Nightfall
AI-native data loss prevention platform that discovers and protects sensitive data across SaaS apps and cloud services.
What it does
Nightfall is an AI-native data loss prevention (DLP) platform that uses ML to discover, classify, and protect sensitive data across SaaS applications, cloud services, and developer tools - preventing accidental exposure of PII, PHI, PCI, and API secrets. AI capabilities include ML-powered sensitive data detection that identifies personally identifiable information, protected health information, credit card numbers, and API credentials across unstructured text in any application, intelligent false positive reduction that understands context to avoid flagging harmless information that matches sensitive data patterns, automated remediation workflows that redact, quarantine, or alert on sensitive data violations, developer tool scanning that monitors GitHub, Jira, and Confluence for exposed credentials, and compliance reporting that documents data exposure incidents for regulatory purposes.
Why AI-NATIVE
Nightfall is AI-native - ML sensitive data detection from unstructured text context across SaaS applications without fixed pattern rules is the core product architecture.
Best for
Small tech companies use Nightfall for SaaS DLP - AI detecting accidental PII exposure in Slack and GitHub without complex enterprise DLP infrastructure.
Mid-market organizations use Nightfall for cloud-native DLP - AI protecting sensitive data across SaaS applications that traditional network-based DLP tools cannot monitor.
Large enterprises use Nightfall for enterprise cloud DLP - AI monitoring sensitive data across the full SaaS estate and automated remediation reducing manual security operations workload.
Limitations
Nightfall protects data in SaaS applications and cloud storage — organizations needing endpoint DLP (data on laptops and USB drives) and network DLP require complementary solutions from vendors like Symantec or Forcepoint.
Nightfall's default ML models cover common sensitive data types but organizations with custom data classification requirements need to configure additional detection rules and train custom models.
Nightfall's automated remediation is most valuable when workflows are carefully designed — organizations must invest in defining appropriate automated responses for different sensitivity levels and violation types.
Alternatives by segment
Nightfall pricing based on employee count. Starter from $10/employee/month. Enterprise pricing negotiated. Annual contracts.
