial manufacturing facilities. Knows the failure patterns of scripted automation at first hand, and what each hour of line stop costs.

Put a VLA model on your production line

Start with a 30-day free evaluation on one arm in your facility. No integration contract required.