Platform Overview
DATA LOSS PREVENTION
Data Detection & Response
Data Exfiltration Prevention
Data Security Posture Management
DATA PROTECTION
Data Encryption
Data Discovery & Classification
DATA PRIVACY FOR AI
Firewall for AI Developers
Firewall for AI Copilots
Key Features
Human Firewall
AI-Native Detection
Extensible Workflows
Use Cases
Prevent Secrets Sprawl
Prevent Data Exfiltration
Safeguard Personal Information
Secure AI Usage
Encrypt Sensitive Data Automatically
INDUSTRIES
SaaS & Cloud
Healthcare
Financial Services
COMPLIANCE
HIPAA
PCI
GDPR/CCPA
ISO 27001
SOC 2
SOX
Attack Vectors
SaaS & Email
AI & Custom Apps
Endpoint & Browsers
SAAS Integrations
ChatGPT & GenAI
Slack
Jira
Confluence
Salesforce
GitHub
Gmail
Google Drive
Zendesk
Notion
Microsoft 365 Suite
Google Suite
Microsoft OneDrive
Microsoft Teams
Microsoft Exchange
Firewall for AI
Getting Started
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API Quickstart
LLM Filtering Quickstart
Detection Playground
RESOURCES
Documentation
Libraries & SDKs
Tutorials
Learn
Blog
Guides
Webinars & Tutorials
Podcasts
AI Security 101
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Nightfall DLP vs. Legacy DLP
Nightfall vs Virtru
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Observability (logs, traces, metrics) is a core tenet to building strong software systems. Logs are used to debug issues and check on system activity, traces provide valuable insights into system performance and architecture, and metrics allow engineering teams to closely track business metrics within their systems.