What is Deepnote?
Founded in San Francisco in 2019, Deepnote offers a novel data science notebook designed to make teams radically more productive. The company's core philosophy posits that solving complex data science and machine learning challenges requires more than just increased computational power; it necessitates a new paradigm of collaborative notebooks that integrate the entire organization into the data science workflow. Deepnote's platform is already utilized by prominent organizations such as Discord, Gusto, Harvard, MIT, and Stanford, highlighting its impact and adoption within leading institutions.
How much funding has Deepnote raised?
Deepnote has raised a total of $23.8M across 2 funding rounds:
Angel/Seed
$3.8M
Series A
$20M
Angel/Seed (2020): $3.8M with participation from Index Ventures, Credo Ventures, YC Partners, and Accel
Series A (2022): $20M led by Index Ventures, Credo Ventures, Y Combinator, and Accel
Key Investors in Deepnote
Index Ventures
Index Ventures is a venture firm investing in the next generation of entrepreneurs from seed to IPO, partnering with founders with bold dreams to build enduring companies. They invest in entrepreneurs globally from offices in San Francisco & London.
Credo Ventures
Credo Ventures partners with exceptional technology founders from Central and Eastern Europe to support their global ambitions, focusing on pre-seed and seed stage companies with initial investments up to 5 million EUR.
Accel
Accel is a global venture capital firm that partners with exceptional teams from the inception of their ideas through all phases of private company growth, focusing on supporting innovative companies and entrepreneurs.
What's next for Deepnote?
With this substantial backing, Deepnote is poised to accelerate its product development and expand its market reach. The company's focus on fostering collaboration and democratizing data science workflows suggests a strategic direction aimed at becoming the de facto standard for team-based data analysis. Future initiatives will likely involve enhancing platform capabilities, scaling its user base, and further integrating advanced AI features to maintain its competitive edge in the rapidly evolving data science landscape. The enterprise-level funding indicates a move towards broader commercial adoption and enterprise solutions.
See full Deepnote company page
