SKY ENGINE AI generates synthetic training data for computer vision. The constraint it addresses is that vision models need large volumes of accurately labelled images, and collecting plus annotating those is the dominant cost of any vision project, often exceeding the modelling work by a wide margin.
Synthetic data changes that arithmetic in two ways. Labels are exact by construction, because the generator knows precisely what it rendered, eliminating annotation error. And rare cases can be produced deliberately rather than waited for, which matters enormously for safety-critical detection where the important events are by definition uncommon.
The known limitation is the domain gap: models trained purely on synthetic images can underperform on real ones, so the usual practice is synthetic data alongside real samples rather than instead of them. Evaluation should test that transfer on your own real-world footage.
