Train
train collectors and annotators
EgoArenaSell your data for 10x more
84%
0.91
QA
The Verification Platform for Robot Policies & Datasets
Before robotics models are deployed, Ego Arena runs physical-world evals across hardware, tasks, and environments to prove what works.
84%0.91QACurateSegment hands, objects, and contact regions before a clip enters the dataset.
Diversitymeasured
Frame continuityreal RLE at 30 fps
Curate verdictkeep high-signal window
Our customers have sold datasets made with us into
12datasets evaluating
213,720+clips reviewed
10,427hours reviewed
Sell your data for 10x more
Keep your data from being a commodity by using our data quality & diversity platform.
Test
test workers continuously
Certify
certify top performers
Drift
detect worker vs team drift
Repair
relabel or repair bad labels and broken episodes
Metadata
attach quality, safety, task, embodiment, contact, and dynamics metadata to raw data
Readiness
score world-model readiness across synchronization, action-observation alignment, contact richness, object motion, latency, embodiment, and task success
Curate
curate silver datasets for your budget
Train Models
train VLMs, robotics models, and forward dynamics models to label and score larger bronze datasets
Benchmark
benchmark which data mixes improve downstream robot policy performance
Rollouts
evaluate counterfactual rollouts through simulators, learned world models, or customer internal evaluators
Recommend
recommend whether data should be kept, upweighted, downweighted, relabeled, recollected, or used for world-model calibration
Every clip gets a training-signal score.
We score downstream usefulness
Industry standard measures surface-level cleanliness
We catch bad robot training signal
Generic QA catches bad labels and doesn't say what labels to update
EgoArena routes and improves data
Most companies accept or reject data, then label with basic VLMs
Prove your datasets are worth training on.
Submit raw egocentric data. EgoArena turns noisy clips into ranked, reviewable signal.