MIND Autonomous DLP

MIND Autonomous DLP is an AI-native data loss prevention platform that combines data security posture management with active prevention capabilities. It is designed to protect unstructured data across SaaS applications, GenAI apps, on-premise file shares, endpoints, and email environments. The platform operates across three primary functional areas: **Discovery & Classification** MIND continuously scans and classifies unstructured data across connected environments using a multi-layered AI classification engine (MIND AI). It surfaces sensitive data risks without requiring manual triage. **Detection & Response** The platform analyzes security signals and user behavior to identify incidents related to data exposure, exfiltration, and insider threats. Each incident is scored by risk severity and enriched with contextual information. Automated responses include revoking access, deleting files, relabeling data, alerting owners, or engaging users directly, with a full audit trail maintained throughout. **Policy Management & Prevention** MIND automates both the creation and enforcement of data security policies. Policies apply to data at rest and data in motion, with context-aware enforcement actions such as blocking, coaching, or escalating. The platform monitors endpoint and user behavior to trigger appropriate responses, including controls targeting GenAI app usage. The platform is positioned as a replacement for static, rule-based DLP tools, offering autonomous operation with minimal manual intervention. It covers data at rest (classification, access understanding, risk prioritization, early remediation) and data in motion (real-time behavior detection, policy enforcement, user collaboration).