Privado Dynamic Data Maps is a data mapping automation platform designed to help organizations build and maintain accurate records of personal data processing activities without manual questionnaires or assessments. The platform scans multiple data sources to discover and map personal data flows: - Code Scanning: Analyzes source code of first-party apps, websites, and backend software to identify personal data elements and how they are shared. - 3rd Party Scanning: Scans third-party SaaS applications (CRM, HRIS, CLM, CDP, ESP, ITSM) to identify personal data flows to external systems. - Web & App Scanning: Scans live user-facing websites and mobile applications to detect real-time privacy risks and data sharing behaviors. - AI Agents: Analyzes documentation, contracts, policies, and data inventories to populate assessments, build data maps, and flag privacy risks. Key capabilities include: - Data Inventory: Identifies and auto-categorizes personal data elements across processing activities, tagging sensitive health, financial, and location data, with links to data sources for validation. - Third-Party Inventory: Discovers all third parties receiving personal data and provides real-time alerts for new data-sharing relationships. - Data Flow Mapping: Tracks data elements across websites, apps, databases, backend systems, and third parties, including cross-border transfers and AI application data sharing. - RoPA Automation: Uses AI agents to populate Records of Processing Activities (RoPAs) by pulling from real-time scan results and uploaded documentation, eliminating manual input. - Integration with privacy tools: Syncs data mapping results to external privacy management platforms.