OpenText Cybersecurity Aviator is an AI-based threat detection platform that uses machine learning to identify and classify cyberthreats. The platform employs unsupervised machine learning models that automatically and continuously learn from security data without requiring human supervision or labeled examples. The system analyzes billions of security events to detect behavior-based patterns and attributes. It can deploy new threat detection models within hours to respond to emerging threats, compared to traditional approaches that may take weeks or months. The platform focuses on behavioral threat hunting by tracking and correlating security events across multiple sources. It uses advanced analytics to identify potential threats with context, enabling security teams to make informed decisions. The threat detection approach combines pattern recognition with automated analysis, integrating data from various sources to identify anomalies and potential security incidents. The unsupervised learning capability allows the system to discover data-based patterns and insights without requiring pre-defined threat signatures. The platform is designed to improve security operations efficiency by automating threat identification processes that traditionally rely on threshold-driven detection and manual hypothesis testing by security teams.