Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Your security tools can detect credit card numbers, but they are blind to the files that actually matter. In this demo, we show how sensitive documents like: Internal source code Financial forecasts Performance reviews Customer lists are automatically detected and blocked in Slack, Google Drive, SharePoint, Gmail, and even ChatGPT using Nightfall’s new AI-powered file classifiers. No regex. No keywords. No training data.

See how to build a prompt-based custom entity detector in Nightfall that understands context, not just patterns. Using a real healthcare example, you’ll see how prescription numbers are detected accurately while similar-looking data like purchase order numbers are ignored. You’ll see: Why regex breaks down in real workflows How prompt-based detection reduces false positives Creating a custom detector with positive and negative examples Deploying it to Slack and validating results across files.

Many sensitive documents don’t fit cleanly into standard categories, and traditional approaches like regex or broad classifiers often create noise and false positives. In this video, we walk through how to use Nightfall’s prompt-based file classifiers to detect business-critical documents based on intent, not brittle patterns or custom model tuning.