Enterprise Data Security Use Cases

Ensure Safe AI Adoption, Compliance, and Effective Controls
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AI adoption is driving enterprise data security to fundamentally change. Sensitive data now flows freely across cloud, SaaS, collaboration platforms, data lakes, and AI systems, far beyond the reach of perimeter-based and point-in-time controls.  Security leaders must shift from static defenses to continuous, automated data discovery, classification, compliance and risk reduction at massive scale.

AI Data Readiness

Adopt copilots and AI agents with confidence by tightly governing what data they can see, how they use it, and where it can flow.
Continuous discovery and classification of sensitive data across AI pipelines
Minimizing sensitive data exposure in copilots and agents
Mapping AI-accessible datasets and monitoring for data leakage

Continuous Data Privacy 
and Compliance

Turn privacy and compliance into always-on risk reduction instead of painful, point-in-time audits.
Real time inventory of regulated data and violation detection
Enforcing least-privilege access and reducing data sprawl
Producing audit-ready evidence without manual effort

Data Loss Prevention 
That Works

Make DLP finally work by grounding every policy in accurate, unified data intelligence.
High-confidence, automated data classification
Consistent labeling and policy enforcement across environments
Integration with cloud, SaaS, and endpoint controls

Prevent Sensitive 
Data Exposure

Shrink your breach blast radius by finding and fixing real sensitive-data exposures across cloud, SaaS, and AI.
Misconfigured cloud storage and overshared SaaS workspaces
Sensitive data drifting into development or analytics environments
Uncontrolled access by third parties, contractors, and AI tools