With authoritative, street-level condition data for all 82 miles, Lakeville moved from reactive to proactive, turning weeks of manual analysis into quick, confident action.
Lakeville faced mounting pressure to explain road decisions without up-to-date network data, leaving staff unsure which streets to fix or when and making accurate paving budgets hard to defend. Crews were stuck reacting to complaints and doing worst-first patching instead of executing a strategic, long-term work plan with clear priorities. At town meetings, leaders were asked “Why not my road?” but lacked consistent, defensible information to communicate tradeoffs, fueling more 311 calls and email traffic.
Lakeville chose Cyvl to rapidly survey the entire network; using vehicle-mounted LiDAR and sensors, Cyvl scanned 82 roadway miles and captured high-resolution surface data across the city. Within weeks, Cyvl’s Infrastructure Intelligence platform used AI to convert the raw data into detailed pavement condition scores, block-by-block diagnostics, and prioritized repair lists tied to budget scenarios. Delivered by August 28, 2025, the city received actionable maps, reports, and defensible plans it could use immediately to schedule work, justify funding, and communicate with residents.
With authoritative, street-level condition data for all 82 miles, Lakeville moved from reactive to proactive, turning weeks of manual analysis into quick, confident action. Because results were delivered on August 28, 2025—weeks instead of months—Public Works could line up crews, contracts, and materials sooner, cutting the time between data collection and visible street fixes. Transparent scoring and map-based priorities now guide budget requests and day-to-day scheduling, which residents experience as faster pothole repairs, smoother commutes, and clearer answers at town hall.