Mage Data has unveiled a new extension to its data protection platform called Data Security and Privacy for AI, aimed at safeguarding sensitive information throughout the lifecycle of artificial intelligence applications. These enhancements are designed to offer comprehensive protection across various AI environments, including training systems, public generative-AI applications, custom-built AI agents, and embedded copilots. The platform’s functionality ensures that data protection measures are applied not only before sensitive information enters an AI system but also during its processing and development, and when the AI system generates a response.
The introduction of these capabilities addresses the challenges faced by enterprises in applying conventional data controls within AI environments, where sensitive information often traverses through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated outputs. Mage Data’s new offering provides five key protective measures: Training Data Guardrails, which detect sensitive data like personally identifiable information (PII) and protected health information (PHI) across various datasets; AI Usage Guardrails, which scrutinize employee interactions with public generative-AI services to prevent sensitive data exposure; Dynamic Data Masking for AI, which can modify AI-generated responses; AI Development Guardrails, which limit access to tools and data for organizations building their own AI agents; and Activity Monitoring for AI, which logs AI interactions and offers reporting and alerting features.
According to Mage Data, organizations can seamlessly extend their existing data protection policies to AI workloads, eliminating the need for separate frameworks specifically tailored to artificial intelligence. Rajesh Parthasarathy, CEO and founder of Mage Data, emphasized that the company’s strategy is rooted in applying established data protection principles to the numerous environments where enterprise data intersects with AI systems. Additionally, the risks associated with employees using public AI tools for handling sensitive information were underscored by Anil Bhat, CTO and Senior Vice President. Bhat noted that the company’s methodology aims to secure data without forcing businesses to block AI tools entirely, which could inadvertently lead to the use of unregulated services by employees.
Data Security and Privacy for AI is now available to enterprises, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in evaluating the new technology. This solution aims to provide a robust framework for protecting sensitive data across the diverse and expanding landscape of AI applications, ensuring that enterprises can safely harness the power of AI without compromising their data security protocols.
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