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"In the first 3 months, 30 people were working inside Deepnote, and this number quickly grew to 100 in the first 6 months."
Find out why more than 100,000 data professionals use Deepnote to explore, collaborate, and share.
Deepnote is built from the ground up for collaboration — whether it’s teams of two or 2,000.
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Deepnote was recognized by Gartner as an industry leader in the 2022 Market Guide for Augmented Analytics
"In the first 3 months, 30 people were working inside Deepnote, and this number quickly grew to 100 in the first 6 months."
"Embracing Deepnote at Homa showcases our willingness to adopt innovative tools and solutions. Deepnote AI has really been a game-changer."
"We moved over to Deepnote ... we’re no longer copying and pasting screenshots from external sources."
“Ultimately, it has made a huge difference for collaboration in our team — it's night and day. There's before Deepnote and after Deepnote time.”
“It always surprises stakeholders how fast we work with Deepnote. We discuss something in the morning and we have results to share in the same afternoon.”
“Our team can conduct analyses in the language most comfortable for them, which makes it accessible to and powerful for everyone.”
“Working in Deepnote is like code review and rapid prototyping at the same time, saving valuable time in the iteration cycles.”
“[W]hen we moved over to Deepnote, we appreciated the similar look and feel as well as the added scalability — we’re no longer copying and pasting screenshots from external sources.”
"Deepnote has revolutionized our data analysis workflow, enabling our teams to deliver insights in a fast collaborative manner.”
"I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was."
“Since metrics require a lot of input … to define and align on definitions, we needed a collaborative layer where we could get immediate feedback.”
Create tighter feedback loops and get answers in minutes instead of weeks. Collaborate directly on data or models.
Speed up analysis with effortless integrations, automated workflows, and point-and-click data visualizations.
Optimize for efficiency with a secure, maintenance-free cloud environment that eliminates infrastructure burdens.
I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was.
Director of Engineering
Working in Deepnote is like code review and rapid prototyping at the same time, saving valuable time in the iteration cycles.
CTO
I have been trying out Deepnote for running shared Jupyter notebooks, and I’m very impressed by how smooth and powerful the whole experience is.
Chief Scientist
Collaborative data analysis where team members can freely share their work and get feedback… This made the analysis workflow much faster.
Data Analyst
Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently.
Data Scientist
I just love how SQL is now a first-class citizen in Deepnote notebooks! 🔥 It is SO easy to query databases!
Developer
Deepnote enables us to bring people into the phase of data science that’s all about experimentation, helps them understand our processes, and encourages folks to leverage data science in even more ways.
Sr. Manager, Data Science
I enjoy writing code on weekends (mostly hack around with data analysis & machine learning in Python). This year I moved my dev environment fully to Deepnote, and I’m never going back. The future of coding is browser-based.
CEO & co-founder
Used by the next generation of data analysts and data scientists.
Learn more ->Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds. Working together with Deepnote gives us a great window into the ways candidates approach the interview problem.
Head of Data Science
Since metrics require a lot of input from subject matter experts, data consumers, and business stakeholders to define and align on definitions, we needed a collaborative layer where we could get immediate feedback.
Head of Analytics Engineering
I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was.
Director of Engineering
Working in Deepnote is like code review and rapid prototyping at the same time, saving valuable time in the iteration cycles.
CTO
I have been trying out Deepnote for running shared Jupyter notebooks, and I’m very impressed by how smooth and powerful the whole experience is.
Chief Scientist
Collaborative data analysis where team members can freely share their work and get feedback… This made the analysis workflow much faster.
Data Analyst
Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently.
Data Scientist
I just love how SQL is now a first-class citizen in Deepnote notebooks! 🔥 It is SO easy to query databases!
Developer
Deepnote enables us to bring people into the phase of data science that’s all about experimentation, helps them understand our processes, and encourages folks to leverage data science in even more ways.
Sr. Manager, Data Science
I enjoy writing code on weekends (mostly hack around with data analysis & machine learning in Python). This year I moved my dev environment fully to Deepnote, and I’m never going back. The future of coding is browser-based.
CEO & co-founder
Used by the next generation of data analysts and data scientists.
Learn more ->Deepnote was incredibly easy to set up and allows us to start new notebooks in seconds. Working together with Deepnote gives us a great window into the ways candidates approach the interview problem.
Head of Data Science
Since metrics require a lot of input from subject matter experts, data consumers, and business stakeholders to define and align on definitions, we needed a collaborative layer where we could get immediate feedback.
Head of Analytics Engineering