The Intelligent Co-Pilot.
iPylot's human-centric AI moves beyond traditional monitoring to redefine the driving experience, ensuring safer journeys and smarter vehicle interaction.
Addressing Critical Human Factors in Driving
Inattention and fatigue at the wheel are not just safety risks; they are significant, costly challenges in the modern mobility ecosystem.
1.6 Million+
Crashes annually in the US from inattentive driving.
390,000+
Injuries attributed to inattention-related incidents each year.
$100 Billion+
Annual economic impact of fatigue-related driving incidents in the US.
A Proven Deep Learning Architecture for Real-World AI
iPylot is a vision-based in-car driver assistance system, designed to enhance driving effectiveness with real-time feedback. Our advanced deep learning architecture combines robust visual analysis with adaptive learning, delivering reliable performance even in unpredictable real-world conditions.
Optimized for On-Board Compute & Cloud Integration
Our intelligent vision processing engine runs on a dedicated edge-optimized GPU and CPU, seamlessly integrating custom-built ML models, sensors, cameras, and connectivity—engineered together into a compact device that mounts effortlessly on the car dashboard. This enables real-time incident prevention and driver personalization, delivering immediate and adaptive support behind the wheel.
Additionally, de-identified data is securely streamed to the cloud, unlocking monetization opportunities through innovative applications such as behavior-based insurance benefits, precision audience engagement, and advanced research initiatives. The system is extensively trained on diverse visual datasets, enabling high-accuracy classification of driver states. It continuously analyzes incoming visual data to detect signs of distraction or fatigue and is architected to support advanced temporal modeling for deeper insights into driver behavior over time.
The Co-Pilot in Action
Our prototype demonstrates the core capabilities of the iPylot platform, turning raw in-cabin video feed and supplementary sensor data into actionable, life-saving insights and proactive assistance.
Drowsiness Detection
Identifies early signs of driver fatigue through continuous temporal video analysis and classification of behavioral patterns to prevent incidents before they happen.
Inattention Monitoring
Detects unsafe behaviors such as phone use, operating secondary controls, or looking away from the road, providing real-time alerts.
Real-Time Feedback
A non-intrusive feedback loop that helps drivers correct behavior and maintain focus on the road, fostering safer habits.
Beyond Safety: The Future of the In-Car Experience
Today's safety features are the foundation for tomorrow's fully integrated, personalized mobility platform. Our roadmap extends to a suite of high-value services.
Personalization
Adapts to individual driving habits and preferences, from climate to infotainment and routing.
Emotion AI
Understands driver and passenger sentiment for enhanced comfort, mood-adaptive features, and experience optimization.
Advanced Assistance
Enables optimal routes, rest stops, and in-cabin adjustments based on real-time driver state and external conditions.
The Team to Execute the Vision
Born from world-class research at UC Berkeley, our team combines deep technical expertise in AI and robotics with a proven ability to innovate.
Let's Build the Future of Driving. Together.
iPylot is currently engaging partners who share our vision for the future of in-cabin AI and enhanced mobility experiences. A secure data room is available for qualified investors upon request.
Contact for a Private Briefing