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AdRem NetCrunchNetCrunch is commercial, self-hosted, agentless network and IT infrastructure monitoring software for Windows Server. It monitors network devices, servers, virtualization platforms, cloud services including AWS, Azure, and Google Cloud, applications, websites, logs, telemetry, and custom data using technologies such as SNMP, WMI, REST APIs, and scripts. NetCrunch supports 680+ monitoring targets and provides 270+ ready-to-use Monitoring Packs for devices, applications, and operating systems. Policy-based monitoring automatically applies monitoring settings, Monitoring Packs, thresholds, and alerts to matching devices and systems. Licensing is based on monitored nodes and network interfaces rather than individual sensors, checks, or metrics. Real-time dashboards and automatic Layer 2 and routing topology maps provide visibility into network status and performance. NetCrunch supports event correlation, dependency-aware alert suppression, predictive thresholds, escalation, and 40+ automated response actions, including script execution, notifications, webhooks, and integrations with external IT and collaboration tools. NetCrunch also provides hardware and software inventory, network device configuration backup and change tracking, bandwidth monitoring, and network traffic analysis using NetFlow, sFlow, IPFIX, and other flow technologies. Distributed Monitoring Probes extend monitoring to remote and isolated locations, while REST APIs support integration and automation with external systems. NetCrunch is self-hosted on Windows Server and can monitor on-premises, air-gapped, cloud, and hybrid IT environments.
What is Raptor GRC Classifier?
The Raptor GRC Classifier is a self-hosted tool tailored for the classification of emails and documents within environments like Microsoft Office and LibreOffice/OpenOffice. Administrators can develop and sign policy bundles with classification labels that modify email subject lines, enhance documents with markings, and incorporate watermarks. Each label can be tailored with specific rules to allow actions, issue warnings, require justifications, or block messages, while users have the chance to evaluate draft policies before they go live. Even when a connection to the server is lost, cached policies continue to be enforced on client devices. A web-based dashboard provides real-time insights into device health, logs events from clients, manages a persistent document inventory with unique IDs, and supports data exportation in CSV or Excel formats. The software also offers functionality for endpoint discovery, integration with Microsoft Purview labels, forwarding capabilities to SIEM systems, and the use of signed webhooks. The server must operate on a Linux container host, while clients are compatible with Windows and Ubuntu systems. Early-access versions of the software are released for testing, although they are not intended for production use. This solution equips organizations with a robust mechanism for document and email classification, promoting compliance while enhancing data governance. Furthermore, its user-friendly interface and extensive features can significantly streamline administrative tasks related to data management.
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
No images available
Integrations Supported
Box
Claude
Claude for Legal
Cohere
Confluence
Gemini
Gemini 2.0 Flash
Gemini Nano
Gemini Pro
GitLab
API Availability
Has API
API Availability
Pricing Information
Pricing not provided
Free Version
Pricing Information
Pricing not provided
Supported Platforms
Windows
On-Prem
Linux
Supported Platforms
SaaS
Windows
Mac
On-Prem
Linux
Customer Service / Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Not specified
Training Options
Documentation Hub
Online Training
Company Facts
Organization Name
Biff Labs
Date Founded
2026
Company Location
United Kingdom
Company Website
raptorgrc.com/products/classifier
Company Facts
Organization Name
MIND
Company Location
United States
Company Website
mind.io
Categories and Features
Data Classification
Not specified
Categories and Features
Data Classification
Not specified
Data Discovery
Not specified
Data Loss Prevention
Not specified
Data Security
Not specified
Insider Threat Management
Not specified