Nightfall AI

Unit21 needed to unlock generative AI. Protecting sensitive financial data was non-negotiable. Legacy DLP tools couldn’t keep up. Employees experimenting with AI put customer info at risk. Nightfall AI allows Unit21 to block sensitive data before it reaches unauthorized AI apps guide teams safely to use approved tools. With everything managed directly in Slack, security stays tight, without slowing anyone down. Discover how Unit21 empowers AI-driven innovation that stays fully compliant with Nightfall: https://lnkd.in/dyww-ZXu

“Employees aren’t trying to hide AI use—they simply don’t know it’s a problem.” – Rohan Sathe, CEO of Nightfall AI As generative AI adoption skyrockets, many businesses struggle to keep pace. Static policies written months ago can leave staff uncertain—some fearful of using AI at all, others using it in secret. The solution is clear: real-time, dynamic guidance, communicated consistently, combined with positive reinforcement. Companies that define permitted tools, disclosure expectations, and responsible use can turn AI from a compliance risk into a productivity advantage. Read the full article to learn how organizations can give employees the clarity they need to use AI safely and confidently: https://lnkd.in/gGVK7qn2

Nightfall Product Updates are here! Nyx 2.0, our autonomous DLP analyst, is faster, smarter, and designed for real insider-risk workflows: - Nightly Insider Risk Brief: Summarized top risks every morning - Full-Screen Review Mode: Clean, distraction-free triage - Smarter Detection & Scoring: Clearer, faster insights - Prompt Cards & Prompt of the Month: Quick queries for hidden exfiltration Plus, Nightfall AI now offers: - AI-Powered Detection: 20+ new file classifiers & natural language prompt-based detectors - Data Exfiltration Prevention: Personal vs. business account checks, endpoint previews, Windows content inspection, and customizable block messages - Zendesk Enhancements: Automated tagging, precise scanning, and streamlined remediation Protect your sensitive data, IP, and insider-risk exposure. More efficiently than ever. Read all about our product updates here: https://lnkd.in/eKqN4JF4 Want Early Access? Reach out to support@nightfall.ai

The recent Palantir lawsuit highlights a growing blind spot in enterprise security: employees with legitimate access using collaboration tools to move sensitive information outside the organization. Files sent via Slack or other SaaS apps, especially during employee offboarding, can expose proprietary IP long before security teams detect any anomalies. At Nightfall AI, we tackle this challenge with: Comprehensive monitoring across SaaS apps, endpoints, email, browsers, and AI tools. AI-powered classification to identify organizational IP, not just regulated data. Data lineage to trace files from origin to external sharing. The lesson from Palantir is clear: if you can’t see how your data moves, you’re vulnerable. No matter the company size. Read more: https://lnkd.in/gbYuJS3j

A new generation of AI-powered browsers, like OpenAI’s Atlas and Perplexity’s Comet, are changing the threat landscape. They remember everything. Sync everywhere. And operate far beyond your DLP’s visibility. Employees are unknowingly creating permanent backdoors to your most sensitive data, from source code to financial projections. Traditional DLPs were never built to see it. Our latest blog breaks down: How AI browsers act as autonomous data agents. The five hidden exfiltration vectors your DLP misses. How Nightfall AI prevents AI browser data leaks before they happen. If you’re not protecting against AI browser exfiltration, you’re already exposed. Read the full analysis: https://lnkd.in/g2SPSz2k

Security leaders are rethinking DLP as operational costs and reliability issues erode trust in legacy solutions. Our latest guide From Cyberhaven to Nightfall: A Practical Migration Blueprint for Modern DLP highlights recurring failures in detection accuracy, system reliability, and scalability that leave organizations exposed, and provides a 30-day plan for migrating DLP from Cyberhaven to Nightfall AI. See why organizations are shifting from reactive monitoring to intelligent prevention: https://lnkd.in/gz5NjMcp

Using Code42 but still experiencing alert overload and missed threats? Common signs you need to modernize include: Alerts focused on metadata rather than actual content Browser-only blocking or limited SaaS coverage Manual policy management and remediation Migrating to Nightfall AI brings AI-native content scanning, real-time enforcement, and streamlined policies that reduce false positives while improving detection coverage. Our latest blog, From Legacy to AI-Native: Your Complete Guide to Migrating from Code42 to Nightfall, lays out exactly how to evaluate, plan, and execute this migration. Read the full migration roadmap: https://lnkd.in/g5ZPEB7p

Pomelo, one of LATAM’s fastest-growing payment processors, faced a challenge familiar to every scaling fintech: how to enable innovation and AI adoption without risking sensitive payment data or PCI compliance. Their legacy DLP tools couldn’t see data before it reached AI platforms. Or stop it from leaving endpoints. That changed with Nightfall AI's AI-native DLP. Now Pomelo protects: 300+ employees across LATAM 8 enterprise applications AI tools by detecting sensitive data before it’s submitted The results: <5% false positives, with real alerts, not noise Full data lineage for compliance and investigations Self-service remediation that empowers users and lightens the security load "Nightfall works really well across different integrations. It offers a lot of possibilities for customizing detections, which is very helpful for us. I'm impressed with Nightfall's functionality and the wide range of use cases it covers,” says Ezequiel Virun, Pomelo Cybersecurity Technical Manager. Read how Pomelo is securing payments with Nightfall: https://lnkd.in/gczHBa3v

Security Teams Are Hitting a Wall with Code42. Here’s Why. With Mimecast’s acquisition of Code42, many security leaders are realizing what their teams already knew: tuning can’t fix fundamental detection blind spots. From broken blocking to missing coverage in Slack, Jira, and AI tools, Code42’s limitations are leaving real gaps that threat actors exploit daily. Our latest guide From Legacy to AI-Native: Your Complete Guide to Migrating from Code42 to Nightfall breaks down: The critical blind spots in Code42’s insider risk platform Why manual watchlists and browser-only blocking can’t scale How AI-native DLP from Nightfall AI delivers real detection, real blocking, and universal coverage A 30-day migration plan with proven results, including a 90% reduction in alert noise and faster investigations powered by AI Read the full migration guide to see what Code42 misses, and how Nightfall customers are already catching it. Read now: https://lnkd.in/g5ZPEB7p

Tuesday win wire: A Top 10 Bank just joined Nightfall! Why Now: They are implementing Nightfall to proactively address compliance risks by detecting and remediating sensitive data in Jira. They need a solution that can scan historical data, handle exposure in real-time, and manage violations of different criticality without leading to noise. How Nightfall solved it: Nightfall provides a flexible platform that allows them to configure granular monitoring policies with different remediation actions. The solution offers both automated and end-user remediation and historical scanning capabilities. Competitive Landscape:  In a head-to-head eval, Nightfall's approach to detection was deemed more sophisticated than alternatives like BigID. Nightfall's models use contextual information to reduce false positives, which contrasts with a regex-only approach that often results in noisy and inaccurate findings.