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Qwak Raises $15 million for MLOps Platform

Qwak

Qwak team (company pic)

Qwak, an Israeli startup that developed an MLOps engineering platform, raised $15 million in a fundraising round led by Leaders Fund and StageOne Ventures. The company previously raised $4 million in seed funding.

MLOps stands for Machine Learning Operations. MLOps is a core function of Machine Learning engineering, focused on streamlining the process of taking machine learning models to production, and then maintaining and monitoring them. An MLOps engineer does the job of a DevOps engineer in the area of machine learning. An MLOps engineer is responsible for all of the activities that are operated after the machine learning model is built. Qwak’s platform aids in this.

Founded in 2021 by Alon Lev, Yuval Fernbach, Lior Penso, and Ran Romano, Qwak is an end-to-end production ML platform designed to reduce the friction between the ML research and the production phases. Qwak allows data scientists and data engineers to build, deploy and monitor their models in production with minimal engineering friction. The company’s three founders have plenty of experience with high tech success. Yuval Fernbach was a machine learning specialist at Amazon Web Services, Alon Lev was the VP of data at Israeli company Payoneer and Ran Romano worked for Wix, another successful Israeli startup.

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Qwak platform includes CI/CD for ML models, version management, model analytics, and a feature store. Our main focus is to enable companies to create ML-based development without spending endless resources on infrastructure and wiring.

“Companies all over the world are recognizing data science’s great value and understand they need to adopt ML to stay relevant in today’s market,” said Alon Lev, co-founder and CEO of Qwak. “We’ve seen large technology companies invest substantial resources to build out ML Engineering platforms, in the hopes of developing solutions to these challenges. These investments will only accelerate in the future as ML infiltrates all of its product offerings. Fast-growing startups, however, are still finding it difficult to build ML-based products, mostly due to the difficulties with model integration and the precious time required for this to be accomplished by supporting teams. Utilizing Qwak’s technology enables companies to expand their line of ML-based products and thereby grow their business influence and compete globally.”

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