Mage Data has unveiled an innovative solution, Data Security and Privacy for AI, broadening its data protection platform to safeguard sensitive information throughout the lifecycle of artificial intelligence. This new extension caters to AI training environments, public generative-AI applications, custom AI agents, and embedded copilots, ensuring data protection policies are enforced before data enters an AI system, during its processing and development, and when the AI generates a response.
Traditional data controls in enterprises often face challenges when applied to AI settings, where sensitive data frequently transitions through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI outputs. Addressing these challenges, Mage Data’s new offering focuses on five principal protection areas. Training Data Guardrails detect sensitive information such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) across varied datasets, enabling organizations to mask data at its origin, shield it as it enters AI pipelines, or impose controls via software development kits.
Additionally, AI Usage Guardrails scrutinize employee prompts and files uploaded to public generative-AI services, masking sensitive data before it exits a user’s device. Dynamic Data Masking for AI can modify AI-generated responses by masking, redacting, generalizing, or blocking content based on user, request, and response information. AI Development Guardrails offer controls for organizations crafting their own AI agents, with Mage Data’s SDKs and MCP Server managing tool and data access according to user permissions. Furthermore, Activity Monitoring for AI logs AI interactions, encompassing users, prompts, tools, data masking efforts, overrides, and policy results, while also providing reporting and alerting functionalities.
Highlighting the importance of integrating existing data protection principles into AI systems, Mage Data’s CEO and founder, Rajesh Parthasarathy, emphasized that organizations can extend their current Mage Data policies to AI workloads without creating a separate framework for artificial intelligence. The company also pointed out the risks posed by employees utilizing public AI tools with sensitive data. According to Mage Data’s CTO and Senior Vice President, Anil Bhat, the company’s strategy aims to protect data without entirely blocking AI tools, a measure that could drive employees to use unregulated services instead.
Data Security and Privacy for AI is already available, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in assessing the technology. For further details, potential users are encouraged to visit Mage Data’s website or contact their media department.
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