Enterprises face significant challenges in moving AI applications from prototype to production, primarily due to the complexities of managing machine learning models efficiently while ensuring security and governance. JFrog's integration with NVIDIA NIM provides a solution by applying enterprise-grade DevSecOps practices to AI development, addressing technical challenges such as specialized artifact management, dependency management, GPU resource optimization, and security. NVIDIA NIM offers containerized microservices tailored for enterprise AI deployment, with features like pre-optimized model execution on NVIDIA hardware and support for multiple LLM runtimes. The JFrog Platform enhances this by providing centralized governance, security, and distribution, enabling streamlined AI model management within existing software development frameworks. This integration ensures secure storage, vulnerability scanning, and efficient deployment across hybrid and multi-cloud environments, empowering organizations to accelerate AI innovation while maintaining scalability and compliance. As AI adoption increases, leveraging JFrog's DevSecOps platform and NVIDIA's inference microservices positions enterprises to excel in an AI-driven landscape.