Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

Get a first look at Nightfall's revolutionary new features that transform how security teams handle insider risk investigations and Gen AI governance. In this product demo, we walk through.

See how security teams reconstruct insider risk investigations with Nightfall's new Forensic Search feature, going beyond policy alerts to uncover the complete story behind every potential threat. In this 15-minute demo, watch three real-world investigation scenarios: Departing engineer exfiltrating code to personal cloud storage Sales associate moving customer data to USB devices CFO accidentally using shadow IT with sensitive financial data.

See the future of data loss prevention in action. This live demo showcases Nightfall's breakthrough session differentiation technology that intelligently blocks sensitive file uploads to personal cloud accounts while seamlessly allowing them in corporate environments.

Tired of drowning in false positives? See how Nightfall's AI-powered detection achieves human-level accuracy and makes DLP automation possible. See three breakthrough capabilities from Nightfall: Prompt-based entity detectors - Protect custom IDs with natural language (no regex!) 23+ AI file classifiers - Detect source code, HR files, customer lists automatically Custom classifiers - Build your own in minutes with one sample file.

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.

ZenBusiness has empowered over 850,000 business owners to launch and grow their businesses. And they’re doing it without letting data protection slow them down. With Nightfall AI’s automation-first DLP, ZenBusiness secures critical enterprise apps, resolves issues efficiently, and keeps their focus on delivering value to business owners. Chris Chipman, Enterprise IT Architect at ZenBusiness, calls Nightfall “that extra IT staff member” that runs 24/7, protecting data wherever it goes.

Discover how Nightfall's advanced AI-based detection is transforming the way organizations protect their most valuable digital assets: API keys and passwords. This short demo illustrates where traditional DLP systems fall short and how Nightfall's innovative approach achieves industry-leading precision.

Discover how Nightfall AI's new insider risk feature tackles the growing challenge of shadow AI and unsecured use of generative AI tools in the workplace in our short demo: Experience how Nightfall can help your organization.