New AI-driven capabilities provide predictive maintenance for bridges, culverts, retaining walls, and seawalls across thousands of infrastructure assets worldwide.
NEW YORK, Feb. 25, 2025 /PRNewswire/ — Dynamic Infrastructure (DI) is unveiling the latest version of its AI-powered platform, delivering real-time, predictive intelligence for civil infrastructure management. By combining advanced computer vision with deep language understanding, DI analyzes both images and inspection reports, even when unstructured and complex, to extract critical insights. This fusion of visual and textual data enables continuous monitoring and risk forecasting across thousands of bridges, culverts, retaining walls, and seawalls, helping asset owners transition from reactive maintenance to proactive, data-driven decision-making.
Immediate Impact on Infrastructure Maintenance and Safety
With this latest platform release, Dynamic Infrastructure is delivering AI-powered monitoring at scale, enabling counties, towns & BOT civil engineers to:
-
Prevent costly failures through automated risk prioritization and predictive maintenance planning.
-
Save processing time by automatically generating objective structural data.
-
Reduce operational costs by optimizing inspections’ data and resource allocation.
-
Enhance public safety with continuous monitoring that proactively identifies structural risks.
As infrastructure agencies worldwide face increasing maintenance challenges, Dynamic Infrastructure is leading the change in AI-driven asset maintenance management. The latest product version is already enhancing maintenance strategies across thousands of bridges, culverts, retaining walls, and seawalls, ensuring safer, more resilient infrastructure for years to come.
Traditional infrastructure assessments struggle to connect the dots between inspection reports and other visual records, making it difficult to build a clear picture of an asset’s condition over time. These data sources complement each other, yet their differences make direct comparison error-prone, especially when trying to detect patterns and assess deterioration from historical records. DI’s multimodal fusion technology bridges this gap by seamlessly integrating images and reports, creating a continuously evolving model of infrastructure health. This latest release enhances condition tracking, enables a deeper understanding of structural changes, automates risk assessment, and supports proactive maintenance across a wide range of civil infrastructure assets.