The Problem
AI teams were
drowning in
annotation work.
Every AI model needs labeled data. Hundreds of thousands of images, videos, and audio files — each requiring a human to carefully describe what they see, click bounding boxes, type labels, and submit.
The process is slow. It is expensive. And it excludes the vast majority of the world's population who either don't have the technical training or the physical ability to work with annotation tools built for keyboards and mice.
We watched medical researchers in developing countries struggle to annotate X-rays. We saw automotive engineers manually label thousands of frames. We met ML teams paying $2,000 per month for annotation platforms that still required hours of manual work.