Computer Vision

1. Own Video Intelligence

• Build and train CV models for driver fatigue & distraction detection, ADAS-style road & event detection, and cargo, theft, and in-cabin monitoring.
• Turn messy, real-world video into reliable detections.

2. Optimize for the Edge

• Make models run cost-effectively at scale using quantization, pruning, distillation, on-device/edge inference, and trigger-based, event-driven processing.
• Treat inference cost-per-camera as a first-class design constraint.

3. Train, Don't Just Wrap

• Build custom models where they create differentiation.
• Use pre-trained backbones and transfer learning to move fast.
• Know when to fine-tune vs. build from scratch.

4. Own the Vision Data Pipeline