Mage Data has launched a new extension to its data protection platform, aimed at bolstering data security and privacy throughout the artificial intelligence lifecycle. This enhancement, known as Data Security and Privacy for AI, is designed to protect sensitive information across various AI environments including training arenas, public generative-AI applications, custom AI agents, and embedded copilots. The platform ensures data protection policies are applied before data enters AI systems, during processing, and in the production of AI responses.
The introduction of this tool comes amid challenges faced by enterprises in applying traditional data controls to AI operations, where sensitive data can traverse through extracts, notebooks, feature stores, evaluation datasets, prompts, and AI-generated outcomes. Mage Data addresses these complexities with five main protection areas. Training Data Guardrails, for instance, help organizations identify and safeguard sensitive information like personally identifiable information (PII), protected health information (PHI), and non-public information (NPI) across both structured and unstructured data sets. Furthermore, AI Usage Guardrails can examine employee prompts and file uploads to public AI services, ensuring sensitive data is masked before it leaves the user’s device.
The platform also introduces Dynamic Data Masking for AI, which can alter AI-generated responses by masking, redacting, generalizing, or blocking content based on user requests and response details. Additionally, AI Development Guardrails are in place to offer controls for organizations developing their AI agents, utilizing Mage Data’s SDKs and MCP Server to manage tool and data access according to user permissions. Complementing these features, Activity Monitoring for AI tracks interactions involving users, prompts, and sensitive data masking, offering comprehensive reporting and alerting capabilities.
Mage Data emphasizes that organizations can seamlessly extend their existing data protection policies to AI workloads without needing to establish a separate framework. The company’s CEO and founder, Rajesh Parthasarathy, asserts that their approach integrates established data protection principles with the expanding environments where enterprise information intersects with AI systems. Highlighting the risks posed by employees using public AI tools, CTO and Senior Vice President Anil Bhat notes that their solution aims to safeguard data while allowing enterprises to avoid completely blocking AI tools, which might push employees towards using 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. This initiative underscores Mage Data’s commitment to providing secure and efficient data protection solutions in the evolving landscape of artificial intelligence.
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