Mage Data has unveiled a new extension to its data protection platform, specifically aimed at enhancing security and privacy throughout the artificial intelligence lifecycle. This new feature, Data Security and Privacy for AI, is crafted to safeguard sensitive information as it moves through various AI environments. It encompasses AI training setups, public generative-AI applications, custom AI agents, and integrated copilots. The platform’s design ensures that data protection policies are enforced before data enters AI systems, during its processing and development, and even when AI systems generate responses.
The challenge of applying conventional data controls to AI environments, where sensitive information can traverse extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses, is addressed by Mage Data’s latest offering. The solution introduces five key areas of protection. Training Data Guardrails help identify and protect sensitive data like personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) across both structured and unstructured datasets. Organizations can mask data at the source, protect it upon entry into AI pipelines, or enforce controls through software development kits.
AI Usage Guardrails are designed to scrutinize employee prompts and file uploads to public generative-AI services, ensuring sensitive information is masked before leaving the user’s device. The Dynamic Data Masking feature enables the masking, redacting, generalizing, or blocking of AI-generated responses based on user requests and the content of the responses. AI Development Guardrails provide necessary controls for companies developing their own AI agents, with Mage Data’s SDKs and MCP Server limiting tool and data access per user permissions. Additionally, Activity Monitoring for AI records interactions, including user details, prompts, and policy outcomes, while offering reporting and alerting capabilities.
Rather than requiring separate policy frameworks for AI, Mage Data allows organizations to extend existing policies to cover AI workloads. CEO and founder Rajesh Parthasarathy emphasized the company’s focus on applying established data protection principles to the growing array of environments where enterprise data interacts with AI systems. The company also addressed the risks associated with employees using public AI tools, which may involve sensitive information. CTO and Senior Vice President Anil Bhat noted that their approach aims to protect data without forcing companies to entirely block AI tools, which could otherwise push employees toward 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. This initiative underscores Mage Data’s commitment to providing robust data protection solutions tailored to the evolving demands of AI environments.
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