Mage Data has unveiled a new extension to its data protection platform, specifically aimed at enhancing data security and privacy throughout the artificial intelligence lifecycle. This latest offering, known as Data Security and Privacy for AI, is designed to safeguard sensitive information across various AI environments, including AI training setups, public generative-AI applications, custom AI agents, and embedded copilots. The platform ensures that data protection policies are enforced before data enters AI systems, during processing and development, and when AI systems generate responses.
The company acknowledges that traditional enterprise data controls often fall short in AI contexts, where sensitive data can traverse through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated outputs. To address these challenges, Mage Data’s new solution incorporates five key protective measures. Training Data Guardrails identify and manage sensitive data such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) within structured and unstructured datasets, allowing organizations to mask data at the source or apply controls as it moves through AI pipelines.
AI Usage Guardrails are designed to inspect employee prompts and file uploads to public generative-AI services, masking sensitive information before it leaves the user’s device. Additionally, Dynamic Data Masking for AI can redact, generalize, or block AI-generated responses based on user requests and the sensitivity of the information. For organizations developing their own AI agents, AI Development Guardrails provide control mechanisms via Mage Data’s SDKs and MCP Server, which restrict tool and data access according to user permissions. Furthermore, the platform’s Activity Monitoring for AI tracks interactions involving users, prompts, tools, and sensitive data masking, while offering reporting and alerting functions.
By extending existing Mage Data policies to AI workloads, the company aims to streamline data protection without necessitating separate frameworks specifically for AI. CEO and founder Rajesh Parthasarathy highlighted the focus on applying established data protection principles in the expanding realm of enterprise AI interactions. This approach helps manage the risk of employees inadvertently exposing sensitive information through public AI tools, a concern echoed by CTO and Senior Vice President Anil Bhat. He emphasized that the platform allows data protection without forcing enterprises to block AI tools entirely, which could otherwise drive employees to use unmanaged services.
Data Security and Privacy for AI is now available, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in evaluating the technology. The company’s approach seeks to provide robust data security solutions that integrate seamlessly into existing enterprise frameworks, ensuring comprehensive protection as AI technologies continue to evolve.
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