FACT360 is a communication network analysis platform designed for insider threat monitoring, fraud investigation, and early case assessment. It applies unsupervised machine learning to analyze large volumes of communication data across multiple formats and sources, including emails, PDFs, instant messaging applications, and telephone conversations. The platform operates on a three-step process and is designed to handle data volumes and formats where manual analysis is not feasible. Because it uses unsupervised machine learning, users are not required to define search criteria or know in advance what topics to look for — the system autonomously identifies anomalies and unusual activity within communication networks. FACT360 surfaces "unknown-unknown" incidents, meaning it detects risks and behavioral changes that users were not previously aware of or actively searching for. It is used in two primary modes: - **Real-time monitoring:** Continuous surveillance of communication networks to detect emerging insider threats and behavioral anomalies as they occur. - **Investigative mode:** Post-incident analysis to support fraud and insider threat investigations, helping uncover admissible evidence and accelerating early case assessment. The platform is aimed at investigators, fraud analysts, and organizations seeking to manage insider risk. It is noted for identifying subtle behavioral changes in communication patterns and enabling fact-based organizational modeling to support strategic decision-making.