Nightfall

Nightfall AI is centered on protecting sensitive data wherever modern organizations create and share it. Its data security capabilities address areas such as data loss prevention, sensitive-data discovery, SaaS environments and emerging AI-related data risks. This matters because confidential information can leave the traditional security perimeter through collaboration tools, cloud applications, developer workflows and AI assistants. Nightfall's approach is therefore focused on identifying the actual data involved and applying controls around how that information is used. Security teams can use this type of visibility to discover sensitive content, investigate risky activity and reduce accidental or unauthorized exposure. The platform is particularly relevant to organizations with large SaaS footprints, distributed employees and growing adoption of generative AI. A useful evaluation should map the applications and data stores that matter most, then examine detection accuracy, policy controls, remediation workflows, integrations and support for AI-related use cases. For companies building a modern data protection program, the combination of DLP and data security posture management can provide a more complete view than isolated endpoint controls.