Detect what your rule-based vision can't.

Objection 01

“Our line runs at 320 parts per minute - your model needs to make a decision in under 40 ms. Can it actually do that on an edge box?”

Yes, and we will prove it on your line. The TensorRT-distilled model dispatches in under 22 ms on Jetson AGX Orin 64GB at 4K input, leaving margin to write the reject event to the PLC inside the line's takt. Higher throughputs (>400 ppm) move to NVIDIA IGX Orin or a multi-Jetson load-balancer. We publish the latency budget by layer and we measure it on your hardware during commissioning.

Proof: anonymised UAE packaging-plant reference - 12 defect classes, 99.1% detection rate on the historical reject library, <22 ms inference latency at 320 ppm sustained.

Objection 02

“Every time we add a new SKU, the Cognex integrator wants three days and a change order. How does your system retrain, and who pays for it?”

New SKU and new defect classes are added through the Inspector Loop annotation tool, operated by your quality engineer - not an integrator visit. A new version is trained on the operator-labelled samples, canary-validated on a shadow camera, and promoted when the validation set is beaten. Retraining is part of the run-phase SLA; no change order needed unless the line geometry physically changes.

Proof: anonymised KSA pharma blister-pack reference - contamination detection lifted from 91.2% to 99.7%, with three new pack variants added by the in-house quality team in the first six months. No integrator visit required.

Objection 03

“We have already paid for Cognex and Keyence sensors. You can't expect us to rip them out. How do you co-exist with the rig we own?”

We do not rip anything out. The appliance we install for you reads the existing Cognex or Keyence pass/fail signal, adds a learned layer on top, and writes its own reject event downstream. The two systems run in parallel during commissioning; you see the per-defect-class delta on the same dashboard before flipping the rejector authority. If the Brocode layer underperforms, the rejector authority stays with the rule-based rig.

Proof: anonymised regional retail reference - shrink reduction from 1.6% to 0.74% across 84 stores in 11 months, running alongside the existing Tyco Sensormatic EAS without modification.