Deepnote

Deepnote is a cloud-based data workspace that combines notebooks, SQL, AI assistance, and collaboration tools into a single platform. The homepage states it is used by 500,000+ data professionals and is now open-source under the Apache 2.0 license. It positions itself as a modern alternative to Jupyter, Google Colab, and Databricks, with built-in multiplayer editing, AI code generation, and one-click data app publishing.

What It Is

Deepnote is a collaborative notebook environment designed for data analytics, data engineering, and machine learning workflows. It supports Python, SQL, and R in a single IDE, lets teams build interactive dashboards and data apps without leaving the notebook, and connects to 60+ data sources including Snowflake, BigQuery, Redshift, and Databricks. The platform runs entirely in the cloud, eliminating local environment setup, and offers scheduling, GPU compute, and notebook-as-API deployment out of the box.

Open-Source Transition

The homepage prominently announces "Deepnote is now open-source!" under the Apache 2.0 license. A quote from the CEO of AlphaSignal on the homepage describes it as "Jupyter, but with SQL, AI, and multiplayer mode, among other handy features." This transition signals a significant product-direction shift, making the core notebook format publicly available while the hosted platform retains commercial tiers.

AI Capabilities Built Into the Workflow

Deepnote AI is woven throughout the product rather than bolted on as a sidebar:

• Auto AI: describe what you want to analyze and Deepnote queries, analyzes, and interprets data automatically
• Code generation, explanation, refactoring, and debugging aware of your code context and data stack
• AI code completion in Python and SQL
• Autonomous data agents: the platform supports building agents that can query, train models, deploy endpoints, and visualize results across multiple notebook cells
• MCP and Google A2A integration for connecting agents to external tools
• Enterprise plans support bring-your-own-LLM and access to GPT-5 and Sonnet 4.6

Collaboration and Deployment Architecture

Deepnote runs notebooks in the cloud with real-time multiplayer editing, inline commenting, and version history. Teams can share work via link or email invite, organize projects in folders, and publish notebooks as white-labeled data apps or dashboards. Compute options range from basic 2 vCPU / 5 GB RAM machines to high-memory (128 GB RAM, 16 vCPU) and GPU (12 GB K80) instances. The platform also supports:

• Scheduled notebook runs (hourly, daily, weekly, monthly)
• Notebook API deployment for model serving
• Spark and Snowpark for terabyte-scale workloads
• VS Code and Cursor integrations for local-to-cloud workflows

Security and Enterprise Readiness

Deepnote is SOC 2 Type II certified and HIPAA and GDPR compliant. Enterprise features include SSO via SAML or OIDC, SCIM directory sync, role-based access control, permission groups, audit logs, federated warehouse authentication, static IPs, SSH tunnels, and private Docker image support. Deployment options span multi-tenant, single-tenant (managed by Deepnote or self-hosted), and on-premise behind a customer's firewall. The enterprise page notes Deepnote was listed as a Sample Vendor in the Gartner® Hype Cycle™ for Analytics and Business Intelligence for 2024.

Audience and Adoption Signals

The platform targets data analysts, data scientists, data engineers, and ML engineers, and the homepage claims use at 96 of the top 100 universities. Vendor-published testimonials on the homepage include users from SoundCloud, Gusto, Statsig, and Floryn. The explore gallery covers use cases from NPS analysis and A/B testing to protein visualization, LLM applications, and fraud detection agents, reflecting a broad practitioner audience across fintech, biotech, gaming, and enterprise segments.