drivebuddyAI, a leading innovator in AI-driven driver monitoring and safety solutions, is proud to announce that it has been granted a patent for its proprietary driver scoring algorithm, CARD (Cognitive Assessment of Risk for Drivers). This cutting-edge analytical framework leverages AI, computer vision, and real-time vehicle monitoring to assess driver behaviour and risk, setting a new standard of driver scoring, driver risk assessment & incentivization methods for fleet risk management.
Nisarg Pandya, CEO at drivebuddyAI shared his excitement about the announcement, stating, “CARD is a comprehensive risk profiling algorithm that integrates data from Advanced Driver Assistance Systems (ADAS) and Driver Monitoring Systems (DMS) installed in vehicles. The CARD algorithm processes vast amounts of contextual data, including driver alert compliance i.e. how well drivers respond to ADAS & DMS-generated in-cabin alerts, behavioural coaching history, which incorporates previous coaching interventions to measure improvement over time, environmental factors, positive driving behaviours, which recognizes proactive actions such as quick reaction times and compliance with alerts, and risk mitigation actions. This 360-degree assessment enables fleet managers to make data-backed decisions on driver assignments, risk mitigation, and overall fleet efficiency & safety enhancement.”
Expanding upon the concept of ADAS & DMS, Nisarg Pandya added, “drivebuddyAI has developed one of the most accurate AI-powered driver monitoring systems, with over 1 billion kilometres of driving data analyzed and learned from across thousands of drivers. The system boasts a 92% validated accuracy rate in detecting risk-prone behaviours such as - phone use while driving, seatbelt non-compliance, drowsiness and fatigue detection, excessive driving hours related risks, forward collision warnings, tailgating and unsafe lane weaving etc.”
He further added, “Traditional in-vehicle cameras alone cannot improve driver behaviour. drivebuddyAI’s approach combines real-time AI-based alerts, and fleet enforcement with pro-active monitoring and driver coaching. This holistic approach ensures measurable driver improvement within 6 months, significantly reducing accident probabilities and enabling fleet operators to optimize resource allocation. With data-driven risk indexing, fleet managers can identify high-risk drivers requiring intensive coaching, moderate-risk drivers with improvement potential, and safe drivers who maintain compliance and best practices.”
Commenting on the latest innovation Rohan Malhotra, CEO of Roadzen said, “At Roadzen, we understand the critical need for data-driven risk reduction and safer mobility solutions. CARD marks a major leap in AI, equipping insurers, fleets, and logistics providers to prevent accidents, assess risks, and create a safer world. This patent solidifies drivebuddyAI’s leadership in AI road safety, and we’re excited to advance toward safer roads and smarter insurance.”
Sharing her perspective on developing CARD Kanaksvi Pacholi, Data Scientist at drivebuddyAI said, “CARD framework is about creating a fair and reliable way to assess driver safety in real-world conditions. We wanted to design a system to ensure that drivers aren’t unfairly penalized for necessary actions, while still identifying risky patterns over time; a system that adapts dynamically to driving conditions, contextualizes risk, and remains resilient to manipulation. By leveraging precise event clustering and sensor data inputs, we have created a scoring model that not only detects unsafe driving but also encourages better driving habits through meaningful feedback.”
Emphasising the real-world impact of AI-driven driver monitoring, Nisarg Pandya said, “We have seen cases where drivers, during long-haul journeys, start feeling tired and fatigued in the middle of the day, afternoon, or even in the early hours. Once they start receiving alerts, they understand the risk themselves and take necessary actions such as stopping their vehicles to refresh. We have also witnessed instances where a single alert has prevented a crucial accident, saving companies significant financial losses. Moreover, our system has highlighted high-risk drivers, enabling fleets to adjust schedules or routes based on data-driven risk assessments. This is the power of AI—turning insights into proactive safety interventions.”
Elaborating upon the impact of drivebuddyAI’s CARD technology beyond fleet operations, Nisarg further said, “Insurance providers can leverage this data to assess risk for usage-based insurance (UBI), enhance claims processing through AI-driven insights, improve First Notice of Loss (FNOL) accuracy. I do imagine the scoring of driver behaviour as a CIBIL-like structure where each good behaviour is rewarded, and risky behaviour is penalized. This would create a safe driving ecosystem in the country and reduce road fatalities by a large margin. We believe that by constantly nudging drivers using a technology which is accurate enough to win the confidence of the drivers, a behaviour change is possible, and we have observed our logistics customers benefitting by reducing critical events by a very high rate of 85%.”
