JFrog teams with NVIDIA to boost secure enterprise AI adoption

JFrog has announced a new integration of its DevSecOps tools with the NVIDIA Enterprise AI Factory validated design, aiming to support enterprises in developing on-premises artificial intelligence systems.

The collaboration is set to position JFrog as the primary software artifact repository and secure model registry for NVIDIA's agentic AI architecture. As businesses increasingly adopt AI-first strategies, the integration is intended to provide a blueprint for building secure, scalable, and efficient AI and machine learning operations (MLOps) on-premises, with particular attention to regulatory, privacy, and data control requirements.

JFrog's platform is being integrated directly into the NVIDIA Enterprise AI Factory, which is described as a suite of validated technologies for enterprises intending to manage AI workloads, including agentic AI, physical AI, and high-performance computing, on their own infrastructure. This is especially relevant for industries facing stringent compliance and security demands.

Shlomi Ben Haim, Chief Executive Officer and co-founder of JFrog, commented on the partnership: "The future of AI depends not only on innovation - but on trust, control, and seamless execution. 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 organisations can build and scale trusted AI solutions with confidence."

Key features of the JFrog Platform within this partnership are designed to offer "single source of truth" management for all software components. This includes secure and governed visibility—allowing machine learning models, engines, and software artifacts to be scanned for security risks, versioned, and made traceable through every step of development.

The platform also supports end-to-end management, providing seamless uploading, hosting, and deployment of AI models and datasets, containers, and other dependencies optimised for the NVIDIA Enterprise AI Factory. By eliminating the need for runtime environments to retrieve components from external sources, the system streamlines configuration and deployment for enterprise AI environments.

Other capabilities include simplified versioning and upgrading of ML models, responding to the rapid evolution of generative AI solutions, and supporting scalable and robust handling of software supply chain requirements across MLOps pipelines.

Justin Boitano, Vice President, Enterprise AI Software Products, NVIDIA, said: "Enterprises building AI factories need to manage the complexity of AI adoption while ensuring performance, governance and trust. JFrog's unified software supply chain platform, paired with the NVIDIA Enterprise AI Factory validated design, enables rapid, responsible AI innovation at scale."

The partnership supports the JFrog Platform running natively on NVIDIA Blackwell systems, which is expected to reduce latency and enable more efficient processing of demanding AI workloads. This support extends to a range of enterprise applications, from agentic and physical AI to real-time data analysis and autonomous decision-making, across sectors such as finance, healthcare, telecommunications, retail, media, and manufacturing.

The integration leverages NVIDIA's engineering expertise and partner network in order to help enterprises reduce deployment risks and expedite the time required to gain value from artificial intelligence solutions.