With current, network-wide condition data in hand, Danvers shifted from reactive decisions to a proactive paving and preservation program residents can see and feel.
Danvers, MA faced growing pavement deterioration across commuter routes and neighborhood streets, while residents expected quick, visible results. Without current, consistent street data, the city struggled to know which roads to fix and when, defend paving budgets, and build a work plan that could stand up in public meetings. Manual windshield surveys were slow and inconsistent, forcing staff to react to complaints and answer constant “Why not my road?” questions instead of executing a strategic, town-wide program.
Danvers chose Cyvl to rapidly survey the entire network with vehicle-mounted LiDAR and sensors, capturing high-resolution surface and geometry data across 109 roadway miles. Cyvl’s Infrastructure Intelligence platform used AI to convert those scans into detailed pavement condition scores, segment-level maps, prioritized repair lists, and budget-ready reports. Delivered in weeks—by June 21, 2022—the city gained a defensible plan and the ability to act faster with confidence, not guesswork.
With current, network-wide condition data in hand, Danvers shifted from reactive decisions to a proactive paving and preservation program residents can see and feel. The team translated results into clear project lists, timelines, and budget scenarios that direct dollars to the most impactful work, shortening the time between assessment and construction. Fast delivery meant less waiting and more resurfacing, sealing, and patching before problems spread, improving safety and ride quality sooner.