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Use Case

Ensure Secure and Responsible AI

Data governance can't keep pace with AI innovation.

Unstructured data holds your most sensitive information and is your biggest risk. Documents, design files, screenshots, voice, video, source code, emails, etc. live in dark corners across your entire data estate.

Sensitive data in model training sets creates privacy and compliance exposure

AI/ML data usage and lineage lack visibility, and oversight

Shadow AI projects bypass governance and auditability

AI agents may expose sensitive data or violate privacy regulations (e.g., GDPR and PCI-DSS)

Responsible AI starts with knowing and securing the data it depends on.

Discover and classify sensitive data across AI/ML and LLM pipelines

Monitor prompts, outputs, and AI agent activity for data leakage

Enforce identity-based access controls across AI-driven workflows

Align AI data usage with NIST AI RMF, ISO 42001, and privacy regulations

Sentra secures the data that powers your AI

Gain visibility into everywhere sensitive data exists, within unstructured assets and files — and insight into its business purpose.

Sensitive data discovery for GenAI and LLMs

Automatically identify and classify sensitive data—like PII, PHI, and proprietary information—to ensure training datasets are clean, compliant, and free of privacy risks before being used by AI models.

Lineage, governance, and risk posture management

Sentra treats LLMs as part of the data attack surface. It maps data lineage, applies posture management, and enforces access governance to help teams reduce risk as they develop and deploy GenAI applications.

Monitoring GenAI prompts and AI agents to prevent leakage

Sentra DDR monitors GenAI prompts, outputs, and AI agent activity for signs of sensitive data exposure. It provides near real-time visibility and enforces identity-based controls to prevent unauthorized access and ensure secure, compliant AI interactions.

AI policy enforcement and framework alignment

Sentra automates enforcement of encryption, anonymization, and residency policies while aligning with frameworks like NIST AI RMF and ISO/IEC 42001. It ensures consistent compliance and ethical AI practices across your cloud-native environments.

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