Physical AI Data Platform
The Data Infrastructure for
Physical AI
Turn factory video into training data and real-time validation for humanoid robots.
Your factory floor is full of training data
Every shift, your operators perform the exact manipulation tasks robots need to learn. That know-how is already on camera. It's just locked inside hours of raw video that no robot can use as-is. A single hour holds thousands of separate actions, across different workers, cameras, and lighting, and labeling all of that by hand is slow and expensive.
Khenda's pipeline does it automatically. We take in raw footage, pull out the structured actions, and hand back ML-ready datasets, turning months of manual labeling into days.
From your video to a robot policy in four steps
Upload
Record your operations with any standard camera. No depth sensors, motion capture suits, or specialized equipment needed.
Analyze
Our Vision-Language Models identify every discrete action: grasps, placements, tool uses, inspections. Each action is timestamped and classified.
Structure
Raw observations are converted into structured datasets: 3D joint trajectories, object 6DoF poses, force estimations, and natural language task descriptions. All formatted for VLA model training.
Deploy & Validate
Train your humanoid with real-world data, deploy it on the floor, and use Khenda's monitoring to validate performance and capture new edge cases for continuous improvement.
Built for the physical world
Action Recognition & Temporal Segmentation
Identify, classify, and precisely timestamp every discrete physical action in video: assembly, grasping, inspection, placement.
3D Kinematics & Pose Estimation
Extract spatial motion data including joint angles, trajectories, and velocity profiles from standard 2D video without depth sensors.
VLA-Ready Dataset Generation
Output structured datasets formatted for Vision-Language-Action models, sim-to-real transfer, and robot policy training.
Automated Video Curation
Automatically filter, segment, and quality-score raw footage at scale. Remove unusable clips and surface high-signal demonstrations without human review.
The missing data layer for robotics
Proven in Production
Commercially deployed with large manufacturing customers today, not a research prototype. Our video analysis platform already runs inside real factories.
Patented Core Technology
Granted U.S. patent (No. 12,450,905 B2) on periodic task analysis, the foundation of our automated step segmentation engine.
Real, Not Simulated
Data from actual factories with real humans, real objects, and real-world complexity. Not synthetic environments.
Scale
Our pipeline is built to process millions of hours of video. The more footage you bring, the richer your training dataset becomes.
No Specialized Hardware
Works with existing cameras and standard video. No depth sensors, suits, or specialized equipment.
Domain Expertise
Years of station-level analysis across repetitive manufacturing operations, from automotive to electronics and heavy industry.
Resources
The latest in humanoid robotics
Which station should the robot do first?
The Humanoid Deployment Feasibility Score (HDFS) ranks every process from 0 to 100 for humanoid automation, built from the operator videos you already collect. Choose the right station with data, not guesswork.
Explore HDFSFrequently asked questions
What is Khenda?
Khenda turns real-world factory video into structured training data for humanoid robots. We also provide real-time performance validation when those robots are deployed on the factory floor.
How is Khenda different from simulated data?
Simulated environments can't capture the unpredictability of real factories: varying lighting, cluttered workspaces, irregular objects, and the subtle physics of human manipulation. Khenda extracts training data directly from real workers performing real tasks. No simulation, no domain gap.
How does Khenda generate robotics training data?
You upload factory video. Our AI pipeline identifies human actions, extracts 3D kinematics and temporal sequences, and outputs structured datasets compatible with Vision-Language-Action (VLA) models.
What industries does Khenda's data cover?
Automotive assembly, electronics manufacturing, logistics, home appliances, heavy industry, and other sectors where humans perform complex physical manipulation tasks.
Does Khenda require special hardware?
No. Khenda works with standard video from existing cameras. No depth sensors, motion capture suits, or specialized equipment required.
What makes Khenda's data unique?
Our data comes from real production environments with real humans and real objects, not simulated or lab settings. This diversity and authenticity is critical for training robust humanoid systems.
What happens after the humanoid is deployed?
Khenda monitors your humanoid's actions in real time, comparing its performance against human demonstration baselines. When deviations are detected, the system provides structured feedback that feeds back into the training pipeline for continuous improvement.
Build the future of Physical AI with us
Whether you're building humanoid robots, preparing your factory for automation, or pushing the boundaries of robot learning, Khenda provides the data foundation.
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