Mage Data has launched a new extension to its data protection platform, called Data Security and Privacy for AI, aimed at securing sensitive information throughout the artificial intelligence lifecycle. This innovative solution is tailored for AI training environments, public generative-AI applications, custom AI agents, and embedded copilots. The platform ensures that data protection policies are applied before data enters an AI system, during its processing and development, and when an AI system generates responses.
The company acknowledges the challenges of applying traditional enterprise data controls to AI environments, given that sensitive information often moves through various extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses. To address this, Mage Data’s new offering focuses on five primary areas of protection. These include Training Data Guardrails, which identify and mask sensitive information such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) directly at its source or as it enters AI pipelines. Additionally, AI Usage Guardrails inspect and mask employee prompts and file uploads to public generative-AI services before they leave the user’s device.
Dynamic Data Masking for AI is another feature that allows masking, redacting, generalizing, or blocking AI-generated responses based on the user, request, and contained information. AI Development Guardrails provide organizations with controls for developing their AI agents, utilizing Mage Data’s SDKs and MCP Server to limit tool and data access according to user permissions. Furthermore, Activity Monitoring for AI records interactions, including users, prompts, tools, and sensitive data masking, while offering reporting and alerting functionalities.
Mage Data emphasizes that its approach allows organizations to extend existing data protection principles to AI environments, rather than creating separate policy frameworks for AI. CEO and founder Rajesh Parthasarathy highlighted the importance of this integration, especially as enterprise information increasingly interacts with AI systems. The company also pointed out the risks associated with employees using public AI tools with sensitive data. According to Anil Bhat, CTO and Senior Vice President, Mage Data aims to protect data without forcing enterprises to completely block AI tools, which could inadvertently result in employees resorting to unmanaged services.
Data Security and Privacy for AI is currently available, and Mage Data is offering demonstrations and proof-of-concept deployments for organizations interested in evaluating this technology. The company’s approach seeks to balance the need for robust data protection with the flexibility required for AI tool utilization in enterprises.
Legal Disclaimer:
The information contained in this article has been provided by independent third-party contributors, clients, or content partners. We do not independently verify the accuracy, completeness, legality, ownership, licensing, or reliability of submitted content, including text, images, videos, trademarks, or other media materials. The submitting party is solely responsible for ensuring that all content, including images and media assets, complies with applicable copyright, trademark, licensing, and intellectual property laws. We disclaim liability for any unauthorized use of copyrighted or proprietary materials by third parties. If you believe that any content published on this platform infringes your intellectual property rights, kindly contact the author above for prompt review and resolution.