MIND Launches Autonomous DLP Analyst to Automate Complex Data Security Operations

New updates have been reported about MIND.

MIND, a Seattle-based data security platform specializing in autonomous Data Loss Prevention and Insider Risk Management, has introduced the MIND Autonomous DLP Analyst to automate core DLP operations that have historically demanded intensive manual work by security teams. The release centers on two AI-driven capabilities—Custom Classifier and Issue Investigator—designed to reduce operational overhead, improve accuracy in detecting sensitive data and accelerate incident response across complex enterprise environments.

The Custom Classifier skill allows customers to train MIND on their own proprietary data types—such as source code, strategic documents, formulas and operational records—by uploading representative examples that the platform converts into tailored classifiers. These classifiers are then pushed into MIND’s multi-layer AI classification engine and deployed within each customer’s private instance, enabling protection across SaaS and generative AI tools, agentic AI systems, on-premise file shares, endpoints and email without relying on brittle regex rules and constant policy tuning.

The Issue Investigator skill targets the investigation phase of data security operations, where analysts often struggle to consolidate user actions, file activity and data sensitivity signals from multiple systems. By automatically reconstructing relevant context and highlighting key risk indicators, this capability aims to speed triage, sharpen risk assessments and support more consistent response decisions, ultimately enabling security teams to focus on higher-value work instead of manual correlation.

MIND positions the Autonomous DLP Analyst as a step forward in its broader strategy to deliver fully autonomous data security, building on its AI-native architecture and its status as the first data security firm to achieve ISO 42001 certification. Leadership, including Co-Founder and CEO Eran Barak and VP of Product Tom Mayblum, emphasizes that the platform is intended to let organizations “teach” the system what matters most in their environment while operating at AI speed. The company plans to continue adding AI skills to the Autonomous DLP Analyst, supporting customers that need to scale data protection without adding headcount or complexity, and is actively marketing the solution to enterprises managing sensitive data in modern, AI-heavy application stacks.