East Coast Hauler Gains Operational Control of Overflowing Bins
Like many haulers, JLT was relying on drivers to manually flag and document overflows using tablets — a method that is time-consuming and lacks both consistency and accuracy. Data showed that haulers using this manual method capture 70–80% fewer overflow events than those using Operational AI.
Beyond lost revenue, manual documentation exposed the operation to distracted driving, increasing safety risks and liability. Bounty programs and driver incentives did not yield better results. Compiling documentation to right-size or bill fees was a cumbersome process, and waste disposal expenses were difficult to forecast due to load variation.
WasteVision's team collaborated with JLT to design a tailored overflow program, including a three-strike customer notification process. The AI system automatically classifies each overflow as marginal or egregious based on JLT's specifications, with an inferencing model that improves over time.
JLT's implementation goals included actionable overflow data, the ability to right-size or bill accurately, standardized processes, and a framework for communicating with customers before fees are levied — while removing distraction from drivers entirely.
Using the manual process, JLT billed on fewer than 1% of lifts. After implementing WasteVision's Operational AI, the system detected that 8–12% of all lifts were overflows, depending on the route. In the 90-day pilot on just 6 trucks, WasteVision recorded 873 overflows. JLT sent 190 letters offering customers the opportunity to right-size, and billed 420 overflows within the first 90 days.
After the success of the pilot, JLT rolled the technology out fleet-wide across all front-end loaders. The system flagged over 25,000 overflows on 28 FELs, generating over $1 million in additional EBITDA. Because expenses for overflowing containers are incurred regardless of billing policies, all revenue generated from overflow billing is a direct bottom-line lift. JLT also instituted a right-sizing program, enabling its salespeople to approach customers with actionable data.
Overflow Detection Breakdown — Fleet-Wide Data (July 2023 – September 2025)
