Mage Data has unveiled its latest innovation, Data Security and Privacy for AI, expanding its existing data protection platform to address the needs of enterprises managing sensitive information across the artificial intelligence lifecycle. This new offering ensures data security at various stages, including AI training environments, public generative-AI applications, custom AI agents, and embedded copilots. The platform applies stringent data protection measures before data enters AI systems, during processing, and at the point of AI response generation.
Traditional enterprise data controls often struggle in AI environments due to the fluid movement of sensitive information through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated outputs. Mage Data’s solution targets this challenge with five core protective features. The Training Data Guardrails can pinpoint sensitive data such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) within structured and unstructured datasets, offering options to mask data at its source or integrate controls via software development kits.
The AI Usage Guardrails scrutinize employee interactions with public generative-AI services, ensuring that sensitive information is masked before leaving a user’s device. Furthermore, the Dynamic Data Masking for AI function allows for the masking, redaction, generalization, or blocking of AI-generated responses tailored to the user, request, and content. For organizations creating their own AI agents, AI Development Guardrails offer control over tools and data access, governed by user permissions through Mage Data’s SDKs and MCP Server.
Additionally, the platform includes Activity Monitoring for AI, which logs AI interactions such as user prompts, tool usage, and data masking activities, while also providing comprehensive reporting and alerting capabilities. This system allows organizations to extend their existing Mage Data policies to AI workloads, eliminating the need for a separate policy framework for AI-specific environments. Rajesh Parthasarathy, CEO and founder of Mage Data, emphasized the company’s dedication to applying established data protection principles across evolving AI interfaces where enterprise data is utilized.
Highlighting the potential risks of employees handling sensitive information via public AI tools, Mage Data’s CTO and Senior Vice President Anil Bhat pointed out the platform’s emphasis on safeguarding data without restricting AI tool usage entirely—preventing employees from resorting to unsupervised services. The Data Security and Privacy for AI platform is now accessible, with Mage Data offering demonstrations and proof-of-concept deployments for organizations interested in assessing this technology.
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