Case Study: Virginia 811 improves excavation ticket error detection with Skapa Tech’s AI-powered VArif-AI app

Virginia 811 finds 1,100 ticket errors in 3 weeks with Skapa Tech

Virginia 811 (VA811), a safe digging organization, faced the challenge of manually auditing thousands of excavation tickets for errors, a process that was inefficient and only uncovered errors in 3% of the tickets they checked. They developed a machine learning algorithm to improve detection but needed Skapa Tech to create an interface to access and act on that data.

Skapa developed the VArif-AI web application, which automated the processing of tickets with the existing ML algorithm and queued errors for human review. This solution allowed auditors to focus on correction instead of discovery. In just three weeks, the system processed nearly 43,000 tickets, identified 1,100 errors, and more than doubled the error detection rate, significantly enhancing safety and enabling swift corrective actions for excavators in Virginia.

Virginia 811 (va811)