About Deepnote

Deepnote is a collaborative data science notebook that integrates Python, SQL, and R, allowing users to create data apps and dashboards without extensive coding skills. It enables teams to analyze and visualize data from various sources in real-time, enhancing productivity and collaboration in data-driven projects.

```xml <problem> Data scientists and analysts often struggle with fragmented workflows, relying on multiple tools for coding, data exploration, and collaboration. Traditional data science notebooks lack native support for real-time collaboration, version control, and seamless integration with various data sources, hindering productivity and efficient data-driven decision-making. </problem> <solution> Deepnote is an AI-powered collaborative data workspace that unifies data science workflows by integrating Python, SQL, and R in a single environment. The platform allows users to create interactive data apps and dashboards with or without extensive coding. Deepnote connects to various data sources, including Snowflake and BigQuery, enabling real-time data analysis and visualization. Its AI capabilities, powered by GPT-4o, automate code generation, debugging, and data interpretation, accelerating the data analysis process. The platform's collaborative features, such as commenting, version control, and sharing, streamline teamwork and knowledge sharing. </solution> <features> - AI-powered assistance for code generation, debugging, and data interpretation using GPT-4o - Support for Python, SQL, and R programming languages within a unified interface - Real-time collaboration features, including commenting, version control, and shared workspaces - Native integration with data warehouses, databases, and lakehouses, including Snowflake, BigQuery, and CSV files - Interactive data visualization tools for creating no-code configurable charts - Data app and dashboard creation capabilities with custom layouts, input blocks, and buttons - Notebook scheduling for automated execution of data pipelines on an hourly, daily, or weekly basis - Notebook deployment as APIs for serving models directly in production - Support for running notebooks on CPUs and GPUs - Role-Based Access Control (RBAC), Single Sign-On (SSO), and directory sync for enhanced data security and compliance (HIPAA, SOC 2, GDPR) </features> <target_audience> Deepnote primarily targets data scientists, data analysts, and other data professionals who require a collaborative and integrated environment for data exploration, analysis, and application development. </target_audience> ```

What does Deepnote do?

Where is Deepnote located?

Deepnote is based in San Francisco, United States.

When was Deepnote founded?

Deepnote was founded in 2019.

How much funding has Deepnote raised?

Deepnote has raised 23800000.

Location

San Francisco, United States

Founded

2019

Funding

23800000

Employees

37 employees

Major Investors

Index Ventures, Accel

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Deepnote

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Executive Summary

deepnote.com 7K+

Crunchbase

Founded 2019 – San Francisco, United States

Funding

Estimated Funding

$20M+

Major Investors

Index Ventures, Accel

Team (30+)

No team information available.

Company Description

Problem

Data scientists and analysts often struggle with fragmented workflows, relying on multiple tools for coding, data exploration, and collaboration. Traditional data science notebooks lack native support for real-time collaboration, version control, and seamless integration with various data sources, hindering productivity and efficient data-driven decision-making.

Solution

Deepnote is an AI-powered collaborative data workspace that unifies data science workflows by integrating Python, SQL, and R in a single environment. The platform allows users to create interactive data apps and dashboards with or without extensive coding. Deepnote connects to various data sources, including Snowflake and BigQuery, enabling real-time data analysis and visualization. Its AI capabilities, powered by GPT-4o, automate code generation, debugging, and data interpretation, accelerating the data analysis process. The platform's collaborative features, such as commenting, version control, and sharing, streamline teamwork and knowledge sharing.

Features

AI-powered assistance for code generation, debugging, and data interpretation using GPT-4o

Support for Python, SQL, and R programming languages within a unified interface

Real-time collaboration features, including commenting, version control, and shared workspaces

Native integration with data warehouses, databases, and lakehouses, including Snowflake, BigQuery, and CSV files

Interactive data visualization tools for creating no-code configurable charts

Data app and dashboard creation capabilities with custom layouts, input blocks, and buttons

Notebook scheduling for automated execution of data pipelines on an hourly, daily, or weekly basis

Notebook deployment as APIs for serving models directly in production

Support for running notebooks on CPUs and GPUs

Role-Based Access Control (RBAC), Single Sign-On (SSO), and directory sync for enhanced data security and compliance (HIPAA, SOC 2, GDPR)

Target Audience

Deepnote primarily targets data scientists, data analysts, and other data professionals who require a collaborative and integrated environment for data exploration, analysis, and application development.