Machine Learning Experiment Tracking startup Weights & Biases Raises Series B

San Francisco based Weights & Biases, a startup that offers performance visualization tools for machine learning raised US$ 45 million in Series B funding on 1 February 2021.

The Series B funding round was led by Insight Partners with participation from Coatue, Trinity Ventures and Bloomberg Beta. Weights & Biases had previously raised US$ 20 million in funding. Insight’s George Mathew will join the board of directors.

Purpose of the funding: The funds will be utilized to continue hiring in engineering, growth, sales and customer success.

About Weights and Biases

Machine Learning Experiment Tracking startup Weights & Biases Raises Series B

Founded in 2018 by Lukas Biewald, Chris Van Pelt and Shawn Lewis, Weights & Biases helps companies turn deep learning research projects into deployed software. It helps the teams to track their models, visualize model performance and easily automate training and improving models. Weights & Biases claims that it has more than 70,000 users at more than 200 enterprises.

Weights & Biases has many notable clients like Toyota, OpenAI, GitHub, Salesforce, Samsung among others. The agriculture giant John Deere is using the startup’s platform to improve the way it uses robotics to spray fertilizer, rather than pesticides, to kill weeds and pests. Some pharmaceutical companies are also using the platform to model how different molecules will behave.

What the founders have to say: “While machine learning practitioners are often compared to software developers, they’re more like scientists in some ways than engineers. It is a process that involves numerous experiments, and Weights & Biases’ core product allows practitioners to track those experiments, while it also offers tools around data set versioning, model evaluation and pipeline management,” said Lukas Biewald. The startup is “completely focused on the ML practitioner” rather than top-down enterprise sales.

“If you have a model that’s controlling a self-driving car and the car crashes, you really want to know what happened. If you built that model years ago and you’ve run all these experiments since then, it can be hard to systematically trace through what happened unless you’re using experiment tracking,” Biewald said.

What Investors have to say: “It’s an honour to make my first investment at Insight to serve an ML practitioner user-base that grew 60x these last two years,” said George Matthew of Insight Partners. 

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Komal writes about the startup ecosystem on VCBay. She is an Economics Hons. graduate from Miranda House, Delhi University, and is passionate about the world of entrepreneurship and finance.



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