Mage Data has unveiled a new extension to its data protection platform, named Data Security and Privacy for AI, aiming to enhance the security of sensitive information throughout the artificial intelligence lifecycle. This enhancement is designed to safeguard data in various AI environments, including AI training settings, public generative-AI applications, custom AI agents, and embedded copilots. The platform ensures the application of data protection policies at every stage, from data entry into an AI system to processing, development, and response generation.
Traditional data controls have often struggled to adapt to AI environments, where sensitive information can traverse through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses. Mage Data’s new offering addresses this challenge with five key protection areas. Firstly, Training Data Guardrails detect sensitive information like personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) across datasets, allowing organizations to mask data directly at its source or as it moves through AI pipelines. Secondly, AI Usage Guardrails analyze user prompts and file uploads to public generative-AI services, ensuring that sensitive data is masked before leaving a user’s device.
The platform also features Dynamic Data Masking for AI, which can mask, redact, generalize, or block AI-generated responses depending on the user, request, and response content. For organizations developing their own AI agents, AI Development Guardrails provide control by using Mage Data’s SDKs and MCP Server to limit tools and data access based on user permissions. Additionally, Activity Monitoring for AI records interactions, including users, prompts, tools, sensitive data masking, and policy outcomes, while offering comprehensive reporting and alerts.
Mage Data allows organizations to extend their existing policies to AI workloads, bypassing the need for a separate policy framework for artificial intelligence. CEO and founder Rajesh Parthasarathy emphasized the company’s strategy of applying established data protection principles to the varied environments where enterprise information interacts with AI. Highlighting the risks associated with employees potentially using public AI tools with sensitive information, CTO and Senior Vice President Anil Bhat noted that their approach aims to protect data without completely blocking AI tools, which might otherwise drive employees towards unmanaged services.
The Data Security and Privacy for AI extension is currently available, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in evaluating this technology.
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