Mage Data has launched a new extension to its data protection platform, named Data Security and Privacy for AI, aimed at safeguarding sensitive information throughout the artificial intelligence lifecycle. This innovative feature set is crafted to secure data across various AI environments, including training platforms, public generative-AI applications, custom AI agents, and embedded copilots. The platform facilitates the implementation of data protection policies at every stage—before data enters an AI system, during its processing and development, and when an AI system generates a response.
Traditional data protection measures within enterprises often struggle to adapt to AI environments due to the complex nature of data flow through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses. Mage Data’s new offering addresses this challenge by introducing five key areas of protection. The Training Data Guardrails component identifies and safeguards sensitive data such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) across various datasets. Organizations can apply data masking at the source or through AI pipelines, utilizing software development kits to maintain security.
The platform also features AI Usage Guardrails, which inspect user prompts and file uploads to public generative-AI services, ensuring sensitive data is masked before leaving the user’s device. Additionally, Dynamic Data Masking for AI can alter AI-generated responses by masking, redacting, generalizing, or blocking information based on the user and request context. For organizations developing their own AI agents, AI Development Guardrails offer controls to restrict tool and data access according to user permissions, facilitated by Mage Data’s SDKs and MCP Server.
Furthermore, Activity Monitoring for AI allows for comprehensive recording of AI interactions including user prompts, tools, sensitive data masking, and policy outcomes, while also providing alerting and reporting capabilities. Mage Data emphasizes the possibility of extending existing data policies to AI workloads, avoiding the need for a separate AI-specific framework. CEO and founder Rajesh Parthasarathy highlights the company’s dedication to applying traditional data protection principles to the diverse environments where enterprise data engages with AI systems.
The company also underscores the risks associated with employees using public AI tools when handling sensitive information. CTO and Senior Vice President Anil Bhat notes that their approach aims to protect data without forcing enterprises to entirely block AI tools, which could inadvertently lead employees to resort to 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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