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Nightfall

AI-native data loss prevention platform that discovers and protects sensitive data across SaaS apps and cloud services.

Listed Needs re-verification
Security IT Ops $ Small business Mid-market Enterprise Technology

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.

Strengths

  • 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.
  • Small tech companies use Nightfall for SaaS DLP - AI detecting accidental PII exposure in Slack and GitHub without complex enterprise DLP infrastructure.

Watch-outs

  • SaaS and cloud DLP focus — not network or endpoint DLP: 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.
  • AI detection requires tuning for organization-specific patterns: 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.
  • Remediation actions require workflow design investment: 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.

Pricing

Nightfall pricing based on employee count. Starter from $10/employee/month. Enterprise pricing negotiated. Annual contracts.