Build 'SafetyNet AI'—a real-time, third-party autonomous vehicle safety monitoring and analytics dashboard. The platform would aggregate telemetry data from multiple OEMs via API, use edge AI to detect anomalies (e.g., 'Autopilot disengagement patterns'), provide 'Safety Scores' for regulators (e.g., 'Tesla Model 3: 92% compliance with NHTSA standards'), and offer 'Incident Alerts' for insurers and law enforcement (e.g., 'Tesla Model X in Houston deviated from lane 3 times in 10 minutes').

The current system of autonomous vehicle safety relies heavily on post-incident data analysis and manufacturer self-reporting, leading to delayed responses, public distrust, and regulatory scrutiny. The financial cost of litigation and reputational damage for manufacturers is growing, while consumers face safety risks.