With comprehensive data in hand and delivery measured in weeks, Gloucester moved quickly from discovery to action, accelerating street improvements residents could feel.
Gloucester’s coastal climate and heavy seasonal traffic accelerated pavement deterioration, yet staff were working from outdated or inconsistent data, making it hard to know which roads to fix or when. Without a clear prioritization method, the team often found itself reacting to complaints and answering “Why not my road?” at public meetings. Budget planning was difficult to defend because estimates were based on partial information rather than a comprehensive network view.
Gloucester chose Cyvl to rapidly survey its entire network using vehicle‑mounted LiDAR and sensors, capturing precise surface condition across 158 miles. Within weeks—delivered by August 19, 2022—Cyvl’s Infrastructure Intelligence platform applied AI to generate condition scores, segment‑level insights, and prioritized repair lists. The city received detailed, actionable pavement condition data and defensible plans and reports to guide budgets, scheduling, and public communication.
With comprehensive data in hand and delivery measured in weeks, Gloucester moved quickly from discovery to action, accelerating street improvements residents could feel. Decision‑makers gained clear, defensible evidence to explain priorities and schedule crews, reducing delays between assessment and construction. Taxpayer dollars were allocated more efficiently because investments were tied to need, lifecycle value, and measurable outcomes.