San Francisco, California-based startup Deepnote that is building a data science platform on top of Jupyter-compatible notebooks raised $20 million Series A funding co-led by Index Ventures and Accel on February 4, 2022.
The company plans to use the new funding to build out its product and expand its foothold in the data science community.
In a blog, Tereza Machackova, Head of People Deepnote said, “Our seed round was heavily focused on building the best product, fostering our community, and proving our product-market fit. We are now entering an exciting phase of doubling down on what works in a rapidly growing market.”
The startup is trying to simplify collaboration in data science projects. These projects are laden with myriad challenges to add to the problem managing Jupyter Notebooks under version control is a laborious task.
Meanwhile, data scientists are now not only analyzing information to get insights but also optimizing algorithms such that firms can integrate it into products. Therefore, they are expected to manage more than just doing research.
The Deepnote team is building a product to effectively manage notebooks
The startup is on a mission to bring data teams together and accelerate their speed and impact with the best notebook experience.
Deepnote is similar to Jupyter Notebook with advanced features like real-time collaboration, versioning, code review, and reusability of algorithms. The idea is to simplify tasks that data scientists manage by enabling others to work along with them in the projects simultaneously.
“Most people don’t realize what’s going to happen with data science notebooks. We are going to see the same transformation in this market as we’ve seen with design and Figma a few years ago. Deepnote is the product that’s going to make it happen,” said Jakub Jurovych, CEO and Founder of Deepnote
“The CEO of Figma understands this, that’s why he, among others, invested in Deepnote. Deepnote is already the standard for the new generation of data scientists. For example, if you are going to take a data science course at Cambridge, Harvard, MIT, etc, it’s going to be taught in Deepnote,” added Jakub.
It is a small but mighty team of builders and makers, excited about reinventing tools for data exploration from first principles. In the past, the company has built tools and infrastructure at companies like Mozilla, Google, Palantir, Amazon, and McKinsey.
