Computer Vision FastTrack

What you get

• Custom model trained on your footage (detection/tracking/classification)
• Edge deployment package: ONNX/TensorRT optimized for Jetson/x86/ARM
• Inference pipeline with <target latency (typically 60-200ms p95)
• Precision/recall benchmarks on test set with confusion matrices
• MLOps workflow: drift monitoring, review UI, re-labeling, retraining hooks
• Production runbook: deployment, rollback, troubleshooting, scaling

Outcomes

• Model meets precision/recall target on your footage
• Edge pipeline ≤ target latency; stable FPS
• Ops workflow (review, re-label, retrain) live
• Measurable reduction in manual review time (typically 87%)
• Drift monitoring and automated retraining triggers

Proof points

• Precision/recall scorecard with per-class breakdown
• Latency benchmarks (p50/p95/p99) across hardware configs
• FPS stability chart (30-day post-deployment)
• Drift detection alert examples with remediation
• Manual review time reduction (before/after workflow analysis)
• Model card with architecture, inputs, outputs, limitations
• Production model inference p95 latency ≤ 200ms

Frequently asked questions