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What is ManageEngine Endpoint DLP Plus?

ManageEngine's Endpoint DLP Plus is an enterprise-grade solution that employs sophisticated strategies for data loss prevention, effectively safeguarding sensitive information on endpoint devices. By automating the identification, tagging, and regulation of data transfer throughout the network, the solution plays a crucial role in swiftly addressing insider threats and safeguarding critical information. Additionally, it generates a variety of reports that enhance data visibility and bolster overall cybersecurity measures, ensuring organizations are well-equipped to manage their sensitive data effectively. This comprehensive approach to data protection not only mitigates risks but also empowers businesses to maintain compliance with data security regulations.

What is MIND?

MIND is an AI-native data loss prevention platform that helps organizations discover, monitor, and protect sensitive information across users, applications, infrastructure, GenAI systems, and autonomous AI agents. The platform combines data discovery and classification, Data Detection and Response, loss prevention and mitigation, integrated identity and data security, and AI-powered DLP agents. MIND continuously identifies and classifies sensitive data across SaaS applications, GenAI services, agentic AI, endpoints, email, and on-premises file shares to reduce data security blind spots. Its real-time detection capabilities analyze billions of signals and enrich incidents with contextual information so security teams can focus on activity that represents meaningful risk. Autonomous remediation can address identified incidents without requiring teams to manually investigate and resolve every data security event. MIND can also prevent sensitive information from leaving an organization in real time and coach users when their actions create data security risks or conflict with organizational policies. The platform is designed to reduce traditional DLP complexity by eliminating the need to manually write regular expressions, extensively tune policies, or depend on professional services for routine operation. MIND supports GenAI security by helping organizations control how sensitive enterprise information is accessed and used as employees adopt generative AI applications. It also addresses agentic AI security, helping organizations protect sensitive information as autonomous AI agents gain access to enterprise data and perform actions on behalf of users. Additional use cases include SaaS data protection, endpoint DLP, on-premises DLP, email DLP, insider risk management, automated data remediation, and reduction of DLP false positives.

Media

Media

Integrations Supported

Google Drive
Microsoft OneDrive
Microsoft Outlook
Siberson Veriket Data Classification
iCloud

Integrations Supported

Google Drive
Microsoft OneDrive
Microsoft Outlook
Box
ChatGPT
Claude
Confluence
Gemini 1.5 Flash
Gemini 2.0
Gemini Enterprise
Gemini Nano
Gmail
HiBob
Intercom
Microsoft Azure
ServiceNow
Windows Server
Zendesk

API Availability

API Availability

Pricing Information

$795/100 Workstations
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

Windows
On-Prem

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

ManageEngine

Date Founded

2000

Company Location

India

Company Website

www.manageengine.com/endpoint-dlp/

Company Facts

Organization Name

MIND

Company Location

United States

Company Website

mind.io

Categories and Features

Data Loss Prevention

Compliance Reporting
Policy Management
Sensitive Data Identification
Web Threat Management
Whitelisting / Blacklisting

Categories and Features

Data Classification

Not specified

Data Discovery

Not specified

Data Loss Prevention

Not specified

Data Security

Not specified

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