Data Privacy & DLP for AI refers to solutions designed to protect sensitive information and ensure compliance with data privacy regulations in environments where artificial intelligence systems process, store, or transmit data. These solutions address the unique risks introduced by AI models, such as inadvertent data exposure, model inversion attacks, and unauthorized data extraction. Core capabilities include monitoring and controlling data flows into and out of AI systems, enforcing data minimization, and applying privacy-preserving techniques such as anonymization, pseudonymization, and differential privacy. Technical features often involve policy-based data loss prevention (DLP), real-time detection of sensitive data usage, and integration with AI model training and inference pipelines to prevent leakage of confidential information. Typical users include data protection officers, AI engineers, compliance teams, and security analysts in organizations deploying AI-driven applications. Their primary objectives are to safeguard regulated data, prevent intellectual property loss, and maintain compliance with frameworks such as GDPR, HIPAA, or CCPA. This category differs from general DLP or privacy tools by focusing specifically on the data lifecycle within AI workflows and the unique threats posed by machine learning models. Cyberin provides a neutral platform for discovering and comparing Data Privacy & DLP for AI solutions.