With objective, citywide data in hand by July 29, 2025, Yonkers gained end-to-end visibility of street conditions and a clear roadmap for action.
Yonkers faces heavy traffic, steep grades, and freeze–thaw cycles that rapidly wear down pavement and expose gaps in planning data. The city’s teams were working from outdated or inconsistent information and reacting to complaints, making it hard to build defensible paving plans and answer the common question, Why not my road?, in public meetings. Without accurate, current condition data, budget forecasts were tough to defend and crews struggled to prioritize work in a way residents could see and trust.
To change that, Yonkers chose Cyvl to rapidly survey the network with vehicle-mounted LiDAR and sensors, capturing high-resolution pavement data across 338 roadway miles. Cyvl’s Infrastructure Intelligence platform applied AI to transform those scans into detailed, actionable pavement condition scores for 338 miles of roadway, prioritized repair lists, and defensible plans and reports the city could use immediately. Delivered on July 29, 2025—weeks, not months—the results gave leaders a single source of truth to communicate clearly, align budgets, and move projects from data to field execution faster.
With objective, citywide data in hand by July 29, 2025, Yonkers gained end-to-end visibility of street conditions and a clear roadmap for action. Public works and engineering aligned funding and sequenced work for the paving season while sharing transparent maps and reports with the council and community. Residents benefited from faster fixes, safer travel, and clear explanations of what would be done, when, and why.