Harness Continuous Verification (CV) leverages machine learning to detect anomalies in deployments, enabling rapid rollback and ensuring deployment reliability by analyzing and comparing data points against control hosts for risk assessment. The process begins by setting up a verification step within a workflow, after which Harness makes an API call to the verification provider to collect data for analysis. The machine learning algorithm then compares this data with the verification type, marking transactions as either risky or not, which aids in isolating issues before final deployment. Harness allows for flexibility through custom queries for metrics and log verifications, ensuring control over specific deployment analyses. It supports major APM and logging vendors, with options to include custom APMs, enhancing its adaptability to various deployment environments.