Milton moved from reactive decision-making to a confident, proactive program grounded in current, trustworthy data.
Milton, MA faced growing pavement maintenance needs across neighborhood streets and commuter corridors without a clear, current picture of road conditions. Outdated or inconsistent data made it hard to build defensible paving plans and set reliable budgets, leaving leaders uncertain in public meetings. The team often had to react to complaints and answer “Why not my road?” without objective evidence, which strained trust and slowed progress.
Milton chose Cyvl to rapidly survey the entire network using vehicle-mounted LiDAR and sensors, scanning 97 roadway miles with consistent, high-resolution coverage. Cyvl’s Infrastructure Intelligence platform used AI to create block-by-block pavement condition scores, prioritized repair lists, and defensible plans and reports that align projects with available budgets. Delivered by April 17, 2025, the city received detailed, actionable pavement condition data to make faster decisions, communicate tradeoffs clearly, and schedule work sooner.
Milton moved from reactive decision-making to a confident, proactive program grounded in current, trustworthy data. With results delivered in weeks rather than months, the city reduced the time between data collection and project implementation—speeding visible improvements for residents. The scan of 97 roadway miles gave public works an objective foundation to plan work, justify budgets, and communicate timelines clearly to the community.