Contamination-proof

DeepHawk inspects the part as it comes off the machine

At DeepHawk, we believe an inspection system should adapt to your parts, not the other way around.

Glare on machined metal, coolant droplets, shadowed bores, a surface that is never twice the same: DeepHawk learns all of it as part of what a normal part looks like.

Why it works : our frugal architecture, a specific arrangement of small neural networks working in synergy, reads the image contextually instead of pattern-matching. Move a shiny machined part two millimetres and the highlight moves with it.

Rule-based systems read that as a defect. Supervised AI only knows the lighting it was trained on. DeepHawk learns the part as it really comes off the machine, glare and coolant included.

What that means for your plant

No light tunnel, no washing station: you inspect the part where it already is, in the state it is already in. That is a capex line item removed.

No false alarm on a droplet : DeepHawk does not stop your line for a reflection. It finds the scratch underneath it.

Proven on the hardest surfaces: motor aluminium parts, 200 images, 100% detection, 0.0% false alarms.

Where the limit is : this is robustness against contamination and lighting variation, not inspection through occlusion. If a chip physically covers the defect, no camera sees it.