Deepnote
Deepnote is a cloud-based data workspace that combines a Jupyter-compatible notebook environment with AI agents, dashboards, and data app publishing.
Profile
A cloud-based data workspace where teams write Python, SQL, and R in collaborative notebooks, build dashboards, and deploy autonomous AI agents that query data and trigger actions.
Deepnote is a cloud-based data workspace that combines a Jupyter-compatible notebook environment with AI agents, dashboards, and data app publishing. Founded in 2019 by Jakub Jurovych and Matej Ftáčnik, the company emerged from Y Combinator and has raised at least $23.8 million in disclosed venture funding from Index Ventures, Accel, Credo Ventures, and angel investors including OpenAI’s Greg Brockman. The platform targets data scientists and analysts who want to write Python, SQL, or R in a collaborative IDE, then deploy interactive dashboards or autonomous data agents without leaving the browser.
As of mid-2026, Deepnote claims 500,000+ data professionals on the platform, with weekly signups of 128,000 (up 12%) and an activation rate of 41%. The company’s internal metrics show 742 accounts flagged as “at risk” (down 18%), and a pipeline of 47 enterprise accounts, 31 startup accounts, and 92 self-serve accounts in the last 30 days. Deepnote has not disclosed revenue, headcount, or a valuation since its 2022 Series A.
The product has shifted from a pure notebook tool toward an “AI-native” workspace where users can build agents that query databases, train models, deploy endpoints, and visualize results — all from within the notebook. The company’s research page openly shares internal A/B test results (e.g., a churn analysis showing a treatment group had 85% higher churn) and product usage data, an unusual level of transparency. Deepnote competes with Hex, Databricks Notebooks, and Google Colab, but differentiates by emphasizing agentic workflows and a CLI integration with Claude Code. No major controversies or leadership changes are publicly documented, but the company remains relatively small compared to incumbents and has not disclosed a path to profitability.
Who buys this
- Data science and analytics teams at mid-market companies
- Startups building data-intensive products or internal tools
- Enterprise data teams needing governed, collaborative notebook environments
- Individual data professionals and freelancers
Strengths and what to watch
Strengths
- Deepnote’s internal metrics show strong growth: 128,000 weekly signups (up 12%), 41% activation rate, and a pipeline of 47 enterprise accounts in the last 30 days.
- The platform integrates AI agents that can autonomously query databases, train models, deploy endpoints, and generate charts — all within the notebook, reducing context-switching.
- Deepnote publishes detailed internal product usage data and A/B test results publicly, signaling a data-driven culture and transparency that builds trust with technical buyers.
Watch for
- Deepnote has not disclosed revenue, headcount, or a valuation since its $20 million Series A in January 2022, making it difficult to assess financial health or growth trajectory.
- The company faces intense competition from well-funded rivals like Hex, Databricks, and Google Colab, each with larger sales teams and existing enterprise relationships.
- With 742 accounts flagged as “at risk” and a churn analysis showing a treatment group had 85% higher churn, Deepnote may struggle to retain users who skip onboarding or fail to adopt the platform as a daily tool.
Key Information
- Industry
- Data Science Notebooks
- Founded
- 2019
Frequently Asked Questions
What is Deepnote?
Deepnote is a cloud-based data workspace where teams write Python, SQL, and R in collaborative notebooks. It also lets you build dashboards, deploy data apps, and use autonomous AI agents that query databases and trigger actions, all from the browser.
How do Deepnote AI agents work?
Deepnote AI agents autonomously query databases, train models, deploy endpoints, and generate charts within the notebook. They reduce context-switching by handling data tasks and triggering actions, making it easier for data professionals to focus on analysis without leaving the workspace.
Who is Deepnote for?
Deepnote targets data scientists, analysts, and teams at mid-market companies, startups, and enterprises. It serves individual freelancers as well as groups needing a governed, collaborative environment for Python, SQL, or R work, with integrated AI agents and dashboards.
How does Deepnote compare to Hex or Databricks Notebooks?
Deepnote competes with Hex, Databricks Notebooks, and Google Colab. It differentiates by emphasizing agentic workflows, a CLI integration with Claude Code, and a transparent culture of sharing internal metrics. However, rivals have larger sales teams and enterprise relationships.
What internal metrics does Deepnote share publicly?
Deepnote publishes weekly signups (128,000, up 12%), an activation rate of 41%, and a pipeline of 47 enterprise accounts. It also shares A/B test results, like a churn analysis where a treatment group had 85% higher churn, showing unusual transparency.
What are Deepnote's strengths and risks?
Strengths include strong signup growth, integrated AI agents, and public data sharing. Risks involve undisclosed revenue since 2022, intense competition from Hex and Databricks, and 742 at-risk accounts, plus a churn analysis showing potential retention issues.
Sources
- deepnote.com — Product description, internal metrics (weekly signups, activation rate, at-risk accounts, pipeline by segment), and feature set (AI agents, dashboards, CLI integration with Claude Code).
- deepnote.com — Internal A/B test results showing churn analysis with treatment group having 85% higher churn, and product usage data.
- techcrunch.com — Series A funding of $20 million co-led by Index Ventures and Accel, with participation from Y Combinator and Credo Ventures.
- techcrunch.com — Seed round of $3.8 million led by Index Ventures and Accel, with participation from Y Combinator, Credo Ventures, and angel investors including Greg Brockman.