Case Study: Network Rail improves safety-critical call compliance with Capgemini AI auditing solution

Network Rail - Customer Case Study

Network Rail, the UK rail operator responsible for millions of passenger journeys and freight movement, needed a way to test whether an AI-based solution could audit phone calls for safety-critical communication (SCC) compliance. The company was looking for a feasibility study to improve call quality, identify training needs, and support safer day-to-day maintenance operations.

Working with Capgemini Applied Innovation Exchange, Network Rail developed a proof of concept that combined speech-to-text, NLP, and custom call-analysis logic to review calls against clarity, completeness, compliance, and focus. Capgemini helped test the model using 200 call recordings and Network Rail’s SCC manual, and the results showed the AI could detect non-compliant calls, spot missing information, and handle background noise reasonably well. The pilot also identified the share of call time devoted to SCC, giving Network Rail a practical path toward more efficient compliance auditing and safer operations.

Network Rail