As a company founded by data scientists, Streamlit may be in a unique position to develop tooling to help companies build machine learning applications. For starters, it developed an open-source project, but today the startup announced an expanded beta of a new commercial offering and $35 million in Series B funding.
Sequoia led the investment with help from previous investors Gradient Ventures and GGV Capital. Today’s round brings the total raised to $62 million, according to the company.
Data scientists can download the open-source project and build a machine learning application, but it requires a certain level of technical aptitude to make all the parts work. Company co-founder and CEO Adrien Treuille says that so far the company has 20,000 monthly active developers using the open-source tooling to develop streaming apps, which have been viewed millions of times.
As they have gained that traction, they have customers who would prefer to use a commercial service. “It’s great to have something free and that you can use instantly, but not every company is capable of bridging that into a commercial offering,” Treuille explained.
Company COO and co-founder Amanda Kelly says that the commercial offering called Streamlit for Teams is designed to remove some of the complexity around using the open-source application. “The whole [process of] how do I actually deploy an app, put it in a container, make sure it scales, has the resources and is securely connected to data sources […] — that’s a whole different skill set. That’s a DevOps and IT skill set,” she said.
What Streamlit for Teams does is take care of all that in the background for end users, so they can concentrate on the app building part of the equation without help from the technical side of the company to deploy it.
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Sonya Huang, a partner at Sequoia, who is leading the firm’s investment in Streamlit, says that she was impressed with the company’s developer focus and sees the new commercial offering as a way to expand usage of the applications that data scientists have been building in the open-source project.
“Streamlit has a chance to define a better interface between data teams and business users by ushering in a new paradigm for interactive, data-rich applications,” Huang said.
They have data scientists at big-name companies like Uber, Delta Dental and John Deere using the open-source product already. They have kept the company fairly lean with 27 employees up until now, but the plan is to double that number in the coming year with the new funding, Kelly says.
She says that the founding team recognizes that it’s important to build a diverse company. She admits that it’s not always easy to do in practice when as a young startup you are just fighting to stay alive, but she says that the funding gives them the luxury to step back and begin to hire more deliberately.
“Literally right before this call, I was on with a consultant who is going to come in and work with the executive team, so that we’re all super clear about what we mean [when it comes to] diversity for us and how is this actually a really core part of our company, so that we can flow that into recruiting and people and engineering practices and and make that a lived value within our company,” she said.
Streamlit for Teams is available in beta starting today. The company plans to make it generally available some time later this year.
Streamlit launches open-source machine learning application development framework
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