TreadSense recently introduced a mobile tire intelligence platform designed to help commercial trucking fleets modernize one of the industry’s most manual and inconsistent maintenance processes—tire inspections.

Using the LiDAR sensors built into compatible Apple iPhone Pro and iPad Pro devices, TreadSense captures highly accurate tread depth measurements in seconds while creating a digital record of each tire throughout its service life, the company reported. The platform gives maintenance, safety, and operations teams consistent tire condition data that supports proactive maintenance decisions, improves inspection accuracy, and increases fleet visibility.

The technology is designed for use in yard inspections, preventive maintenance, and pre- and post-trip inspections, enabling fleets to identify tire issues before they result in roadside breakdowns, costly emergency replacements, or unnecessary downtime.

Meiborg Companies is among the fleets implementing TreadSense as part of its maintenance and safety operations.

“Our maintenance team has always understood the importance of accurate tire data, but consistency has been one of the biggest challenges,” Zach Meiborg, Meiborg owner and CEO, said in a news release. “TreadSense gives us a faster, standardized way to inspect every tire while providing data we can actually use to make better maintenance decisions.

“It’s helping us improve efficiency, increase accountability, and be more proactive instead of reactive.”

In addition to recording tread depth, TreadSense is expanding its platform with new capabilities, including tire wear pattern recognition, predictive tire replacement forecasting, casing management, and maintenance analytics. By integrating tire intelligence into existing fleet maintenance workflows, the platform is designed to help fleets reduce operating costs while improving safety and compliance.

Built specifically for commercial transportation, TreadSense is designed for truckload, refrigerated, bulk, private, vocational, and dedicated fleets seeking a more data-driven approach to tire management.