JFrog and Qwak’s Collaboration Provides MLOps Solutions to Streamline Application Delivery

Highlights:

• JFrog Artifactory and Xray will be able to utilize Qwak’s ML Platform to integrate machine learning applications with all other software development components in a contemporary DevSecOps and MLOps process.
• Through the native connection, users can design, train, and deploy models with improved visibility, governance, versioning, and security both on-premises and in the cloud by connecting JFrog’s universal ML Model registry with a centralized MLOps platform.

A software supply chain company, JFrog Ltd., announced its latest integration with Qwak AI Ltd., a machine learning platform provider. This collaboration introduces machine learning models into the conventional software development lifecycle procedures, aiming to streamline, expedite, and expand the secure delivery of artificial intelligence applications.

Qwak is an organization that focuses on streamlining the operational process of machine learning through the provision of a platform that effectively oversees and implements diverse models, operating in both batch and real-time environments. Aiming to improve operational efficiency by addressing the complexities associated with machine learning model deployment, integration, and optimization, the organization’s platform provides observability and a vector database layer to facilitate the deployment of multiple models into production.

As part of the partnership, JFrog Artifactory and Xray collaborate with Qwak’s ML Platform to deliver machine learning applications in a modern DevSecOps and MLOps workflow, in addition to all other software development components. By doing so, the development of initiatives at scale will be simplified for data scientists, machine learning architects, developers, and DevOps teams.

Through the native connection, users can design, train, and deploy models with improved visibility, governance, versioning, and security both on-premises and in the cloud by connecting JFrog’s universal ML Model registry with a centralized MLOps platform. It is also claimed that using a centralized platform for machine learning model deployment allows users to concentrate more of their time on their primary data science responsibilities and less on infrastructure.

Gal Marder, Executive Vice President of Strategy at JFrog, said, “Data scientists and software engineers are the creators of modern AI applications that are having a dramatic impact on our society, but there are still hurdles to overcome in terms of bringing ML models to production, such as bridging the gap between MLOps and DevSecOps workflows. Working with Qwak, we can provide customers with a complete MLSecOps solution that helps bridge this gap by bringing ML models in line with other software development processes, creating a single source of truth for all software components across Engineering, DevOps and DevSecOps teams.”

Qwak Chief Executive Alon Lev mentioned that “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.”

According to Tracxn, an Israel-based Qwak is backed by venture capital and has raised USD 31 million. Bessemer Venture Partners Inc., Leaders Fund LLC, StageOne Ventures Ltd., and Amiti Inc. are among the company’s investors.