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PAIG takes on the challenge of taming generative AI’s unpredictability

PAIG takes on the challenge of taming generative AI’s unpredictability

Privacera, a leading data security and governance company, has announced the private preview of Privacera AI Governance (PAIG). This new offering aims to tackle the privacy and compliance risks associated with the use of generative AI and large language models (LLMs) in enterprise operations and customer engagements. PAIG empowers organizations to effectively manage the entire AI data security lifecycle, from scanning and classifying training data to securing and auditing AI models, model outputs, and user requests.

The increasing use of generative AI and LLMs has the potential to revolutionize various aspects of business operations. However, the presence of personal, private, and confidential information in training data and subsequent models has led to concerns regarding privacy and compliance. Enterprises are now racing to implement proper security and access controls to mitigate these risks.

PAIG addresses these challenges by providing native enforcement of security and privacy controls across diverse data estates and architectures. Built on open standards, Privacera’s innovative solution helps companies reduce sensitive data exposure, enhance privacy and ethics, and ensure compliance with regulatory and legal requirements in AI applications.

One key aspect of PAIG is its ability to foster powerful AI data security governance and enable federated stewardship between IT departments and business teams. The solution encompasses comprehensive data security governance for relational and non-structured data, as well as AI model training and access. This ensures that companies can avoid potential data misuse, effectively enforce compliance policies, and simplify complex runtime contexts during inference.

PAIG leverages Privacera’s expertise in building scalable data and access security solutions for AI and diverse data estates. Powered by the company’s Unified Data Security Platform, PAIG offers a common security administration and monitoring platform across all data, with consistent policies, roles, and controls for AI models. The combined solution provides compliance support for major regulations such as CCPA, GDPR, and HIPAA throughout the AI model lifecycle.

Balaji Ganesan, co-founder and CEO of Privacera, emphasized the importance of AI data governance in harnessing the potential of generative AI and LLMs. He noted that these technologies, while transformative, can unknowingly expose intellectual property, Personally Identifiable Information (PII), and sensitive data. Privacera’s mission is to empower enterprises to leverage their data as a strategic asset through intelligent and adaptive AI data governance solutions.

PAIG offers several core capabilities to support AI-driven data governance and security. It leverages Privacera’s existing strengths and combines purpose-built AI and LLMs to drive dynamic security, privacy, and access governance. The solution also features real-time discovery, classification, and tagging of training data, continuous scanning for sensitive data attributes, and data-level controls for access, masking, and encryption.

Furthermore, PAIG enables real-time scanning of user inputs and queries for sensitive data elements, applying privacy controls based on user identity and data access permissions. It also includes the ability to redact or de-identify sensitive data in model responses. To ensure compliance and risk management, PAIG employs AI-powered auditing and monitoring capabilities, enabling continuous monitoring of model usage and user behaviors.

While still in private preview, PAIG represents an important advancement in AI data security and governance. Privacera continues to demonstrate its commitment to empowering enterprises to harness the power of data while ensuring privacy, compliance, and ethical use. With PAIG, organizations can confidently embrace generative AI and LLMs, knowing that their data is protected throughout the entire AI data security lifecycle.

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