Separating the noise from the signal at industrial scale
We prepare pristine, production-ready datasets and experiment workspaces for AI-based machine vision —so you cut iteration time, raise accuracy, and deploy with confidence.
Remove irrelevant or poor-quality images, balance classes, and eliminate noise and confounders.
Structured training plans with corresponding, versioned datasets delivered as workspaces.
Surface decisive features and provide clear dataset health metrics for model readiness.
We align on inspection goals, classes, edge cases, and production variability.
Curate, clean, and structure data; generate experiment lists and workspace folders.
Provide validated datasets, reports, and a repeatable process for future lines or SKUs.
A global manufacturing client required a high-precision vision system to detect microscopic defects in a critical product. Initial AI detection was ~60% with false positives >5%, far too high for export quality standards.
DataGin AI prepared an optimized dataset and designed targeted experiment workspaces, enabling the integrator to rapidly refine and validate the model.
Result: 99.98% detection accuracy with only 0.02% false positives—unlocking global rollout, preserving multi-million-dollar sales, and eliminating customer quality complaints.
Predictable, project-based pricing sized for integrators.
Cut model iteration time, reduce false rejects, and deploy with confidence.