Ai-powered Blyncsy Solution Adopted by The Alabama Department of Transportation

With an emphasis on modernization and evidence-led decisions, the agency has begun using the ai-powered Blyncsy platform statewide to refresh asset inventory work and reinforce planning for upkeep.

Blyncsy and Roadway Maintenance and Asset Inventory

Following a formal update from the engineering-technology provider, it was confirmed that the Alabama Department of Transportation has rolled out Blyncsy to refine its results-focused funding approach for road upkeep. To frame the partnership, the solution is part of a broader Asset Analytics lineup from Bentley Systems, and within the agency it sustains a budgeting process for highway maintenance that has guided decisions for more than fifteen years.

Automate Roadway Asset Inventory Without Manual Field Inspections

Spanning roughly eleven thousand miles, the system previously leaned on crews in the field and other labor-heavy approaches to check assets. For many years, decisions drew on a broad state-spanning review; with Blyncsy now in the mix, the department can automate targeted asset inspection and produce faster, steadier evaluations.

Imagery From Dash Cameras: An AI Approach to Road Asset Inventory

By drawing on imagery from dashboard-mounted cameras contributed by everyday vehicles, the platform applies machine learning to evaluate surface and roadside conditions at scale. That pipeline yields consistent, measurement-based reads on critical items—from guardrail segments to signage—across the full network, and an earlier pilot reported accuracy approaching ninety-seven percent from its AI models, supplying the dependable evidence needed for precise allocation and clearer roadway conditions.