Fewer False Positives
Context-aware rules and thresholds reduce noise and alert fatigue.
Classic DLP fails when it treats every file the same or fires on every keyword. Real protection starts with knowing which data matters, where it flows, and who should use it. We align policies to your crown-jewel datasets (customer, financial, health, IP/source code) and the channels they actually move through—email, SaaS, collaboration suites, cloud storage, endpoints, and developer tooling—so controls stop real loss, not daily collaboration.
We tune for context and intent: labels and patterns that reflect your data model, thresholds that ignore benign traffic, coaching pages that teach the right next step, and exception paths that are time-boxed and auditable. Results are measurable—fewer false positives, fewer “workarounds,” and clear evidence that sensitive data isn’t walking out through email, shadow SaaS, or copy-paste into AI tools.
Context-aware rules and thresholds reduce noise and alert fatigue.
Targeted controls for PII/PHI, contracts, financials, and source code across email, SaaS, storage, and endpoints.
Policies that prevent sensitive data from being pasted into unapproved AI tools.
Coaching and smart exceptions keep work moving while risk drops.
Incidents arrive with context, severity, and next steps—no detective work required.
Reusable evidence shows policies enforced and exceptions managed.