06/11/2025 | Press release | Distributed by Public on 06/11/2025 05:07
Sovereign AI ensures control over AI/ML data, models, and infrastructure, which is now essential for enterprises, regulated industries, and national interests.
JFrog and NVIDIA have collaborated to deliver a secure, scalable solution for sovereign AI. NVIDIA provides the accelerated computing and AI software while JFrog ensures trusted DevSecOps and MLOps practices across the entire AI lifecycle, from model development and security scanning to deployment at the edge and in air-gapped environments.
Together, they enable organizations to build, manage, and deploy AI models with full transparency, traceability, and compliance, accelerating innovation while maintaining control: the essence of sovereign AI.
To deliver AI at scale, enterprises need to adopt the same concepts that have achieved these outcomes in traditional software development and management. This includes supporting seamless workflows, strong security, robust governance, and full lifecycle management. Why? Gartner projects that 33% of enterprise software applications will include AI agents by 2028, which is why companies need to have the right systems and measures in place to leverage AI responsibly.
Agentic AI systems are designed to operate with greater autonomy, making decisions and taking actions with minimal human intervention. As agentic AI handles increasingly complex tasks, it will process and rely on sensitive data. This raises valid concerns about data privacy, security, and compliance, which are core tenets of "Sovereign AI."
Sovereign AI has become a strategic imperative for nations, industries, and enterprises alike. Sovereign AI refers to the ability to independently build, deploy, and manage AI systems while retaining full control over data, models, and infrastructure, free from external dependencies and aligned with regulatory, security, and ethical mandates.
To make sovereign AI a reality, organizations need a platform that supports the entire AI lifecycle: from model development to secure supply chain management, deployment, and continuous monitoring. That's where the powerful integration of NVIDIA Enterprise AI Factory validated design with the JFrog Platform comes in.
Sovereign AI is about more than just national interests. It's about control, security, and compliance, especially in highly regulated industries such as healthcare, Defense, automotive, and financial services. As AI becomes deeply embedded in decision-making processes, ensuring transparency, auditability, and data locality becomes essential.
Key principles of sovereign AI include:
NVIDIA provides the foundational compute, AI frameworks, and ecosystem for training and deploying advanced models, from data centers to edge devices. The JFrog Platform underpins this with enterprise-grade software supply chain management, binary lifecycle control, DevSecOps, and MLOps practices critical for operationalizing sovereign AI.
JFrog ML extends this foundation by delivering dedicated ML model lifecycle management capabilities, including versioning, provenance tracking, model promotion, and security policies. This ensures that AI and model artifacts are handled with the same rigor as traditional software. It empowers organizations to govern, distribute, and operationalize AI models with confidence across teams and environments.
JFrog and NVIDIA have collaborated to provide a robust framework for AI-enabled enterprise applications, including agentic and physical AI workflows. The integration of the NVIDIA Enterprise AI Factory validated design and the JFrog Software Supply Chain Platform enables enterprises to securely develop, deploy, and manage AI models and model pipelines while ensuring compliance and governance. Together, NVIDIA and JFrog offer a seamless solution for managing and scaling AI in a secure, compliant, and reproducible manner.
JFrog serves as a secure model registry, ensuring that AI models are versioned, governed, and traceable throughout their lifecycle. AI models, datasets, and dependencies are managed as first-class software artifacts within JFrog's platform.
This eliminates the need for runtime environments to pull components from external sources, enhancing security. Enterprises can scan AI models for vulnerabilities, ensuring compliance with security policies.
NVIDIA AI models, including those containerized and packaged as NVIDIA NIM, available for testing at build.nvidia.com and download from NVIDIA NGC, can be automatically cached in the JFrog Platform. NVIDIA NIM containers are easily tested and downloaded into Artifactory for approval, with easy instructions integrated into the build.nvidia.com page.
This enables them to be accessed locally, with role-based access control (RBAC), as an immutable, traceable artifact. This ensures:
JFrog scans NVIDIA NIM containers using JFrog Xray, performing deep inspection of container layers to detect known vulnerabilities (CVEs), malicious packages, and any license compliance issues. JFrog provides continuous security and policy enforcement from development through to deployment, so you can deploy confidently knowing your NIM containers are secure throughout their software supply chain journey.
Using JFrog's secure and automated binary management, teams can manage everything from AI models to containers and Python packages while maintaining a zero-trust software pipeline for AI workloads, leveraging features like:
For organizations requiring sovereign control over AI processing, edge deployments ensure data never leaves organizational or national boundaries. NVIDIA infrastructure enables real-time inferencing, while the JFrog Platform ensures that:
Sovereign AI often requires air-gapped or on-premise environments due to sensitive data and regulations. The Enterprise AI Factory can also enable optimized AI Deployments to run natively on NVIDIA Blackwell systems, meaning that enterprises can deploy AI workloads on-premises, ensuring full control over their data and reducing latency and improving efficiency.
Both NVIDIA and JFrog support full deployment in isolated infrastructures:
This setup enables enterprises to maintain complete control over their AI infrastructure and data, building sovereign AI capabilities without sacrificing performance or innovation.
The NVIDIA Enterprise AI Factory validated design ensures that organizations can operate AI agents in a secure and compliant environment. The integration of JFrog with popular CI/CD tools, combined with the NVIDIA AI Enterprise platform (including automated training orchestration, secure model deployment via NIM, and NGC registry integration), allows teams to:
JFrog's metadata and promotion workflows ensure AI artifacts can only move between stages (prototype → dev → test → prod) when all quality, security, and legal checks have passed. AI models are continuously monitored and updated to align with evolving regulations.
By combining NVIDIA's compute power and AI tools with the award-winning JFrog Software Supply Chain Platform, organizations can:
As AI adoption accelerates, enterprises must prioritize security, governance, and control. The integration of NVIDIA and JFrog provides a future-proof solution for organizations seeking to build and scale AI while maintaining sovereignty over their data and models. By leveraging trusted AI infrastructure, enterprises can innovate with confidence, ensuring that their AI systems remain secure, compliant, and efficient.
Sovereign AI is not just a technological advancement, it is a necessity for enterprises navigating the complexities of AI governance. With JFrog and NVIDIA leading the charge, organizations can embrace AI with trust, control, and seamless execution.
Sovereign AI isn't just a buzzword, it's a necessary evolution in how we build and trust intelligent systems. With JFrog and NVIDIA, organizations can strike a balance between innovation and control.
Whether you're just starting or scaling your AI initiatives, JFrog and NVIDIA can help you build and govern AI that's secure, compliant, and entirely yours.
→ Learn more about the JFrog + NVIDIA integration
→ Try JFrog for AI Artifact Management
→ Explore NVIDIA NGC Catalog