Within weeks, the city had a comprehensive, network-level assessment and an actionable plan that aligned maintenance, rehabilitation, and preservation to community needs.
Westlake Village faced growing pressure to keep neighborhood and commuter corridors smooth, but outdated or inconsistent data made it hard to know which roads to fix or when. Without a reliable network-wide view, the city often found itself reacting to complaints instead of executing a strategic plan. Town discussions were tense and staff struggled to show a clear, defensible basis for decisions, leaving residents uncertain about when their street would be addressed.
Westlake Village selected Cyvl to rapidly survey the entire network, capturing 45 roadway miles with vehicle-mounted LiDAR and sensors to objectively measure pavement condition and distresses. Cyvl’s Infrastructure Intelligence platform used AI to turn raw data into block-level condition scores, prioritized repair lists, budget scenarios, and defensible multi-year plans. Delivered by May 1, 2025, the city gained actionable reports and maps that made it easy to brief council, communicate with residents, and schedule work quickly.
Within weeks, the city had a comprehensive, network-level assessment and an actionable plan that aligned maintenance, rehabilitation, and preservation to community needs. Staff could show clear, map-based condition scores and funding options, replacing debate with data and accelerating decisions. Crews immediately targeted the most critical segments within a balanced program, shortening the time between data collection and visible improvements for residents.