Mage Data has introduced a new extension to its data protection platform, specifically targeting the security of sensitive information throughout the artificial intelligence lifecycle. This offering, named Data Security and Privacy for AI, is designed to safeguard data across various AI environments, including training environments, public generative-AI applications, custom AI agents, and embedded copilots. The platform aims to enforce data protection measures from the moment data enters an AI system, through its processing and development stages, up until the AI generates a response.
The company has highlighted the challenges that conventional enterprise data controls face in AI settings, where sensitive information can traverse through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses. To address these challenges, Mage Data’s new solution offers five key areas of protection. These include Training Data Guardrails that detect sensitive information like personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) in datasets. Enterprises can implement data masking at its source, protect data as it integrates into AI pipelines, or apply controls via software development kits.
Additional features include AI Usage Guardrails that monitor employee prompts and file uploads to public generative-AI services, ensuring sensitive information is masked before leaving a user’s device. Dynamic Data Masking for AI offers the ability to obscure, redact, generalize, or block AI-generated responses tailored to the user, request, and response content. Furthermore, AI Development Guardrails provide governance for organizations developing their own AI agents, with Mage Data’s SDKs and MCP Server restricting access to tools and data based on user permissions.
The platform also features Activity Monitoring for AI, which records interactions, including user prompts, tools used, data masking actions, and policy outcomes, while offering reporting and alerting capabilities. Mage Data emphasizes that existing data protection policies can be extended to AI workloads, eliminating the need for a separate policy framework for artificial intelligence. CEO and founder Rajesh Parthasarathy noted the company’s commitment to applying well-established data protection principles to the expanding array of environments where enterprise information interacts with AI systems.
Recognizing the risk posed by employees using public AI tools with sensitive data, CTO and Senior Vice President Anil Bhat stated that the company’s approach protects data without necessitating a complete ban on AI tools, which could drive employees towards unmanaged services. Data Security and Privacy for AI is now available, with Mage Data offering demonstrations and proof-of-concept deployments for organizations considering the technology.
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