Mage Data has unveiled a new feature within its data protection platform tailored to enhance the security of sensitive information throughout the lifecycle of artificial intelligence applications. Dubbed Data Security and Privacy for AI, this extension is designed to cover various AI environments, including AI training, public generative-AI applications, custom AI agents, and embedded copilots. The platform aims to enforce data protection policies from the point of data entry into an AI system, continuing through processing and development, to the final AI-generated output.
Applying traditional enterprise data controls to AI contexts has been a challenge, as sensitive information often traverses through extracts, notebooks, feature stores, evaluation datasets, and AI-generated responses. Mage Data’s new offering seeks to address this issue by providing comprehensive protection across five key areas. Training Data Guardrails help identify sensitive data types—such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI)—within both structured and unstructured datasets. The platform allows organizations to mask data at the source, safeguard it as it enters AI pipelines, or apply controls using software development kits.
For AI usage, Guardrails scrutinize employee prompts and uploads to public generative-AI services, masking sensitive information before it leaves the user’s device. Dynamic Data Masking for AI can adjust AI-generated responses by masking, redacting, generalizing, or blocking content based on user profiles and requests. Additionally, AI Development Guardrails offer organizations developing their own AI agents a means of controlling tool and data access according to user permissions, facilitated by Mage Data’s SDKs and MCP Server.
Mage Data places a strong emphasis on monitoring AI interactions. The platform’s Activity Monitoring for AI feature documents user interactions, prompts, tools, and sensitive data masking activities, while offering reporting and alerting functionalities. The company enables organizations to extend their existing Mage Data policies to AI workloads, thus avoiding the complexity of maintaining separate policy frameworks specifically for AI.
Highlighting the significance of data protection in AI, Mage Data CEO Rajesh Parthasarathy emphasizes the company’s strategy of applying conventional data protection principles to AI environments. CTO and Senior Vice President Anil Bhat adds that their approach safeguards data without necessitating a total block on AI tools, which might otherwise prompt employees to resort to unmanaged services. The Data Security and Privacy for AI is currently available, with Mage Data offering demonstrations and proof-of-concept deployments for interested organizations.
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