Margo is an AI-driven cybersecurity assistant developed by Cervello, designed specifically for rail organizations. It uses Large Language Models (LLMs) to translate complex cybersecurity data and network insights into plain language, making security information accessible to personnel across different departments — from dedicated security teams to operational staff with no cybersecurity background. Margo provides contextual, role-specific responses based on the user's position within the rail organization, tailoring the depth and format of security insights to suit each team. This role-aware communication model aims to bridge the gap between cybersecurity specialists and non-technical rail operations staff. The assistant is intended to support incident response by delivering immediate, actionable insights during cyber events, reducing the time required to understand and act on threats. It also supports broader security risk management across departments by enabling teams to access relevant security data without waiting for direct input from security personnel. Key capabilities include: - Role-tailored delivery of cybersecurity insights in plain language - LLM-powered translation of technical security data for non-technical users - Accelerated incident investigation and response through on-demand querying - Cross-departmental collaboration support for unified security decision-making - Reduction of dependency on security team availability for routine security queries