Autonomous DLP Analyst

Your next DLP Analyst is now autonomous.

The Autonomous DLP Analyst helps security teams run modern data security programs without the traditional burden. Its Custom Classifier and Issue Investigator skills are designed to autonomously handle the most complex and time-consuming DLP workflows. And this is just the beginning.

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An unsustainable amount of manual work

Most DLP programs require enormous amounts of manual input from highly skilled security analysts. Building classifiers, investigating alerts or tuning regex patterns. All of this is time consuming, difficult to scale and prevents them from focusing on what truly matters.

Reliance on complex regex rules, static policies and continuous tuning to classify business-specific sensitive data

Security teams spend significant time sorting out signals from noise and reconstructing activity across systems

Autonomous DLP Analyst

Custom Classifier skill

Organizations hold unique data like formulas, code and intellectual property. Custom Classifier is trained from your examples and prompts to generate precise classifiers across SaaS, AI apps, on-prem, endpoints and emails.

Issue Investigator skill

Issue Investigator analyzes alerts, reconstructs user activity and data movement, highlights true risk signals and guides investigations so teams resolve incidents faster with clear context and confident decision-making.

Designed to evolve

The first skills of the Autonomous DLP Analyst are Custom Classifier and Issue Investigator. Future skills will help organizations reduce manual effort while improving their response to real risk.

Why this matters

Security teams are under constant pressure to protect sensitive data across their entire IT environment. Yet running a DLP program often requires hours of manual work defining classifiers, reviewing alerts and reconstructing incidents across multiple systems. As environments grow more complex, this operational burden only increases.

The MIND Autonomous DLP Analyst is a force multiplier. By applying AI to the repetitive workflows that consume analyst time, the result is a more scalable, effective approach to data security that lets teams focus on what truly matters.

What is the future of autonomous data security?

Modern environments operate at the speed of AI and legacy controls with manual workflows cannot keep pace. Autonomous data security aims to change that equation. These first skills of the Autonomous DLP Analyst accelerates how MIND reduces risk and improves data security operations.

The Autonomous DLP Analyst will continue to evolve with additional skills designed to handle more of the workflows that slow security teams down today. Each skill moves another operational task from manual effort to intelligent assistance.

See more of MIND

Data discovery and classificaton

Gain a complete inventory of your data, users and activities across the business. Now you can see the content and context of your sensitive data and drastically reduce false positive alerts.

Data detection and response (DDR)

MIND pinpoints exposure risks and automatically enforces policies for your data at rest. Now you can secure the sensitive data in your organizations and fix issues before they become incidents.

Loss prevention and mitigation

MIND™ developed autonomous, context-aware and risk-based assessments to prevent loss of your most valuable information in real-time, rather than the manual and static compliance policies of conventional data loss prevention (DLP) tools, in order to put your DLP and Insider Risk Management (IRM) programs on autopilot.

Integrated identity and data security

Stop insider threats with the integration of Okta, the leading independent identity partner, and MIND, the first autonomous data security platform to protect data at rest and in motion.

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