Deepnote
Free tierThe collaborative data workspace built for humans and AI agents
Free tier available·All audiences·API available·Open source
Key strengths
Collaborative notebooks with multiplayer modePython & SQL in the same notebookAI-powered data analysis and agents100+ data source integrationsData apps and dashboardsScheduled notebooks and pipeline automationGPU support for ML workloadsSOC2, HIPAA, and GDPR complianceMCP support for agent workflows
Free tier + paid plans · from $39 USD/mo
San Francisco, USA
Founded 2019
Self-hostable
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Recent changes
- Plans updated: Free plan (up to 3 editors, 5 projects, limited AI). Team plan at $39/editor/month billed yearly (14-day free trial). Enterprise plan at custom pricing.
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Deepnote — Technical Use Cases
- Collaborative EDA & model development — data scientists and ML engineers work together in multiplayer notebooks, combining Python for modelling and SQL for data retrieval in a single environment
- ML pipeline automation — schedule notebook runs to retrain models, generate evaluation reports, or refresh feature stores on a recurring basis
- GPU-accelerated ML workloads — run training and inference jobs directly in Deepnote's GPU-enabled compute environments without provisioning separate infrastructure
- Agent-driven data workflows — leverage MCP support to build AI agent pipelines that query, transform, and analyse data programmatically
- dbt & LookML integration — embed dbt model runs or LookML queries into notebooks for end-to-end analytics engineering workflows
- Data app development — build and publish interactive data applications and dashboards directly from notebooks, reducing the need for separate front-end tooling
- Multi-source data pipelines — connect BigQuery, Snowflake, Spark, Snowpark, Salesforce, and AWS within a single workspace to orchestrate cross-source analysis
- Compliant enterprise deployments — self-host Deepnote on internal infrastructure to meet SOC2, HIPAA, or GDPR requirements, with API access for integration into existing toolchains
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