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AI Glossary

Data Loss Prevention (DLP)

Technologies and practices that detect and prevent unauthorized transmission of sensitive data.

TL;DR

  • —Technologies and practices that detect and prevent unauthorized transmission of sensitive data.
  • —Understanding Data Loss Prevention (DLP) is critical for effective AI for companies.
  • —Remova helps companies implement this technology safely.

In Depth

DLP for AI involves scanning all interactions between users and AI models for sensitive data patterns. This includes detecting PII, financial data, API keys, passwords, source code, and proprietary information. When sensitive data is detected, DLP systems can block the transmission, redact the sensitive portions, or alert security teams.

Related Terms

PII Redaction

The automatic detection and removal of personally identifiable information from text before it reaches AI models.

AI Guardrails

Safety mechanisms that constrain AI system behavior to prevent harmful, biased, or off-policy outputs.

Content Safety

Mechanisms ensuring AI-generated content is appropriate, accurate, and aligned with organizational standards.

AI Safety Layer

A middleware component that sits between users and AI models to enforce safety policies and controls.

Knowledge Hub

Glossary FAQs

Data Loss Prevention (DLP) is a fundamental concept in the AI for companies landscape because it directly impacts how organizations manage technologies and practices that detect and prevent unauthorized transmission of sensitive data.. Understanding this is crucial for maintaining AI security and compliance.
Remova's platform is built to natively manage and optimize Data Loss Prevention (DLP) through our integrated governance layer, ensuring that your organization benefits from this technology while mitigating its inherent risks.
You can explore our full AI for companies glossary, which includes detailed definitions for related concepts like PII Redaction and AI Guardrails.

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