Short pieces for regulated teams evaluating privacy controls for generative AI.
The next breach will not begin with a dramatic intrusion. It will begin with a well-meaning employee pasting a client file, an access token, or a patient note into a generative AI window. Browser-resident AI privacy controls close that gap at the point of use, before sensitive data leaves the endpoint.
Read CompliancePrivacy policies often say the right thing: do not share personal information, payment data, secrets, or regulated records with unauthorized AI systems. The operational problem is that employees work faster than policies can be reread.
Read Security ArchitectureRedaction is blunt. It removes risk by removing meaning. Pseudonymization is more disciplined: it substitutes sensitive identifiers with realistic synthetic values so the AI system can still reason about roles, formats, relationships, and workflow context.
Read DLP StrategyThe most effective prompt DLP programs start with the data attackers prize and regulators scrutinize: credentials, financial identifiers, personal information, infrastructure details, and confidential business terms.
Read OperationsEnterprise AI security succeeds when the control reaches the place where employees actually work. For many organizations, that place is the managed browser.
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Context Security