Cogniscient develops fine-tuning methods for vision models trained on a few hundred labelled images — the regime most real-world defect classification actually lives in.
Every new customer, product line or inspection standard is a fresh model trained on whatever was labelled by hand. Usually a few hundred images.
On public industrial defect benchmarks, 2–13 percentage points of accuracy over standard fine-tuning of the same backbone. Largest gains at 300–500 labelled images per class.
Free benchmark pilots under NDA for vendors already running defect classification in production. Your data, your splits, side-by-side against your current pipeline.