By August 26, 2022, Woodstock had network-wide condition scores and ready-to-use plans—delivered in weeks rather than months—so crews could act sooner.
Woodstock, CT manages a large, rural road network that takes a beating from New England freeze–thaw cycles, making it hard to know which roads to fix first and when to schedule work. Without current, consistent data, the town lacked accurate paving budgets and struggled to create defensible plans, often defaulting to reactive maintenance. At town meetings, leaders were pressed with “Why not my road?” and had limited evidence to justify decisions, fueling 311 calls and resident frustration.
Woodstock chose Cyvl to rapidly survey and analyze its entire network using vehicle-mounted LiDAR and sensors, scanning 117 roadway miles with uniform, high-resolution coverage. Cyvl’s Infrastructure Intelligence platform used AI to convert raw scans into detailed, actionable pavement condition data, standardized scores, and segment-level insights. The town received prioritized repair lists, data-backed multi-year scenarios, and clear reports that made planning, budgeting, and communication faster and more defensible.
By August 26, 2022, Woodstock had network-wide condition scores and ready-to-use plans—delivered in weeks rather than months—so crews could act sooner. The town moved from reactive fixes to a proactive, transparent program that directs dollars where they deliver the most community benefit. Residents saw faster patching and paving on the highest-need corridors, fewer surprises, and clearer explanations of what’s next.