iboss Announces AI DLP to Stop Sensitive Data Loss Across Every Destination

AI DLP reads content in real time with AI/ML, without relying on data labels, to detect, flag and block sensitive data that legacy regex, pattern matching and labels miss, wherever the data is going: AI platforms and tools, cloud apps and every other cloud destination. AI DLP is available in private preview in December 2026.

ORLANDO, Fla., Nov. 3, 2026 /PRNewswire/ -- iboss today announced AI DLP, data loss prevention that reads content in real time with AI/ML, without relying on data labels, to detect, flag and block sensitive data on its way to any destination, from AI platforms and tools to cloud apps and every other cloud service. Legacy DLP depends on regex, pattern matching and data labels, which find only data that fits a pattern written in advance or carries the right label; AI DLP inspects the content itself and catches the sensitive data those approaches miss. iboss will show AI DLP in a live demo webinar on Thursday, November 5, 2026, at 12:00 PM ET, and AI DLP is available in private preview in December 2026.

Sensitive data leaves through a file shared to a cloud drive, a form posted to a web app, or source code pasted into AI tools. Much of it has no fixed format, so rules looking for an account number or ID string let it pass. DLP that depends on data labels has a second gap: a file that is mislabeled or never labeled falls outside the policy, and it leaks.

In AI DLP, AI/ML classification and deep content inspection read what the data contains as it moves. File analysis and OCR read documents and the text inside images, and classification finds sensitive data whether it is labeled, mislabeled or not labeled at all. Where Microsoft Information Protection labels exist, AI DLP also reads and enforces them inline.

Policies set by user, group and department detect, flag or block source code, customer data, PII and intellectual property in real time, with a full audit trail. The same policies cover AI platforms and tools, so teams can keep sensitive data out of AI without banning the tools. They also apply when AI agents move the data, with control over which AI services, tools and APIs agents may use, and agent activity is retained.

AI DLP adds data-loss risk scoring and one-click GDPR, HIPAA, PCI-DSS and SOX reports that give auditors evidence of what was found and stopped.

AI DLP runs on the iboss containerized architecture. Each customer's traffic is processed in dedicated containers with isolated SSL keys and dedicated IPs, and customer data is never co-mingled. It works alongside the iboss Secure Web Gateway, CASB, GenAI Protection and Zero Trust Network Access, with one console, one policy engine and one data lake.

"Data labels are a challenge for DLP. Files get mislabeled, and data that is never labeled leaks," said Paul Martini, CEO and Co-Founder of iboss. "AI DLP reads the content itself in real time, without relying on labels, wherever it is headed. We can solve that problem and plug that hole immediately."

Availability

AI DLP is available in private preview in December 2026. The live demo webinar, Live Demo: AI DLP That Stops Data Loss in Real Time, is on Thursday, November 5, 2026, at 12:00 PM ET, and registration is open at https://www.brighttalk.com/webcast/17589/677893. Learn more at www.iboss.com/data-security (https://www.iboss.com/data-security).

About iboss

iboss is a unified AI and data security platform that helps organizations secure AI, protect sensitive data, and discover and control applications. Built on a containerized Zero Trust architecture, iboss is trusted by global enterprises and government agencies. Learn more at www.iboss.com (https://www.iboss.com).

SOURCE iboss