AI in Logistics: How Radar is Revolutionizing Fleet Data Analysis
Fleetworthy introduces Radar, a new AI tool designed to transform how fleets manage their tolling, safety, and compliance data. Discover how this innovative solution allows users to query complex information in plain language, turning…
Fleetworthy introduces Radar, a new AI tool designed to transform how fleets manage their tolling, safety, and compliance data. Discover how this innovative solution allows users to query complex information in plain language, turning raw data into actionable insights for improved efficiency and cost savings. Michael Precia, President & CRO, explains the strategic focus on reducing toll leakage and streamlining operations.
Fleetworthy has unveiled Radar, an AI-powered tool that allows fleets to interact with their tolling, safety, and compliance data using plain-language questions. The launch marks the company’s first AI product layered on top of its existing technology stack and targets one of the most persistent cost and operational headaches in trucking: toll leakage and compliance inefficiency.
Tolling was the deliberate starting point for Radar, according to the company’s president and chief revenue officer. Regardless of fleet size, toll spend represents a significant share of operating costs, and the sources of leakage — from violations to transponders migrating between vehicles — are difficult to track without dedicated tooling. Radar is designed to surface those inefficiencies through conversational queries rather than manual data pulls.
Fleetworthy brought together three companies — DriveWise, FleetWorthy Solutions, and BestPass — under one brand, consolidating toll management, weigh station bypass, and safety compliance into a single platform. The company describes the structure as a “three-legged stool,” where compliant drivers earn more weigh station bypasses, which in turn supports safer travel and lowers per-trip costs.
This story was originally published by FreightWaves. Read the full story at FreightWaves →




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