All Case Studies
ManufacturingIndustrial Robotics2025
Aurora Vision Platform
Built a real-time defect detection system processing 4K video at 60fps across 12 production lines, replacing manual QA with sub-second automated triage.
Client
Industrial Robotics
Sector
Manufacturing
Duration
22 weeks
Team
4 engineers · 2 researchers
The Challenge
The starting point.
The client's existing QA process required two operators per line and missed an estimated 18% of defects. Latency budget for any automated solution was 200ms end-to-end.
The Approach
What we built.
- 01Collected and labeled 240k defect images across 9 categories
- 02Distilled a YOLOv9 detector into a 14M-parameter student model
- 03Deployed via NVIDIA Triton on-prem with hardware-accelerated preprocessing
- 04Built a feedback loop letting line operators flag false positives in one tap
Results
What shipped, what changed.
99.4%
Defect recall
47ms
End-to-end latency
12
Production lines live
$2.8M
Yearly scrap reduction
Stack
What's running in production.
PyTorchYOLOv9TritonTensorRTKafkaGrafana
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