Modern AI applications are transforming industries, but challenges persist in deploying machine learning (ML) models to production, often due to the complexity and time demands of building these models. The integration of MLOps and DevSecOps workflows is crucial for streamlining this process, and the introduction of Qwak—a fully managed ML platform—aims to address these challenges. Qwak connects machine learning with traditional software development processes to accelerate, scale, and secure ML application delivery, managing the ML lifecycle from model development to deployment while ensuring artifact security and compliance. The collaboration between JFrog and Qwak enhances this by providing a comprehensive MLSecOps solution, fostering seamless collaboration across engineering, DevOps, and DevSecOps teams. This integration offers advanced dependency scanning, enforced compliance, and centralized artifact management, promoting transparency, consistency, and adherence to organizational standards. The synergy between JFrog and Qwak endeavors to improve the efficiency and security of ML model development and deployment, encouraging organizations to confidently advance their machine learning initiatives.