Deepnote: Analytics and data science notebook for teams.

Explore data with Python & SQL, work together with your team, and share insights that lead to action — all in one place with Deepnote.

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Deepnote is now open-source! Star us on GitHub ⭐️

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Jupyter notebook for the AI era

Notebooks, data apps, dashboards
No-code, Python, SQL, R
Snowflake, BigQuery, and 60+ data sources

500,000+500,000+data professionals

AI superpowers for everydata analystanddata scientist

Become a senior data analyst overnight

Describe what you want to do and Deepnote will automagically query, analyze, and interpret data for you. No coding skills necessary.

Deepnote understands your business context and your data stack to deliver high-quality analyses fast.

See in action

Write Python, SQL, R...

Enhance your productivity by using your favorite languages and tools in a single AI-enabled IDE.

...or let Python, SQL, R be written for you

Aware of your code, context, and metadata. Deepnote continuously adapts to turbocharge your work.

Refactor code

Generate code

Explain code

Code completion

Debug & fix

From quick explorations to powerful data apps

Quick explorations
Notebooks
Data apps
Dashboards
ETL pipelines
Data catalog
Knowledge base
Sales report
Customer 360
Churn prediction model
Lead scoring
Sync Salesforce to Notion
A/B test evaluation
AWS cost analysis
NPS analysis
Fine-tune LLaMA 7B
Protein visualization
Forecast sales pipeline

Interactive visualizations

Instantly visualize dataframes as no-code configurable charts.

Beautiful apps & dashboards

Deepnote turns quick data explorations into impressive reports & apps. See some examples.

Arrange into custom layouts

Hide code blocks

Add input blocks and buttons

Schedule notebooks

Schedule notebooks to run hourly, daily, weekly, or monthly.

Deploy notebooks as APIs

Put your notebook into production. Serve your models directly.

Run on powerful GPUs

Choose what kind of hardware you want to use, from CPUs to big GPUs.

Collaborate with the whole team

Deepnote runs seamlessly in the cloud, making environment management and collaboration with your team a non-issue. And sharing work is as easy as sending a link or email invite.

Product manager

Organize your work

Build a library of data projects sorted by folders so teammates can get needed information fast.

Comment, review, version

Have your team comment on blocks to ask questions, provide feedback, and work faster.

Data scientist

Sharing made simple

Share your work with others by simply sending a link or email invite. Or use advanced permission models.

100s of integrations

Connect to your data in seconds with built-in integrations for the most popular warehouses, databases, and lakehouses.

Based on open standards & extensible APIs

See all integrations →

dbt metadata

Run your queries with Jinja in Deepnote’s SQL blocks and browse your company metrics right next to your warehouse schema.

Drag and drop your CSVs

And use them like any other data source.

Spark & Snowpark

Work with terabyte-scale data. Connect to your own cluster or spin up serverless Spark clusters on demand.

Improve your data security with Deepnote

Security gets better and easier with Deepnote. Stop exporting CSVs and taking screenshots of sensitive data. With Deepnote, you have complete control over data access and security.

Secure & compliant

All data is secure and encrypted. Deepnote is compliant with HIPAA and SOC 2, GDPR, and more.

RBAC, SSO, directory sync

Control who can access data and code. Enjoy single sign-on via SAML or OIDC connections and sync your directory.

Custom deployments

Get a secure, compliant, and fully managed Deepnote instance orbook a demoto learn about all deployment options.

What makes Deepnote so secure?

Discover how we mitigate risks and protect your data using industry best practices and continuous improvements.

Loved by a community of 500,000+ data professionals

I knew I’d made the right decision when I started getting feedback from data scientists about how delightful their user experience was.

Working in Deepnote is like code review and rapid prototyping at the same time, saving valuable time in the iteration cycles.

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.

Collaborative data analysis where team members can freely share their work and get feedback… This made the analysis workflow much faster.

Delightful user experience reminds me of Superhuman with the command palette and constant reminders of how to use hotkeys to work more efficiently.

I just love how SQL is now a first-class citizen in Deepnote notebooks! 🔥 It is SO easy to query databases!

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.

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.

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.

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.