Nightfall

Nightfall is an AI-native data security and data loss prevention (DLP) platform designed to help organizations protect sensitive data across cloud and AI applications. The platform focuses on detecting, classifying, and preventing data leaks in real time, with a particular emphasis on modern workflows that involve SaaS tools, generative AI services, and autonomous AI agents. Unlike traditional DLP solutions that rely on static rules and manual oversight, Nightfall employs machine learning-based content classification to identify over 200 types of sensitive data, including personally identifiable information (PII), protected health information (PHI), payment card numbers, API keys, secrets, credentials, intellectual property, and custom patterns defined by the organization. One of its primary capabilities is data exfiltration prevention, which provides complete lineage tracking to understand how sensitive data moves within an organization. This is complemented by data detection and response (DDR) features that can instantly flag and block exposure events, such as someone pasting a credit card number into a public Slack channel or uploading a confidential document to a shared Google Drive. The platform also includes data discovery and classification tools that scan existing repositories—including email archives, cloud storage, and collaboration tools—to locate and remediate years of accumulated data exposure. A standout component is Nyx, an autonomous DLP analyst that functions as an AI agent itself. Nyx can independently observe data flows, reason about anomalous patterns, and take actions such as quarantining sensitive content, notifying security teams, or automatically revoking access permissions. This agentic capability addresses the growing complexity of AI agent eco