JFrog will integrate its DevSecOps tools with 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.
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 JFrog CEO Shlomi Ben Haim. “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.”
“Machine learning models are binaries, and they must be managed as first-class software artifacts,” he added. “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 organisations can build and scale trusted AI solutions with confidence.”
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 organisations to have full control of their data and operate advanced AI agents in a secure environment. Key capabilities include:
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Secure and governed software component visibility: Enables all machine learning models, engines, and software artifacts to be scanned for security issues, versioned, governed, and traceable across the entire software development lifecycle.
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End-to-end software artifact and machine learning model management: Enables the seamless pulling, uploading, and hosting of AI models and datasets, AI containers, Docker containers, and dependencies optimised for the NVIDIA Enterprise AI Factory validated design.
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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 organisation, thanks to the universality, proven scalability and robustness of JFrog Artifactory.
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Future-proofed for evolving GenAI applications: Quickly and easily manages machine learning model versioning and upgrades to new and approved model generations.
“Enterprises building AI factories need to manage the complexity of AI adoption while ensuring performance, governance and trust,” said NVIDIA’s Enterprise AI Software Products VP Justin Boitano. “JFrog’s unified software supply chain platform, paired with the NVIDIA Enterprise AI Factory validated design, enables rapid, responsible AI innovation at scale.”
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.
