Global – October 23, 2026 -- MIND is marketing a cloud-native platform that connects to existing systems in minutes and classifies sensitive data across SaaS applications, on-premise file shares, endpoints and email, with the stated aim of sharply reducing false positive alerts.
MIND says legacy RegEx and tagging leave gaps in data security
The company argues that sensitive data is scattered across four environments: SaaS apps, on-premise file shares, endpoints and email systems. Many data security tools cover only narrow areas, creating silos and gaps where risk can build. Pattern matching, RegEx and user tagging, it says, produce incomplete views and excessive false positives.
MIND also points out that each business holds unique sensitive data beyond common identifiers such as credit card or social security numbers.
Platform builds a living catalog of data, users and file activity
After connecting to existing systems, MIND generates a catalog of resources, users, authorizations, file activities and metadata. The company says this lets security teams assess and act on risk immediately. It claims the visibility covers data at rest and exceeds what conventional DLP delivers.
Hundreds of tailored algorithms classify files by content
MIND's multi-layer AI engine uses hundreds of tailored algorithms to categorize file types, including agreements, source code, medical records and board minutes. It classifies the sensitive elements inside files rather than relying on pattern matching alone.
The platform supports file types ranging from images to archives. Every file is automatically assigned tags and user-based labels. MIND says the business context it surfaces feeds policy-setting, compliance and incident response.