Within days of delivery, staff converted the analysis into an implementable paving program that schedules the right treatment at the right time.
Artesia’s public works team was relying on outdated or inconsistent data, making it hard to know which streets to fix first and to estimate costs with confidence. Because the city was reactive to complaints, crews were frequently diverted to short-term patching, causing delays on planned work and frustration for residents. Pressure mounted in council and community meetings as leaders had to justify choices without a consistent, citywide picture of pavement needs.
Artesia chose Cyvl to rapidly survey the network with vehicle-mounted LiDAR and sensors, capturing a precise view of pavement conditions across 41 roadway miles. Cyvl’s Infrastructure Intelligence platform used AI to turn this into detailed pavement condition scores, prioritized repair lists, budget scenarios, and ready-to-share maps and reports—actionable pavement condition data the city could use immediately. Delivered in weeks on December 11, 2024, the city received defensible plans that enabled faster decisions and quicker mobilization of crews and contractors.
Within days of delivery, staff converted the analysis into an implementable paving program that schedules the right treatment at the right time. With objective condition scores and clear GIS maps, the city communicated tradeoffs and timelines so residents knew what to expect and when. The weeks-not-months turnaround reduced the lag between data collection and projects, bringing improvements to neighborhoods faster and ensuring taxpayer dollars went where they delivered the most benefit.