Privacera Announces Availability of PAIG OSS: The First-of-its-Kind Open-Source Framework for Responsible Generative AI Development

News provided by

Sep 10, 2024, 08:00 ET

Innovate with GenAI without compromising data security or privacy

FREMONT, Calif., Sept. 10, 2024 /PRNewswire/ -- Privacera, the AI and data security governance company founded by the creators of Apache Ranger™ and the industry's first comprehensive generative AI governance solution, today announced the open-sourcing of their industry-leading Privacera AI Governance (PAIG) solution. PAIG Open-Source Software (PAIG OSS) is an open-source framework empowering developers to build innovative Generative AI (GenAI) applications while adhering to the highest standards of ethics, privacy, and security.

A Framework for Responsible and Secure Innovation
The rapid adoption of GenAI has moved faster than most organizations anticipated, with 10% of the Global 2000 already claiming to have GenAI projects in production. However, the risks associated with AI applications involving sensitive corporate or personal information are becoming increasingly clear.

Larger organizations must prioritize piloting an end-to-end solution before fully committing to GenAI. Attempting to bolt on security and governance after issues arise is risky. Meanwhile, smaller organizations require an easy-to-consume method for protecting sensitive, unstructured, semi-structured, and structured data. PAIG OSS offers a robust, open-source toolkit for organizations of all sizes to pilot and productize secure GenAI solutions.

"Open-source frameworks like PAIG OSS are vital for the future of GenAI because they embody the principles of transparency, collaboration, and inclusivity," said Balaji Ganesan, CEO and Co-Founder of Privacera. "By standardizing on open APIs and fostering a community-driven approach, we not only accelerate innovation but also ensure that the development of GenAI aligns with ethical standards and diverse perspectives. API governance and data leadership are crucial for building trust in AI systems and making them more resilient, secure, and adaptable to the evolving needs of businesses and society."

"PAIG Open-Source provides guardrails for GenAI applications, allowing developers to focus on innovation without sacrificing security," said Jiang Chen, Head of Ecosystem and Developer Relations at Zilliz. "Through fine-grained access control with Milvus vector database, PAIG carries forward the original data source's access policies, ensuring that sensitive data remains protected while maintaining high search performance."

In a recent study of C-suite executives, the IBM Institute for Business Value found that only 24% of current-gen AI projects have a component to secure the initiatives, even though 82% of respondents say secure and trustworthy AI is essential to their business's success.

Given the obvious need for solutions in this area and Privacera's introduction of PAIG.ai as a new open-source initiative that enables safety and security guardrails for generative AI applications, PAIG.ai is one of the open-source projects showcased during IBM's TechXchange Conference 2024 as part of Open-Source Community Day. Over 8,000 developers will attend the event.

Key Features of PAIG OSS

Extensibility: Seamless integration with a wide range of Large Language Models (LLMs), Vector Databases (VectorDBs), orchestrators, and other AI tools. This extensibility allows developers to leverage the best technologies available, ensuring their GenAI applications are powerful and adaptable. PAIG OSS empowers users to build AI solutions tailored to their specific needs by supporting a broad ecosystem of tools.
Security and Safety: Implements best practices and recommendations from leading security frameworks, including NIST and OWASP. These comprehensive security measures ensure that AI applications are protected against a wide range of threats, safeguarding sensitive data and maintaining the integrity of AI systems. The framework's commitment to security and safety gives developers the confidence to deploy AI solutions in even the most regulated environments.
Flexibility: Designed with flexibility at its core, PAIG OSS allows users to integrate new tools and solutions without needing to rewrite their applications. This customizable approach ensures organizations continuously evolve AI capabilities to meet emerging challenges and opportunities. Whether adapting to new regulations or incorporating the latest AI innovations, PAIG OSS provides the flexibility needed to stay ahead.
Observability: Organizations can monitor all invocations to LLMs and Retrieval-Augmented Generation (RAG) systems, providing comprehensive observability for security, compliance, and operational reviews. This level of visibility ensures that AI operations are transparent and accountable, enabling organizations to maintain control over their AI deployments and swiftly address any issues.
Future-Proofing: Continuously updated to include the latest security and safety solutions, ensuring long-term relevance and protection against emerging threats. This commitment to future-proofing gives developers the confidence that their AI applications are always equipped with cutting-edge tools to protect against new vulnerabilities and challenges, instilling a sense of security and confidence in their work.
User-Focus: Designed with a strong focus on user needs. PAIG OSS provides a robust framework incorporating the best available point solutions, allowing developers to concentrate on their core use cases. This user-centric approach ensures developers can dedicate their efforts to innovation and problem-solving rather than being bogged down by AI governance and security complexities.

Empowering Developers and Practitioners

PAIG OSS is a platform that empowers individual developers and practitioners, providing them with easy access to essential tools and libraries. This democratizes the development of responsible AI applications, making it accessible to both seasoned AI experts and newcomers. PAIG OSS offers the resources to build innovative and ethical AI solutions, making every developer and practitioner an integral part of the AI community.

"At our healthcare startup, building GenAI solutions comes with unique challenges around speed, safety, and compliance. PAIG helps us overcome those hurdles by providing an easy-to-use framework with built-in security and governance features. It's enabled us to bring applications to market faster while ensuring we meet the highest standards for safety and privacy," adds Preetpal Singh, co-founder of Heald.

Availability

PAIG OSS is now available for download on our GitHub repository. To learn more about the features and capabilities of our open-source framework, visit http://paig.ai or follow us on Discord.

Join the Movement

We invite developers, researchers, and practitioners to join us in our mission to foster responsible AI innovation. By contributing to and utilizing PAIG OSS, you can play a pivotal role in shaping the future of AI technology. Your expertise and insights are invaluable in this journey.

About Privacera
Privacera, based in Fremont, CA, was founded in 2016 by the creators of Apache Ranger™ and Apache Atlas. Delivering trusted and timely access to data consumers, Privacera provides data privacy, security, and governance through its SaaS-based unified data and AI security platform. Privacera's latest innovation, Privacera AI Governance, is the industry's first AI data security governance solution. Privacera serves Fortune 500 clients across finance, insurance, life sciences, retail, media, consumer, and government entities. The company achieved AWS Data and Analytics Competency Status and partners with and supports leading data sources, including AWS, Snowflake, Databricks, Azure and Google. Privacera is recognized as a leader in the 2023 GigaOm Radar for Data Governance; was named a 2022 CISO Choice Awards Finalist; and received the 2022 Digital Innovator Award. The company is also named a "Sample Vendor" for data security platforms in the Gartner® Hype Cycle™ for Data Security, 2023. Learn more at Privacera.com.

SOURCE Privacera