Veridium AI-Driven Identity Threat Protection is an identity security solution that uses machine learning algorithms to monitor and analyze user behavior for threat detection. The system creates quantifiable profiles based on user biometrics, mobile devices, computers, and network data to establish standard behavioral contexts. The solution leverages device sensors including accelerometers and gyroscopes from mobile phones to measure user-smartphone-computer relationships. It performs continuous behavioral analysis during authentication and re-authentication attempts to detect anomalies and potential security threats. The platform includes Intelligent Login Protection with User Behaviour Analysis that generates behavior scores. These scores can be processed by the Veridium server or integrated with third-party risk engines. The system combines behavioral data with additional phone data such as geolocation to provide adaptive authentication decisions. When an imposter attempts to login or steal a session, the system can automatically log out the unauthorized user. The solution operates as a transparent security layer that learns typical user authentication patterns over time. The platform supports deployment across on-premises, hybrid, and cloud environments, addressing digital sovereignty concerns for organizations managing sensitive identity data. It integrates with Zero Trust security architectures and includes low-code orchestration capabilities for policy management.