Designed for teams that need to bridge the gap between discovery and technical execution. Its architecture allows for processing massive data volumes without sensitive information ever leaving the client's infrastructure.
Key Features:
Local-first PII Discovery: Deep database scanning with zero data egress.
Confirmation Flow: A technical interface to validate labels and sensitivity levels (High/Medium/Low) based on confidence scores.
Executable Metadata: Once confirmed, labels act as the "source of truth" to automatically trigger anonymization and synthesis engines.
Ideal for: Companies in regulated sectors (Fintech, Healthtech, Insurance) that need to move from discovery to operational protection without security trade-offs.
Specializes in unstructured data analysis and managing the blast radius of information across file servers and cloud storage.
Key Features:
Data Privilege Management: Visualizes permission structures to eliminate excessive access to sensitive data.
User Behavior Analytics (UBA): Proactively detects threats and ransomware by analyzing access patterns.
Automation Engine: Automatically repairs misconfigured permissions in file systems.
Ideal for: Organizations with massive volumes of unstructured data (PDFs, Excels, shared docs) that need to ensure access governance and detect breaches in real-time.
A platform designed with a strong focus on privacy compliance (GDPR, CCPA), centered on finding relationships between disparate data points.
Key Features:
Identity Intelligence: Advanced correlation that links technical data points to specific real-world identities.
Privacy Portal: Automates compliance workflows like Right-to-be-Forgotten or Data Subject Access Requests (DSAR).
Data Cataloging: Creates a unified inventory spanning public clouds to SaaS applications.
Ideal for: Compliance and Privacy teams in global enterprises managing data across multiple jurisdictions.
A veteran solution that combines data discovery with leak prevention at the network perimeter and endpoints.
Key Features:
Exact Data Matching (EDM): Identifies specific data (like account numbers) even when in motion or fragmented.
Endpoint Control: Monitors user activity on physical devices, blocking unauthorized copies to USBs or personal clouds.
OCR Scanning: Classifies sensitive data contained within images or screenshots.
Ideal for: Companies concerned with insider threats and data exfiltration from a distributed workforce.
The natural choice for organizations residing entirely within the Azure and Microsoft 365 ecosystem.
Key Features:
Native M365 Integration: Automated sensitivity labeling integrated directly into Word, Excel, Outlook, and Teams.
Unified Map: Visibility of data assets across Azure, third-party clouds, and on-premises databases.
Information Barrier Policies: Prevents communication and data sharing between specific departments to avoid conflicts of interest.
Ideal for: Microsoft-centric organizations looking for a seamless governance solution that deploys natively within their daily productivity tools.
The effectiveness of modern data classification tools lies in how metadata translates into actionable controls. While legacy tools provide visibility, platforms like Gigantics enable active governance—ensuring that sensitive data is not only identified but protected every time it moves through your pipelines. Building a scalable strategy for data classification is the first step toward a true Zero Trust architecture.
