Skylark Labs deployed a vehicle-mounted AI inspection system in Riyadh to verify post-construction road quality and hold vendors accountable to contractual durability standards -- powered by the Kepler platform and Synapse AI Box.
Riyadh's rapid infrastructure expansion creates specific quality assurance challenges. Contractual durability commitments require objective, repeatable verification methods. Roads span urban centers to desert corridors, each with distinct wear profiles, while high daily vehicle counts accelerate surface degradation beyond initial projections.
Extreme heat and sandstorms compound damage from construction traffic and heavy loads. Without AI-driven inspection, infrastructure investment lacks the accountability framework needed to protect public funds and ensure transportation network quality.
"When vendors guarantee a road will last ten years, you need an objective system to verify that claim. That is what we built."
HD cameras paired with adaptive AI classify crack types, rutting depth, and surface texture in a single pass. Defects are flagged instantly and mapped against vendor contract specifications through Sentinel AI Camera technology.
Every defect is geotagged and logged, creating an auditable record for contract enforcement. Live hazard detection protects inspection crews and alerts road users to active defects. The system integrates with international pavement standards for objective quality scoring.
Vendor accountability is built into the platform. When a contractor guarantees a road will last ten years, the system provides objective, repeatable evidence to verify that claim -- transforming road quality assurance from subjective inspection to data-driven enforcement.
The deployment in Riyadh demonstrated that AI-powered inspection can replace months of manual survey work with a single vehicle pass. Contract disputes that previously relied on subjective assessments now reference timestamped, geotagged evidence.
The platform is being extended to additional Saudi infrastructure programs, validating the approach for large-scale transportation quality assurance across the region.
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