This is where we started. We label the field imagery that teaches autonomous weeders, harvesters and crop-monitoring systems to tell a crop from a weed, a healthy plant from a diseased one, and exactly where to act — down to the millimetre.
Our work is informed by our parent company H2L Robotics BV and partner Cropr, who operate autonomous laser weeders on real Dutch farms. We annotate imagery from the same conditions the machines face — variable light, overlapping canopies, and disease.
Stem-base keypoints and tight boxes give a laser weeder the exact coordinates to fire, sparing the crop and killing the weed. Precision here isn't cosmetic — a misplaced point costs a plant.
We label plants from emergence to harvest, including disease-affected specimens, so detection models stay reliable across the whole season.
Agriculture remains our deepest domain, and the QA process we built here — multi-pass review, per-annotator quality tracking — now underpins our work in every other sector.
