In a move to bolster data protection in the realm of artificial intelligence, Mage Data has unveiled its new extension called Data Security and Privacy for AI. This enhancement to their existing data protection platform aims to secure sensitive enterprise information throughout the AI lifecycle. The extension is designed to safeguard data in various AI contexts, including training environments, public generative-AI applications, custom AI agents, and embedded copilots. By applying data protection measures before, during, and after AI processes, the platform addresses the challenges of traditional enterprise data controls in AI settings.
Mage Data’s latest offering focuses on five key protective measures. Training Data Guardrails are utilized to detect sensitive data like personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) in both structured and unstructured datasets. This allows organizations to mask data at its origin or as it enters AI pipelines. AI Usage Guardrails oversee employee prompts and file uploads to public generative-AI services, ensuring sensitive information is masked before leaving the user’s device. Furthermore, Dynamic Data Masking for AI can alter AI-generated responses by masking, redacting, generalizing, or blocking them based on the user’s role and request specifics.
The platform also includes AI Development Guardrails, which impose control over the development of AI agents. This is achieved through Mage Data’s SDKs and MCP Server, which restrict tool and data access according to user permissions. Additionally, the Activity Monitoring for AI feature logs AI interactions, documenting users, prompts, and sensitive data handling, while also offering reporting and alerting functionalities. These comprehensive features enable organizations to extend existing data protection policies to AI applications without the need for a distinct policy framework dedicated solely to artificial intelligence.
Rajesh Parthasarathy, CEO and founder of Mage Data, emphasized the company’s commitment to applying established data protection principles to the diverse environments where enterprise data interacts with AI systems. The company also pointed out the potential risks associated with employees using public AI tools with sensitive information. Anil Bhat, CTO and Senior Vice President of Mage Data, remarked that their approach aims to shield data without completely prohibiting AI tools, which could otherwise push employees to resort to unmanaged services.
Available now, Data Security and Privacy for AI offers organizations a chance to explore its capabilities through demonstrations and proof-of-concept deployments. This new extension reflects Mage Data’s proactive stance on securing data in an era where AI continues to permeate various facets of enterprise operations.
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