With 66 miles analyzed and reported by June 25, 2025, Ivins gained a complete, block-level pavement condition map and an executable work plan built on trustworthy data.
Ivins, UT was experiencing rapid growth and heavy seasonal traffic on aging pavement, but leaders lacked a citywide view of street conditions to guide investment. Outdated or inconsistent data left the city reactive to complaints and without a clear prioritization method, making it hard to answer residents who asked why their street was not being fixed. Manual assessments were slow and often obsolete by the time they were compiled, making it difficult to defend budgets or schedule work efficiently.
Ivins chose Cyvl to rapidly survey its network using vehicle-mounted LiDAR and sensors, capturing surface distresses across 66 roadway miles with uniform, repeatable precision. Cyvl’s Infrastructure Intelligence platform used AI to convert the scans into standardized condition scores for every block, prioritized repair lists, and scenario-based, defensible paving plans aligned to available budgets. The city received comprehensive, actionable pavement data and ready-to-use reports by June 25, 2025—delivered in weeks instead of months—empowering leaders to communicate clearly and take action faster.
With 66 miles analyzed and reported by June 25, 2025, Ivins gained a complete, block-level pavement condition map and an executable work plan built on trustworthy data. Public works shifted from guesswork to scheduled work, shrinking the time between survey and construction mobilization. Residents now see faster fixes, smoother commutes, and clearer explanations of what will be done and when.