Qwak MLOps Platform doubles valuation with $12M Bessemer funding

Bessemer's first investment in MLOps comes after a year of rapid growth.

TEL AVIV, Israel, March 1, 2023 /PRNewswire/ -- Qwak, the end-to-end MLOps platform, today announced a new investment from Bessemer Venture Partners. The $12 million financing, at double the valuation from the company's last funding round, follows a year of growth and represents Bessemer's first meaningful investment in the growing area of MLOps and machine learning infrastructure. Existing investors Leaders Fund, StageOne Ventures and Amiti also participated in the round. The investment comes as machine learning (ML) is breaking into the mainstream, with generative AI applications like Dall-E, MidJourney and ChatGPT becoming massively popular and disrupting the creative industries.

Qwak has experienced 10x year-on-year growth, signing dozens of customers that use the platform in production including some of the most advanced machine learning teams in the world. Customers include NetApp, Lightricks, Yotpo, JLL, Guesty and OpenWeb. The company has doubled its team size to 30, and is recruiting to expand deeper into the US and European markets.

"I'm very excited that Bessemer Venture Partners has invested in Qwak," said Alon Lev, co-founder and CEO of Qwak. "We see the funding as backing Qwak's approach, our platform and our growth in recent months. As we continue to expand and develop the platform, this strategic relationship with Bessemer will aid Qwak's long-term vision of building what I see as the machine learning cloud, helping to turn data science insights into true business impact, driven by machine learning."

Data Science and ML require experts, specialist tools and technology that can be radically different from the traditional software, hardware and skills employed in the rest of a business, even a technology business. Many organizations have struggled and failed to translate the work of their data science team into ML content in their apps. The sheer number of tools and solutions needed to address the breadth of the ML stack is daunting and companies waste resources trying to construct functioning workflows, data and deployment pipelines. Making the very expensive investment of data science to be inefficient. Gartner claims that 85% of AI initiatives fail.

Qwak brings all stages of the MLOps lifecycle together into a single end-to-end platform that unifies all parts of ML development through to production. It replaces dozens of other tools and enables collaboration across a whole organization, empowering data science teams to deploy more at optimal resource efficiency. A fully managed platform that can be hosted on Qwak's cloud or on the customer's cloud, Qwak removes the burdens of infrastructure installation and maintenance as an 'off the shelf' solution that serves all the AI needs of companies from small startups through to large enterprises. Recently-added features include streaming aggregation, A/B tests, experiment tracking, multi-environment for multiple clouds and regions, and monitoring.

Bessemer invested in Qwak after conducting detailed research about the future of machine learning and MLOps. Ariel Sterman, vice president at Bessemer Venture Partners, explained the decision. 

"There's no question that data-driven companies out-executed their competitors over the past decade," said Sterman. "As a result nearly every company today has a sophisticated BI and analytics stack, relying on third party platforms like Cloud Data Warehouses and BI Infrastructure. Machine Learning Ops and infrastructure will be no different, as companies focus on their core business and rely on specialized platforms under the hood. Qwak's full-stack ML Ops platform allows data teams to operationalize their models far more effectively than ever before, creating significant ROI for its customers as it allows them to more quickly turn data science research into trusted models in production that have measurable business impact out of the box."

About Qwak:

Qwak's ML Platform empowers data science and ML engineering teams to continuously build, train and deploy ML models and features to production at scale.

By abstracting the complexities of model deployment Qwak brings agility and high-velocity to all ML initiatives designed to transform business, innovate, and create a competitive advantage. Qwak allows data teams to focus on the science

Read more at www.qwak.com

Contact:
Lazer Cohen
[email protected]
347-753-8256

SOURCE Qwak