JFrog And NVIDIA Team Up For AI Innovation

JFrog Ltd, the Liquid Software company and creators of the award-winning JFrog Software Supply Chain Platform, now announced the integration of its foundational DevSecOps tools with the NVIDIA Enterprise AI Factory validated design.

JFrog will serve as the cornerstone software artifact repository and secure model registry for the landmark agentic AI architecture.

NVIDIA NIM integration

New collaboration delivers a full-spectrum MLOps solution, designed to ensure scalable

Following a successful NVIDIA NIM integration with the JFrog Platform, this new collaboration delivers a full-spectrum MLOps solution, designed to ensure scalable, secure and seamless deployment of AI-powered applications using the NVIDIA Blackwell platform.

"The future of AI depends not only on innovation - but on trust, control, and seamless execution," said Shlomi Ben Haim, CEO and co-founder of JFrog.

JFrog’s Software Supply Chain Platform

"To deliver AI at scale, enterprises need to adopt the same concepts applied to software: developer-friendly workflows, strong security, robust governance, and full lifecycle management. ML models are binaries, and they must be managed as first-class software artifacts."

"That’s why we’re excited to partner with NVIDIA to bring JFrog’s Software Supply Chain Platform as the single source of truth for all software and AI assets to the NVIDIA Enterprise AI Factory so organizations can build and scale trusted AI solutions with confidence."

Delivering critical infrastructure to enable future AI innovation

JFrog Platform provides customers with a “single source of truth” for software components within NVIDIA

The JFrog Platform provides customers with a “single source of truth” for software components within NVIDIA Enterprise AI Factory, which contains an integrated and validated suite of software technology solutions enterprises can use to develop, deploy, and manage agentic AI, physical AI, and HPC workloads on-premises.

This validated design aims to allow organizations to have full control of their data and operate advanced AI agents in a secure environment. Key capabilities include:

• Secure & Governed Software Component Visibility: Enables all ML models, engines, and software artifacts to be scanned for security issues, versioned, governed, and traceable across the entire software development lifecycle.
• End-to-End Software Artifact & ML Model Management: Enables the seamless pulling, uploading, and hosting of AI models and datasets, AI containers, Docker containers, and dependencies optimized for the NVIDIA Enterprise AI Factory validated design. 
• Rapid, Trusted AI/ML Application Provisioning in Runtime: Simplifies configuration of AI environments by eliminating the need for runtime environments to pull components from outside of the organization, thanks to the universality, proven scalability and robustness of JFrog Artifactory. 
• Future-proofed for Evolving GenAI Applications: Quickly and easily manages ML model versioning and upgrades to new and approved model generations.

Complexity of AI adoption

JFrog Platform to run natively on NVIDIA Blackwell systems to help reduce latency and process tasks

“Enterprises building AI factories need to manage the complexity of AI adoption while ensuring performance, governance and trust,” said Justin Boitano, Vice President, Enterprise AI Software Products, NVIDIA.

“JFrog’s unified software supply chain platform, paired with the NVIDIA Enterprise AI Factory validated design, enables rapid, responsible AI innovation at scale.”

NVIDIA Blackwell systems

The integration is designed to enable the JFrog Platform to run natively on NVIDIA Blackwell systems to help reduce latency and process tasks with unparalleled performance, efficiency, and scale. It supports a wide range of AI-enabled enterprise applications, agentic and physical AI workflows, autonomous decision-making, and real-time data analysis across various industries, including financial services, healthcare, telecommunications, retail, media, and manufacturing.

Additionally, the system leverages NVIDIA’s engineering know-how and partner ecosystem to help enterprises accelerate time-to-value and mitigate the risks of AI deployment.