Lytx has launched Dynamic Risk, a suite of tools designed to help fleets identify and respond to on-road environmental risks in real time.

The company says Dynamic Risk transforms traditional fleet safety systems from reactive to proactive tools, helping drivers anticipate and prevent incidents caused by shifting weather and road conditions. By harnessing data from Lytx’s extensive network of cloud-connected cameras, Dynamic Risk leverages data science, historical context, and live environmental inputs to provide fleets with a comprehensive, forward-looking view of safety and operational challenges.

By integrating real-time data from machine vision and AI-powered road imagery, advanced environmental sensors, and National Oceanic and Atmospheric Administration weather insights (more regions to come), the tool enables fleets to receive clear, timely alerts for hazards before they develop.

“Today’s fleets face a complex landscape of unpredictable hazards, from sudden weather events and construction zones to increased pedestrian and cyclist activity,” said Chris Cabrera, CEO at Lytx. “Dynamic Risk is not just about detecting risk after the fact. It empowers drivers and managers with the intelligence to anticipate and proactively prevent incidents before they happen, helping protect their drivers, avoid costly incidents, and operate more efficiently in a rapidly changing world.”

The suite’s current capabilities include automated tagging of events with poor weather conditions such as low visibility, snow, and wet roads. Currently in beta, the Dynamic Risk Index is a weighted scoring model that will be incorporated into existing coaching workflows and adjusted based on the environmental factors happening in the moment. In-cab Weather Alerts is also in beta and will be released soon to further help fleets and drivers manage weather-driven risk.

Future updates planned for 2026 include enhancements to pedestrian detection and roadwork detection. Lytx says these tools are being tested by customers through its Lytx Lab program.