Armed with current, trustworthy data across 57 miles and a clear plan delivered quickly, Sherborn shifted from reactive maintenance to proactive asset management that residents can see on the street.
Sherborn’s road network was managed with outdated and inconsistent information, which meant leaders did not know which roads to fix or when and could not reliably estimate paving budgets. Without a clear, defensible prioritization method, staff struggled to create work plans and often had to react to complaints instead of executing a strategy. At town meetings, residents frequently asked “Why not my road?”, and the city lacked objective, up-to-date data to justify decisions and timelines.
Sherborn chose Cyvl to rapidly survey the entire network, capturing 57 miles with vehicle-mounted LiDAR and high-resolution sensors in a matter of weeks. Cyvl’s Infrastructure Intelligence platform used AI to transform the scans into detailed, actionable pavement condition scores, segment-level repair recommendations, and budget scenarios—delivered by August 20, 2024. With defensible reports, prioritized repair lists, and GIS-ready layers, Sherborn gained the evidence needed to plan proactively, communicate clearly, and move projects to construction faster.
Armed with current, trustworthy data across 57 miles and a clear plan delivered quickly, Sherborn shifted from reactive maintenance to proactive asset management that residents can see on the street. Public works now schedules crews, times bids, and coordinates utilities with confidence, reducing the lag between data collection and project implementation. City leadership communicates priorities with maps and scores, making it easier to defend budgets and show taxpayers where and when improvements will occur.