We integrated a simulation stack to exercise ML-based computer vision features under challenging conditions:
- Synthetic data generation across lighting, weather, and clutter
- Scenario orchestration and automated assert checks
- Seamless pipelines to feed model training and evaluation
Impact: significant reduction in manual testing (≈10 weeks/year) and prevention of potential RMAs.