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FRACTA’s As-Built Digitization transforms how utilities and engineers digitize and manage legacy infrastructure data. By combining computer vision, machine learning, and geospatial intelligence, As-Built Digitization automatically converts scanned as-builts and raster maps into precise, GIS-ready datasets—delivering clean, connected spatial data in a fraction of the time and cost of traditional digitization.
FRACTA’s Likelihood of Failure (LOF) model uses AI and machine learning to predict which water mains are most likely to fail—before they break. By analyzing historical data, environmental factors, and pipe conditions, LOF helps utilities prioritize replacements, optimize budgets, and reduce emergency repairs with higher accuracy than traditional methods.
FRACTA’s Cost of Failure (COF) model quantifies the financial impact of water main failure. By analyzing economic, social, and operational risks, COF estimates the true cost of a break. When combined with FRACTA’s Likelihood of Failure (LOF) model, utilities gain a complete risk assessment.
FRACTA’s Total Risk (TR) model provides a comprehensive, data-driven approach to managing water main replacement decisions. By combining Likelihood of Failure (LOF) and Cost of Failure (COF), TR quantifies the financial and operational risk of potential pipe failures.
