Designing an AI agent for support ticket extraction under strict compliance necessitates a multi-faceted approach, prioritizing data privacy and security from the outset. Key is implementing robust anonymization and encryption techniques for sensitive information, coupled with stringent role-based access controls to extracted data and model configurations. The agent must be trained with a focus on data minimization principles, extracting only the absolutely necessary information while flagging or redacting any personally identifiable information (PII) that falls outside defined scope. Furthermore, an essential component involves integrating a human-in-the-loop validation process for high-risk extractions, ensuring accuracy and adherence to specific regulatory requirements. All operations must include comprehensive auditing and logging capabilities, providing an immutable record of what data was accessed, extracted, and by whom, fulfilling transparency obligations. This holistic strategy ensures not only efficient information retrieval but also unwavering compliance with strict data governance policies. More details: https://www.grcactedev.fr/ACTEDEV_WEB/FR/emailing_clique.awp?AWP=oui&url=https://infoguide.com.ua&nombd=ACT_RACAN&idr=22882