Nisarg Pandya, CEO at drivebuddyAI shared his excitement about the announcement, stating, “CARD is a comprehensive risk profiling algorithm that integrates data from Advanced Driver Assistance Systems (ADAS) and Driver Monitoring Systems (DMS) installed in vehicles. The CARD algorithm processes vast amounts of contextual data, including driver alert compliance i.e. how well drivers respond to ADAS & DMS-generated in-cabin alerts, behavioural coaching history, which incorporates previous coaching interventions to measure improvement over time, environmental factors, positive driving behaviours, which recognizes proactive actions such as quick reaction times and compliance with alerts, and risk mitigation actions. This 360-degree assessment enables fleet managers to make data-backed decisions on driver assignments, risk mitigation, and overall fleet efficiency & safety enhancement.”
Expanding upon the concept of ADAS & DMS, Nisarg Pandya added, “drivebuddyAI has developed one of the most accurate AI-powered driver monitoring systems, with over 1 billion kilometres of driving data analyzed and learned from across thousands of drivers. The system boasts a 92% validated accuracy rate in detecting risk-prone behaviours such as - phone use while driving, seatbelt non-compliance, drowsiness and fatigue detection, excessive driving hours related risks, forward collision warnings, tailgating and unsafe lane weaving etc.”
He further added, “Traditional in-vehicle cameras alone cannot improve driver behaviour. drivebuddyAI’s approach combines real-time AI-based alerts, and fleet enforcement with pro-active monitoring and driver coaching. This holistic approach ensures measurable driver improvement within 6 months, significantly reducing accident probabilities and enabling fleet operators to optimize resource allocation. With data-driven risk indexing, fleet managers can identify high-risk drivers requiring intensive coaching, moderate-risk drivers with improvement potential, and safe drivers who maintain compliance and best practices.”
Commenting on the latest innovation Rohan Malhotra, CEO of Roadzen said, “At Roadzen, we understand the critical need for data-driven risk reduction and safer mobility solutions. CARD marks a major leap in AI, equipping insurers, fleets, and logistics providers to prevent accidents, assess risks, and create a safer world. This patent solidifies drivebuddyAI’s leadership in AI road safety, and we’re excited to advance toward safer roads and smarter insurance.”
Sharing her perspective on developing CARD Kanaksvi Pacholi, Data Scientist at drivebuddyAI said, “CARD framework is about creating a fair and reliable way to assess driver safety in real-world conditions. We wanted to design a system to ensure that drivers aren’t unfairly penalized for necessary actions, while still identifying risky patterns over time; a system that adapts dynamically to driving conditions, contextualizes risk, and remains resilient to manipulation. By leveraging precise event clustering and sensor data inputs, we have created a scoring model that not only detects unsafe driving but also encourages better driving habits through meaningful feedback.”
Emphasising the real-world impact of AI-driven driver monitoring, Nisarg Pandya said, “We have seen cases where drivers, during long-haul journeys, start feeling tired and fatigued in the middle of the day, afternoon, or even in the early hours. Once they start receiving alerts, they understand the risk themselves and take necessary actions such as stopping their vehicles to refresh. We have also witnessed instances where a single alert has prevented a crucial accident, saving companies significant financial losses. Moreover, our system has highlighted high-risk drivers, enabling fleets to adjust schedules or routes based on data-driven risk assessments. This is the power of AI—turning insights into proactive safety interventions.”
Elaborating upon the impact of drivebuddyAI’s CARD technology beyond fleet operations, Nisarg further said, “Insurance providers can leverage this data to assess risk for usage-based insurance (UBI), enhance claims processing through AI-driven insights, improve First Notice of Loss (FNOL) accuracy. I do imagine the scoring of driver behaviour as a CIBIL-like structure where each good behaviour is rewarded, and risky behaviour is penalized. This would create a safe driving ecosystem in the country and reduce road fatalities by a large margin. We believe that by constantly nudging drivers using a technology which is accurate enough to win the confidence of the drivers, a behaviour change is possible, and we have observed our logistics customers benefitting by reducing critical events by a very high rate of 85%.”
