JFrog to Acquire Qwak AI to Streamline AI Models from Development to Production
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Union will expand JFrog's Platform to deliver advanced MLOps capabilities to organizations, enabling them to build, deploy, manage, and monitor AI workflows. (Graphic: Business Wire)
With the acquisition, JFrog aims to offer a unified and scalable solution for DevOps, Security, and MLOps stakeholders. This advanced, industry-leading MLOps functionality is designed to free data scientists and developers from infrastructure concerns, accelerating the creation and delivery of AI-powered applications. JFrog is the single system of record for all software packages (binaries), including models stored in Artifactory. Enhancing its machine learning (ML) model capabilities will enable users to streamline models from development to deployment.
“Next-generation Software Supply Chain platforms will need to expand and natively include MLOps solutions to better serve development organizations,” said
As part of the JFrog Platform, Qwak technology will deliver a straightforward and hassle-free user experience for bringing models to production, combined with the level of trust and provenance enterprises expect from JFrog as they deliver AI-powered applications. This combination leverages Qwak’s advanced model training and serving capabilities to manage the previously-siloed and complex lifecycle of models, alongside model storage management and security scanning of models provided by JFrog.
The acquisition follows a successful integration between JFrog and Qwak solutions announced earlier this year, based on JFrog’s “model as a package” approach. The holistic solution aims to eliminate the need for separate tools, separate compliance efforts and will offer full traceability in a single solution.
“We’re beyond excited to join the JFrog family and to help customers accelerate their AI initiatives,” said
Speed to market and a secure flow of ML models - the fuel behind artificial intelligence - is the key driver behind modern MLOps initiatives as companies attempt to deliver AI-powered applications. According to Gartner, MLOps plays a critical role in the operationalization of AI, with 75% of companies shifting from piloting to operation of AI by the end of 2024 (
“Data scientists and ML engineers currently use tools that are mostly disconnected from standard DevOps and Security processes within companies, delaying release timeframes and eroding trust,” said
Today’s market demands a single platform experience across the software supply chain to accelerate development processes and that treats the fuel of AI - machine learning models and their metadata - accordingly. Like any other software component, ML models must be stored, built, traced, versioned, signed, secured and efficiently delivered across systems in order to deliver AI at scale. Utilizing DevOps practices in a unified solution addresses these market expectations.
The acquisition of Qwak will expand JFrog solutions with the following capabilities:
- One Platform for DevSecOps & MLSecOps, offering a holistic ML software supply chain from traditional models to LLMs and GenAI
- Fast and straightforward model serving into production with simplified model development and deployment and serving processes, improving AI initiatives
- Model training and monitoring with OOTB dataset management and feature store support
- Manage models as a package allowing you to version, manage, and secure models the same way you do any other software package with DevSecOps best practices
- Ensure provenance and security of AI naturally in the development workflows
- Pull from a governed, secure source of truth that marries ML models with the other building blocks such as containers and Python packages
- Trace models back to their source for easy recall, retraining and redeployment if something goes wrong with production models
JFrog’s MLOps Road Map
As part of the acquisition and integration process, JFrog plans to assimilate Qwak’s talent into JFrog, rapidly growing the MLOps-centric team. JFrog will also accelerate the process of technology integration to bring Qwak technology into the JFrog Platform, across JFrog DevOps and Security products. JFrog and Qwak will work together with customers to ensure business continuity and streamlined migration to future jointly-developed and supported offerings.
MLOps Ecosystem & Partner Integrations
Earlier this year, JFrog announced integrations with AWS Sagemaker and
For a deeper look at how the union of JFrog and Qwak is expected to help build, train, secure, deploy and monitor ML models and GenAI in a unified experience, visit our solution page, read this blog and join us for a webinar the week of
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