PrePass released AI Toll Insights, a machine learning capability built into its PrePass INFORM Tolling analytics platform, a comprehensive toll verification and cost optimization solution that helps fleets manage toll spend and validate charges.
PrePass INFORM Tolling combines vehicle GPS data with toll transactions and agency rules to give fleets visibility into toll usage, support dispute resolution workflows, and help optimize toll operations. With the addition of AI Toll Insights, fleets gain a deeper layer of intelligence that interprets toll activity at scale and provides clear signals about issues that traditional reporting and manual reviews can miss.
“Toll costs can be one of the most persistent and unclear expenses for carriers,” says Chris Murray, president of PrePass. “Device mismatches, incorrect transponder assignments, and improper toll usage are difficult to spot without dedicated analytics. AI Toll Insights helps fleets quickly uncover these issues, take action to fix them, and make better decisions that improve toll spend and operating efficiency.”
Key takeaways:
· AI Toll Insights uses proprietary machine learning models designed specifically for toll data, allowing fleets to correlate vehicle movement, toll transactions, device details, and agency pricing rules; detect patterns and anomalies that indicate mismatches or misuse; and turn raw data into recommendations fleets can act on to control costs.
· This specialized intelligence goes beyond generic analytics by providing contextually relevant insight tailored to how toll systems actually operate, an essential advantage as toll networks and agency pricing options continue to expand in scope and complexity.
· AI Toll Insights highlights potential problems closer to when they occur and helps fleets accelerate investigation and resolution.
· Key outcomes include significant time savings identifying and resolving device configuration and assignment issues; reduced manual review and administrative workload for toll invoices and transactions; lower overpayment tied to misconfiguration and improper lane or device use; and fewer recurring disputes and downstream administrative costs.
