io-ai®
Expert-managed data for AI

Expert data for serious AI.

Annotation, generative-AI evaluation, and real-world data collection for vision, sensor and frontier models, delivered by a vetted team at over 98% accuracy.

Abstract sculptural render in io-ai brand orange vision · sensor · frontier
Trusted on hard problems
Uber Airbus Anthropic NVIDIA Trace Labs Abyss Solutions

Official global vendor for Uber AI Solutions.

0
data experts in-house
0
projects delivered
0
tasks completed
>0
accuracy on rolling audits
Off-the-shelf datasets

Licensable data, ready to train on.

Expert-collected, human-verified datasets you can license today — across text, multimodal, video, audio, image, code, medical and egocentric.

2.6B+
words of text
132k+
hrs video
2.1M+
hrs audio
100k+
hrs egocentric
Egocentric & physical-AI data

The first-person data behind embodied AI.

Robots, wearables and AR models learn from the world as it's actually seen and done. io-ai collects and annotates egocentric (first-person), teleoperation and embodied-AI data: head- and wrist-mounted video, manipulation, and real-world tasks, a capability most data vendors don't offer.

Synchronized head- and wrist-mounted video of real tasks: the exact first-person view a robot or wearable model learns from.

First-person (egocentric) capture
REC EGO-CAM 01 · 60 FPS

Trusted across the industries where data is hardest.

Safety-critical, sensor-heavy and frontier-AI workloads: domains that demand trained experts, not anonymous crowds.

Why io-ai

Expert-managed, not anonymous crowd.

Every task runs through a multi-level pipeline with PII masked on every item and a rejection reason recorded on every task. That's how we hold >98% accuracy on work as exacting as runway labeling and subsea defect detection.

Independent & lab-neutralNot owned by a model lab or hyperscaler.
PII-safe by defaultMasking and NDAs on every engagement.
Weekly reportingThroughput, QC scores and rejection reasons every cycle.
Flexible engagementProject-based or a dedicated managed team.
The QA pipeline >98% accuracy threshold
Annotator
labels to SOP
Peer check
cross-review
Auditor
rolling audits
Lead review
sign-off
Client delivery
audit-traceable
First-batchaudits before scale-up
Every taskrejection-reason metadata
Weeklystatus reporting
Let's talk

Tell us what you're building.

Send us your data challenge and we'll scope a pilot, usually within a couple of working days.