Mage Data has rolled out 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 for enterprises. This new offering encompasses AI training environments, public generative-AI applications, custom AI agents, and embedded copilots. It is crafted to implement data protection policies at multiple stages: before data enters an AI system, during its processing and development, and at the point when an AI system generates a response.
The company acknowledges the challenge enterprises face in applying traditional data controls to AI environments, where sensitive information can traverse through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated responses. To address these challenges, Mage Data’s solution incorporates five key areas of protection. Training Data Guardrails are designed to identify sensitive information, such as personally identifiable information (PII), protected health information (PHI), and non-public information (NPI), within structured and unstructured datasets. This allows organizations to mask data at its source, secure information as it enters AI pipelines, or apply controls using software development kits.
Additionally, AI Usage Guardrails inspect employee prompts and file uploads to public generative-AI services, with the capability to mask sensitive information before it leaves a user’s device. Dynamic Data Masking for AI can modify AI-generated responses by masking, redacting, generalizing, or blocking them based on user requests and the information contained in the response. For organizations developing their own AI agents, AI Development Guardrails provide essential controls, with Mage Data’s SDKs and MCP Server offering the ability to limit tools and data access according to end-user permissions.
Another component, Activity Monitoring for AI, records AI interactions, including details about users, prompts, tools, sensitive data masking, overrides, and policy outcomes, while providing robust reporting and alerting functionalities. Mage Data assures that organizations can extend their existing data protection policies to AI workloads without needing to create a separate policy framework specifically for AI. CEO and founder Rajesh Parthasarathy emphasized the company’s strategy of applying well-established data protection principles to the expanding environments where enterprise information interacts with AI systems.
Highlighting the risk of employees using public AI tools with sensitive data, Mage Data CTO and Senior Vice President Anil Bhat noted the company’s approach is geared toward safeguarding data without restricting the use of AI tools entirely, which might otherwise drive employees to use unmanaged services. The new 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 further.
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