Within weeks, Apple Valley moved from guesswork to a data-driven pavement program that residents could see and feel on their streets.
Apple Valley’s freeze–thaw cycles and steady suburban growth were accelerating pavement wear on neighborhood streets and key arterials. Without current, consistent data, the team didn’t know which roads to fix or when and struggled to present accurate, defensible paving budgets, pulling them into reactive decisions. At town meetings, staff were constantly asked “Why not my road?” and lacked a clear, unbiased prioritization method to justify choices across the entire network.
Apple Valley chose Cyvl to rapidly survey the full network using vehicle-mounted LiDAR and sensors, capturing precise measurements across 80 roadway miles. Cyvl’s Infrastructure Intelligence platform used AI to transform raw measurements into segment-level condition scores, prioritized repair and preservation lists, and communication-ready maps and reports the city could stand behind. Delivered by July 10, 2024, the city received defensible plans and budget scenarios they could act on immediately to accelerate work for residents.
Within weeks, Apple Valley moved from guesswork to a data-driven pavement program that residents could see and feel on their streets. The city re-sequenced summer work to address the most critical segments sooner, tightened cost estimates, and scheduled crews with confidence. With clear evidence in hand, council discussions ran smoother, resident questions were easier to answer, and fixes reached the street faster.