JFrog Ltd, the Liquid Software company and creator of the JFrog Software Supply Chain Platform, is unveiling its latest technology integration with Qwak, a fully managed ML Platform, aiming to accelerate, scale, and ease the development process of ML applications while maintaining adherence to security and compliance standards.
This integration merges the power of JFrog Artifactory and Xray with that of Qwak’s platform, connecting JFrog’s universal ML Model registry with a unified MLOps solution. This will empower data scientists, ML engineers, developers, security, and DevOps teams to build, train, and deploy models—all with the benefit of improved visibility, governance, versioning, and security easily and quickly.
“Currently, data scientists and ML engineers are using a myriad of disparate tools, which are mostly disconnected from standard DevOps processes within the organization, to mature models to release. This slows MLOps processes down, compromises security, and increases the cost of building AI powered applications,” said Gal Marder, executive vice president of strategy at JFrog.
“The combination of the JFrog Platform—with Artifactory and Xray at its core—plus Qwak provides users with a complete MLSecOps solution that brings ML models in line with other software development processes, creating a single source of truth for all software components across engineering, MLOps, DevOps, and DevSecOps teams so they can build and release AI applications faster, with minimal risk and less cost,” Marder continued.
The right infrastructure for supporting MLOps is crucial, especially amid the growing adoption of ML/AI tech and the financial impact of its realization at scale. Without it, enterprises are left with ML projects that are difficult to build, maintain, scale, and secure, according to the companies. JFrog and Qwak’s integration seeks to rectify this evolving challenge for a variety of organizational personas, ensuring that companies can embark on this exciting era of technology with confidence and a focus on core tasks, not infrastructure.
“AI and ML have recently transformed from being a distant future prospect to a ubiquitous reality. Building ML models is a complex and time-intensive process, which is why many data scientists are still struggling to turn their ideas into production-ready models,” said Alon Lev, CEO at Qwak. “While there are plenty of open source tools on the market, putting all of those together to build a comprehensive ML pipeline isn’t easy, which is why we’re thrilled to work with JFrog on a solution for automating ML artifacts and releases in the same, secure way customers manage their software supply chain with JFrog Artifactory and Xray.”
To learn more about JFrog and Qwak’s integration, please visit https://jfrog.com/ or https://www.qwak.com/.