Delivered on October 7, 2022, the results arrived in weeks instead of months, shrinking the time between inspection and construction so residents saw improvements faster.
Tewksbury’s pavement program was slowed by outdated and inconsistent condition data, making it hard to know which roads to fix and when. Staff were stuck playing defense to resident complaints without a clear, defensible prioritization method to explain at council and community meetings. Budget planning was difficult to justify because estimates relied on guesswork instead of a current, measurable view of network needs.
Tewksbury selected Cyvl to modernize its roadway assessment using vehicle-mounted LiDAR and sensors to rapidly survey the city’s streets. Cyvl’s Infrastructure Intelligence platform used AI to convert the field data into detailed, actionable pavement condition scores, prioritized repair lists, and ready-to-share reports for leadership and residents. In total, 143 roadway miles were scanned and analyzed, unlocking a defensible multi-year plan with project-level quantities the city could act on immediately.
Delivered on October 7, 2022, the results arrived in weeks instead of months, shrinking the time between inspection and construction so residents saw improvements faster. With citywide condition scores and quantities, Tewksbury produced clear, transparent paving programs that aligned engineering needs with taxpayer value. The new data made it easier to communicate choices, secure funding, and schedule work so crews could fix the right roads at the right time.