Streamlit, the creators of the fastest and most powerful app framework for machine learning and data science, announced that it has secured $21 million in Series A funding. The investment was co-led by GGV Capital and Gradient Ventures, with additional participation from Bloomberg Beta, Elad Gil, Daniel Gross and others. Glenn Solomon, Managing Partner of GGV Capital, and Anna Patterson, Managing Partner at Gradient Ventures, have joined Streamlit’s board of directors. The capital investment will accelerate the development of Streamlit’s software which has been used to build over 200,000 applications at some of the world’s biggest companies since being open-sourced just eight months ago.
“Apps are the communication medium of the 21st century,” said Adrien Treuille, co-founder and CEO. “There’s been a thirst in the data and machine learning communities to create rich apps that blend together data, models, visualizations, and business logic. Streamlit makes it effortless to create and share these complex apps. We’re excited to continue developing with the global Streamlit community and making the underlying technology more and more powerful and useful.”
Streamlit was founded in late 2018 with the mission of becoming the best platform for creating and sharing data science apps. Co-founders Amanda Kelly, Thiago Teixeira, and Adrien Treuile met in 2013 while working at Google X and witnessed first-hand how a lack of access to tooling expertise was stymying the progress of machine learning and data science projects. Creating machine learning and data tools in existing app frameworks is prohibitively expensive, requiring front-end programming knowledge that many data scientists don’t have easy access to, thus extending iteration cycles and time to market. Streamlit solves these problems by enabling data scientists to build apps in Python, the fastest-growing programming language and the native language of machine learning and artificial intelligence.
Streamlit’s Ecosystem Is Expanding Rapidly
The 200,000+ that have already been built using Streamlit span everything from explanations of neural networks to product recommendation systems, and they scale from small student projects to sophisticated apps in production at large companies.
“My team found Streamlit to be the quickest way to spin up interactive dashboards on top of Python code. Streamlit democratizes using data, ” observed Koen Havlik, a Data Science leader at Uber.” We’re really excited about integrating Streamlit into our data tooling platform.”
“Our data science team was working on a project that had the potential to change how we worked in our call center, and I challenged the team to create an app for the call centers to use,” explained Justin Lahullier, CIO at Delta Dental of New Jersey and Connecticut. “My team was able to show me a prototype in a matter of weeks, and we had it rolled out to all call centers within a couple of months. Streamlit was faster and more flexible than anything else we had tried, and it allowed our Data Science team to easily port existing work into the Streamlit application for visualizing our data. We now have several business cases for additional apps we are starting to develop with Streamlit.”
World-Class Investors Support The Streamlit Mission
“Streamlit is well positioned to change the way machine learning data is used in organizations,” said Anna Patterson, Managing Partner at Gradient Ventures. “We’re excited to continue working with Streamlit and see their open source tool in the hands of all data scientists.”
“Adapting quickly to new information and insights is one of the biggest challenges facing companies today,” said Glenn Solomon, Managing Partner at GGV Capital. “Streamlit is leading the way in helping data science teams accelerate time to market and amplify the work of machine learning throughout companies of all sizes across a wide variety of industries. At GGV we’re very excited to back this exceptional founding team and support their ambitious global growth plans.”
Streamlit released its open source project for creating apps late last year, and later this year will release Streamlit for Teams, its platform for deploying and sharing those apps. To download and try out Streamlit visit http://streamlit.io or simply $ pip install streamlit.