Secuvy Data Discovery & Classification is a data discovery and classification platform that uses unsupervised machine learning and data linkage techniques to identify and tag sensitive data across an organization's data environment. Unlike rule-based or regex-dependent tools, the platform learns patterns from data autonomously without requiring pre-labeled datasets. It adapts over time as data changes, reducing the need for manual configuration or rule tuning. Key capabilities include: - Unsupervised Learning: The platform self-trains on organizational data to identify unique patterns, reducing reliance on predefined rules and enabling detection of complex, organization-specific data types such as intellectual property, CUI, ITAR documents, proprietary research, CAD files, and confidential supplier agreements. - Data Linkage: Connects records that refer to the same entity across different formats and systems, improving classification accuracy and reducing false positives by understanding data in context. - Continuous Monitoring: Provides automated, ongoing visibility into sensitive data to support audit readiness. The platform is designed for use cases including DLP programs, AI governance, and data privacy initiatives. It supports on-premises deployments, including air-gapped environments, making it applicable for regulated industries such as defense contracting and biopharma. The product targets organizations that need to manage regulated data (e.g., CUI, ITAR) and proprietary information that traditional classification tools fail to detect.