# Nightfall vs Legacy DLP: What's the difference? Traditional data loss prevention (DLP) platforms focus primarily on securing data on endpoints (devices like laptops, phones, servers) or networks. As such, they don’t provide visibility into cloud applications and cloud data infrastructure that enterprises are rapidly moving towards. Nightfall is the industry’s first cloud-native DLP platform focused on detecting & protecting data in the cloud by integrating directly with these services via their APIs. Legacy DLP solutions are also limited in what they can recognize because they rely on traditional detection methods, such as regex rules and digital signatures/fingerprints. These have severe limitations in accuracy, usually resulting in a high volume of false positives, and significant alert fatigue for end-users. This means negative ROI and limited value. In contrast, Nightfall leverages machine learning to scan data and its surrounding context, meaning Nightfall can scan both structured & unstructured data with high accuracy. Because of this higher accuracy, customers often have Nightfall automate the response to data leakage events, yielding measurable time savings. Security, compliance, and engineering teams can focus on other problems, versus triaging alerts, getting hours back in their day. What was once negative ROI with traditional DLP is now positive ROI with Nightfall. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://help.nightfall.ai/faqs/nightfall_vs_legacy_dlp.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.