JFrog Collaborates with NVIDIA to Deliver Secure AI Models With NVIDIA NIM

JFrog swampUP – JFrog Ltd. (“JFrog”) (Nasdaq: FROG), the Liquid Software company and creators of the JFrog Software Supply Chain Platform, now expanded to include a unified MLOps platform through the acquisition of Qwak AI, today announced a new product integration with NVIDIA NIM microservices, part of the NVIDIA AI Enterprise software platform. The integration of the JFrog Platform with the JFrog Artifactory model registry and NVIDIA NIM is expected to combine GPU-optimized, pre-approved AI models with centralized DevSecOps processes in an end-to-end software supply chain workflow. This allows organizations to bring secure machine learning (ML) models and large language models (LLMs) to production at lightning speed, with increased transparency, traceability, and trust.

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JFrog and NVIDIA Collaborating to Deliver Secure AI Models at Scale (Graphic: Business Wire)

“As organizations rapidly adopt AI technology, it's essential to implement practices that ensure their efficiency and safety, and that incorporate AI responsibly,” said Gal Marder, EVP Strategy, JFrog. “By integrating DevOps, security, and MLOps processes into an end-to-end software supply chain workflow with NVIDIA NIM microservices, customers will be able to efficiently bring secure models to production while maintaining high levels of visibility, traceability, and control throughout the pipeline.”

With the rise and accelerated demand for AI in software applications, data scientists and ML engineers face significant challenges when scaling ML model deployments in enterprise environments. Fragmented asset management, security vulnerabilities, compliance issues, and performance bottlenecks are compounded by the complexities of integrating AI workflows with existing software development processes and the requirement for flexible, secure deployment options across various environments. This compounded complexity can result in very long, expensive deployment cycles and, in many cases, failure of AI initiatives.

“As enterprises scale their generative AI deployments, a central repository can help them rapidly select and deploy models that are approved for development,” said Pat Lee, Vice President, Enterprise Strategic Partnerships, NVIDIA. “The integration of NVIDIA NIM microservices into the JFrog Platform can help developers quickly get fully compliant, performance-optimized models quickly running in production.”