With objective street-level data and a transparent plan in hand, Lexington shifted from reactive maintenance to proactive, resident-focused delivery.
Before adopting modern data practices, Lexington’s pavement decisions relied on scattered spreadsheets and occasional windshield surveys, leaving staff unsure which roads to fix or when. The city often found itself playing defense at town meetings, fielding “Why not my road?” questions without consistent, up-to-date evidence to justify choices. That uncertainty slowed work planning and strained budgets, as staff reacted to complaints instead of executing a clear, data-driven program.
Lexington selected Cyvl to rapidly survey its network using vehicle-mounted LiDAR and calibrated sensors, capturing high-resolution surface condition across 20 roadway miles. Cyvl’s Infrastructure Intelligence platform used AI to transform that raw data into clear condition scores, prioritized repair lists, and defensible, multi-year treatment plans—complete with quantities and cost implications. Results were delivered in weeks, on May, 23, 2022, giving city leaders detailed, actionable pavement condition data for every mile and the ability to move from ideas to implementation before the next paving window.
With objective street-level data and a transparent plan in hand, Lexington shifted from reactive maintenance to proactive, resident-focused delivery. The rapid turnaround—weeks instead of months—compressed the time between assessment and action, so crews could schedule and stage work sooner. Public communication improved as maps, scores, and project rationales replaced guesswork with clarity.