Quirk Labs

The training data layer for physical AI.

We capture real human behavior at scale — in factories, farms, and homes — so robots can learn from it.

The Problem

Robots can't learn what they've never seen.

Robotics and physical AI teams need massive, diverse datasets of real human motion and interaction. Today, that data barely exists.

Synthetic data can never fully replicate the noise, variability, and edge cases of the real world.

Motion captured in controlled settings fails to transfer to unstructured, diverse environments.

Compute scales. Data doesn't. Physical AI teams are starved for diverse, real-world human motion data.

How It Works

Camera-equipped headsets and sensor gloves are deployed into real environments — factories, farms, and households across Asia.

Workers and individuals wear the devices during normal routines, capturing high-fidelity egocentric video and human motion data.

Raw data is processed, labeled, and packaged into structured datasets ready for training robotics and foundation models.

Where We Operate

Our capture network spans diverse real-world settings — collecting data where human tasks actually happen.

Assembly lines, packaging stations, and industrial workflows.

Agricultural tasks, harvest handling, and crop maintenance.

Cooking, cleaning, organizing, and daily domestic routines.

Who We Serve

Training manipulation, locomotion, and interaction policies with real human data.

Building human-like movement and dexterity into next-generation humanoid platforms.

Pre-training large-scale models on physical world data for embodied reasoning.

Advancing the science of imitation learning, embodied AI, and human-robot interaction.