Qwak raises $12M for its MLOps platform
MLOps platform Qwak today announced that it has raised a $12 million Series A1 funding round from Bessemer Venture Partners. The startup, which offers a fully managed platform that combines machine learning engineering and data management tools, previously raised a total of $15 million. Existing investors Leaders Fund, StageOne Ventures and Amiti also participated in this round, which doubled the company’s valuation.
Qwak’s current customers include the likes of NetApp, Lightricks, Yotpo, JLL, Guesty and OpenWeb (which we use here at TechCrunch to power our comment section). The company says it saw its revenue grow 10x year-over-year.
Image Credits: Qwak
The founding team, Alon Lev (CEO), Ran Romano (VP of Engineering), Yuval Fernbach (CTO) and Lior Penso (COO) previously worked at companies like Payoneer, AWS, VMware, ironSource and Wix. There, Lev told me, they saw how machine learning can help transform businesses.
“Despite our unique journeys, we shared similar challenges with building ML pipelines, which led each of us to the realization that if designed correctly, ML could equip companies with a powerful solution to dramatically enhance business goals,” said Lev. “The breakthroughs we each witnessed were significant, and our desire to add more ML capabilities to our solutions only grew stronger.”
He noted that as the founders explored this market, they noticed that the largest and most advanced players were building their own ML platforms, but the rest of the industry was struggling to turn their ideas into production-ready models. And while there are plenty of open source tools on the market, putting all of those together to build a cohesive platform doesn’t come easy — and that’s obviously where tools like Qwak come in.
And while there are obviously other MLOps platforms on the market, Qwak argues that its full-stack approach sets it apart from the competition. “At Qwak, we believe in a pay-as-you-go model, allowing you to get a fully managed, end-to-end ML platform that streamlines your entire ML pipeline in a very economical way. With Qwak, you can eliminate the need for cross-functional collaboration and the headache of integrating multiple vendors, enabling you to focus on what matters most — building exceptional ML models,” said Lev.
The Qwak platform currently offers a feature store, model registry, tools for deploying models and monitoring them in production, as well as a data pipeline orchestrator.
Lev noted that the company wasn’t actively looking for new funding but the team had always had a close relationship with Bessemer VP Ariel Sterman. “While catching up over coffee, I updated Ariel on our progress, and he was impressed with our vision and the strides we had made,” Lev said. “He also shared his own vision for the industry and gave his prediction for the future of ML. Following this conversation, it soon became clear to both of us that we needed to work together to achieve our shared goal, which is why we are proud to collaborate with BVP and Ariel today.”
