Kai Ego Suite: From Human to Humanoid

A full-stack embodied AI data solution,

from rapid training data acquisition to real-world robot deployment

High-quality multimodal embodied training data empowers robots to execute real-world tasks
Our proprietary dataset enables robots to autonomously complete household tasks: folding clothes, folding cartons, and organizing tools.
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Kai Halo

Elaborately optimized placement and microsecond-level synchronization, these four fisheye cameras support panoramic environmental perception for geometric reconstruction and robust, occlusion-free tracking of dexterous hand manipulation.

Complementing the front camera array, four downward-oriented cameras are thoughtfully laid out for comprehensive human pose capture.

Lightweight and low-cost hardware for unbounded large-scale deployment, flexible and natural data collection anywhere.

High-performance processing AI infra enable fine-grained action semantic annotation,3D scene and full body pose recovery, validated across multiple different robot embodiments for real-world task training.

One-shot capture,

comprehensive multi-modal dataset acquisition

Every natural human manipulation synchronously

captures multi-modal dataset spanning vision, motion semantics and 3D scene,

delivering complete perceptual priors to empower efficient embodied robot training.

First-person video
First-person video
Full-body pose capture
Full-body pose capture
Hand pose (fine-grained)
Hand pose (fine-grained)
3D scene reconstruction
3D scene reconstruction
Semantic action annotation
Semantic action annotation
Rich scene coverage
Rich scene coverage
Data Collection Hours
100,000+

150+

Annotated Action Types

2,000+

Annotated Skills

10,000+

Scenarios

Daily collection count:1848

Cumulative total: 68891

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Cumulative total: 70571

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Cumulative total: 72678

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Cumulative total: 75015

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Cumulative total: 77482

Daily collection count:1972

Cumulative total: 79454

Daily collection count:1986

Cumulative total: 81440

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Cumulative total: 83738

Daily collection count:2398

Cumulative total: 86136

Daily collection count:1200

Cumulative total: 87336

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Cumulative total: 91953

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Cumulative total: 95892

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Cumulative total: 106802

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Cumulative total: 126352

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Cumulative total: 127357

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Cumulative total: 190225

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Daily collection count:1174

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Cumulative total: 923956

2026 - 01
2026 - 02
2026 - 03
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2026 - 05
2026 - 06

From raw capture to

delivery-ready datasets

Covers collection task management, data quality assurance, annotation and data augmentation

Collection Management
Step1
Collection Management
Unified management of task progress, operator assignment, and device status, with real-time tracking of data volume and completion rate.
Automated Quality Inspection
Step2
Automated Quality Inspection
Automatically detects issues such as video image quality, abnormal joint poses, and data synchronization errors, and generates quality inspection reports with real-time visibility into pass rates and issue distribution.
Semantic Annotation & Task Segmentation
Step3
Semantic Annotation & Task Segmentation
Conducts frame-by-frame annotation on continuous video for action types, interaction objects, operating hands and other labels, auto-segments videos into separate task clips, and provides Chinese-English bilingual semantic annotations.
Data Augmentation
Step4
Data Augmentation
Applies data augmentation to generate supplementary training samples from existing data, expanding dataset size while enriching visual diversity.
Real-world deployment

Every task below was trained

on our captured data.

The robotic arm with dexterous hands uses a knife to open a delivery box, takes out a bouquet of flowers, and puts it into a vase.
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Trained on egocentric data, the dual-arm robot with dexterous hands can imitate human behaviors to execute long-horizon sequential task.
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The dexterous robotic arm grasps a pair of scissors to slice through adhesive tape, demanding high-precision fine manipulation.
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The dual-arm robot picks up a glass cup with its left arm and a water bottle with its right arm, then pours water from the bottle into the cup. Trained on real-world data, the robot is capable of manipulating fluids.
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Box folding is a long-horizon task with deformable cardboard; our low-cost egocentric data collection greatly reduces the high cost of traditional teleoperation-based training data gathering.
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This dual-arm manipulation demo includes unscrewing and extracting the bit from a power drill, followed by stowing both the drill and its bit inside a toolbox, demanding sophisticated coordinated motion control of two manipulators.
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By virtue of precise dual-arm coordination, the robot pick and place a dish into a paper carton and completes the subsequent carton closing operation.
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The dual-arm robot resumes clothes folding automatically after human interruption. It continues finishing the task once the garment is taken away and placed back manually.
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Kai Ego Suite pairs compact wearable device with an end-to-end pipeline from data capture to real-world robot deployment, enabling embodied intelligence across different embodiments.