Real Data, Not Synthetic
Synthetic data can't replicate the noise, variation, and edge cases of real human work. We capture it at the source - from an actual worker doing an actual task.
We turn real human work into robot-ready datasets
Robotics and foundation-model teams don't fail on algorithms - they fail on data. We built an end-to-end pipeline that captures real-world tasks from a wearable camera and auto generates structured, labeled, human-verified datasets in every major training format.
94%Hand detection accuracy
92%Action detection accuracy
88%Object detection accuracy
7Training formats supported
Overview
Robotics and foundation-model teams are bottlenecked by data: real-world demonstrations are expensive to capture and even harder to label consistently. This platform closes that gap with an end-to-end pipeline. A worker wears a camera and performs a task; computer vision automatically understands every moment - extracting actions, objects, and context frame by frame - and turns it into reviewable, version-controlled datasets. What synthetic data cannot replicate, we capture from real human activity.
Why teams choose our vision intelligence platform
Every Label, Human-Verified
Computer vision does the first pass. A structured human review queue approves, corrects, or rejects every annotation before it ships - so nothing reaches your training set unchecked.
Export-Ready, Not Just Labeled
Datasets are versioned, quality-scored, and exportable in the format your training pipeline already expects - LeRobot, RLDS, Open X-Embodiment, DROID, and more.
Built for Scale, Pilot to Production
Start with a single wearable capture session. Scale to fleets of workers, thousands of episodes, and continuous dataset growth - without changing your pipeline.
Platform capabilities
Wearable Capture
Record any task with smart glasses, helmet cams, or mobile devices, with reliable offline sync built in.
AI-Powered Processing
The model automatically understands every moment of footage - extracting actions, objects, and context without manual tagging.
Smart Annotations
Every chunk of footage is labeled with objects, actions, transcript, and a confidence score - generated automatically, not typed by hand.
Episode Builder
Individual annotated chunks are merged into complete task workflows, complete with steps, tools used, and a knowledge graph.
Human Review Queue
A built-in quality assurance layer where reviewers approve, reject, or modify AI-generated labels before a dataset is finalized.
Dataset Export
One-click export to LeRobot, RLDS, Parquet, or JSONL - version-controlled, with a quality score attached to every dataset.
Inside the platform
01 - Live Record
Live Record
Wearable capture with a live camera preview and voice-driven task intent, so context is captured in real time - not reconstructed later.
REC 00:04:121080p · 30fps
◉ intent "picking up the bottle and sliding it to the left tray"
Episode #0142 · assembling4 steps
01Approach workstation0:00–0:06
02Grasp bottle0:06–0:11
03Slide to tray0:11–0:17
04Release & retract0:17–0:22
02 - Episodes
Episodes
Captured footage chunks assembled automatically into complete, step-by-step task workflows - steps, tools, and timing intact.
03 - Review Queue
Review Queue
The human-in-the-loop layer for QA - approve, reject, or correct AI labels before they ship into a dataset.
Review queue12 pending
action: slide_objectconf 0.92
ApproveEditReject
object: bottleconf 0.88
object: gripperconf 0.71
Datasets
VersionEpisodesQualityFormat
v1.31,204ALeRobot
v1.2980ARLDS
v1.1612B+DROID
04 - Datasets
Datasets
Versioned, quality-scored datasets, ready to export to any supported training format - with full lineage on every release.
05 - Knowledge Graph
Knowledge Graph
Actions and objects mapped across every episode, with occurrence counts and average confidence scores.
Knowledge graph · 6 nodes
grasphand · 214bottle · 188slide · 142tray · 96release · 88
⚲ action:slide AND conf>0.9
3,410
episodes
128h
footage
0.91
avg conf
06 - Search & Analytics
Search & Analytics
Search episodes by action or annotation, and track episode counts, duration, annotation volume, and confidence trends over time.
Where it's used
Foundation Model Training
High-quality, multimodal datasets for training next-generation AI models on real-world human activity.
Robotics & Manipulation
Real-world demonstrations exported in LeRobot format, ready for robot learning and manipulation research.
Agent Training
Step-by-step task workflows that teach autonomous agents how real tasks actually unfold, not just how they're described.
Enterprise SOPs
Auto-generate standard operating procedures directly from expert demonstrations - no manual documentation required.
Exports to every major training format
- LeRobot
- RLDS
- Open X-Embodiment
- DROID
- AgiBot World
- Parquet
- JSONL
Have a vision-intelligence problem in mind?
Tell us what you want to build - we'll tell you how fast we can ship it and what it'll cost.