Mage Data has unveiled a new extension to its data protection platform, aimed at safeguarding sensitive information throughout the lifecycle of artificial intelligence (AI). The offering, named Data Security and Privacy for AI, is designed to ensure the security of data within AI training environments, public generative-AI applications, custom AI agents, and embedded copilots. This platform facilitates the implementation of data protection policies at every stage—before data enters an AI system, during its processing and development, and when the AI generates a response.
In the evolving landscape of AI, applying conventional enterprise data controls presents challenges, particularly as sensitive information traverses through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated outputs. Mage Data’s new solution addresses this by providing a suite of five key protection areas. Training Data Guardrails detect and manage sensitive data, including personally identifiable information (PII), protected health information (PHI), and non-public information (NPI), across both structured and unstructured datasets. The system enables data masking at its source, protection during its entry into AI pipelines, and control application via software development kits.
The platform also introduces AI Usage Guardrails, which scrutinize employee prompts and file uploads to public generative-AI services to ensure sensitive information is masked before it leaves the user’s device. Additionally, Dynamic Data Masking for AI offers capabilities to mask, redact, generalize, or block AI-generated responses based on user specifics, request details, and the nature of the information involved. For organizations developing their own AI agents, AI Development Guardrails provide essential controls, leveraging Mage Data’s SDKs and MCP Server to restrict tools and data access according to user permissions.
Moreover, the platform includes Activity Monitoring for AI to record and report AI interactions, offering insights into users, prompts, tools, sensitive data handling, and policy outcomes. This feature enhances the monitoring capabilities with alerting functions. Mage Data emphasizes the extension of existing data protection policies to AI workloads, avoiding the need for a separate framework specifically for AI. According to CEO and founder Rajesh Parthasarathy, the focus is on applying established data protection principles to the increasing number of environments where enterprise information engages with AI systems.
Highlighting the potential risks associated with employees using public AI tools, the company’s CTO and Senior Vice President Anil Bhat points out that their approach is to protect data without necessitating a complete block on AI tools, which might otherwise push employees towards unmanaged services. Data Security and Privacy for AI is currently available, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in evaluating the technology.
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