MIND DLP (Data Loss Prevention) is a data security product designed to reduce the operational burden associated with managing data security alerts. The product focuses on lowering alert volume through smarter data classification, automated remediation, and user-guided enforcement. Key capabilities center on reducing the total number of alerts analysts must handle — claimed at a 67% reduction in alert volume — which in turn decreases the number of full-time employees (FTEs) required for alert triage. This allows organizations to achieve full alert coverage without adding headcount. The product also addresses autonomous DLP for agentic AI environments, positioning itself within AI-related data security use cases. The page being analyzed is a DLP Savings Estimator tool — an interactive calculator — rather than a full product page. It allows organizations to input: - End-user count - Alerts per user per month - Annual analyst salary - Average alert triage time (in minutes) Based on these inputs, the estimator projects cost savings by comparing the status quo triage effort to the effort required with MIND, factoring in annual alert hours, FTEs required, and total FTE cost.