Hex is a connected platform for using AI to work with data. It allows users to ask questions in natural language, partner with agents for better analysis, and curate context for trusted answers.

What can I do with Hex?

Hex enables deep data analysis, governed self-service analytics, and the creation of trusted data context. It helps make everyone in an organization a data person.

What type of analysis does Hex support?

Hex supports a wide range of data analysis, from asking questions in natural language to partnering with AI agents for more in-depth exploration.

What technologies does Hex utilize?

Hex utilizes AI to work with data, and supports languages such as Python and SQL.

Who is Hex designed for?

Hex is designed to make everyone a data person, suggesting it's built for a wide range of users within an organization, regardless of their technical expertise.

Hex

Name: Hex
Rating: 4 (53 reviews)

Hex is a connected platform for using AI to work with data, offering deep analysis, governed self-serve, and trusted context.

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Published: 2025/12/14

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Introduction

Hex is a connected platform designed to revolutionize how teams work with data, leveraging AI to empower everyone within an organization. It combines deep analysis, governed self-serve capabilities, and trusted context to provide accurate answers to critical data questions.

Key features include:

AI and Agents: Agentic data workflows powered by leading LLMs.
Notebooks: Powerful environment for deep-dive analysis, supporting SQL, Python, and no-code approaches.
Data Apps: Build and share interactive dashboards and reporting.
Threads: AI-powered conversational self-serve for broad accessibility.
Context Curation: Semantic models and AI governance to build trust in data.
Collaboration: Real-time multiplayer editing, commenting, and versioning.

Hex targets data teams and data-driven organizations aiming to democratize data access and ensure reliable insights. It uniquely combines advanced analytics with AI-driven self-service, fostering a data-literate culture.

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JupyterLab
As a web-based interactive development environment, it allows users to work with notebooks, code, and data in a flexible and extensible manner.
Google Colaboratory
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Mode Analytics
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Dataiku
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Amazon SageMaker Studio
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Domino Data Lab
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Count
This collaborative data analysis platform focuses on SQL and Python notebooks, facilitating interactive data exploration and storytelling within teams.
Microsoft Azure Machine Learning Studio
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User Reviews

4.0/5.0

(53reviews)

Click stars to rate

Pricing

Pricing Model: Freemium

Community

For hobbyists completing small projects and showcasing work.

Free

Professional

For individuals accelerating data insights and solo workflows.

$36 per Editor / month

monthly

Team

For companies collaborating with data and automating manual work.

$75 per Editor / month

monthly

Enterprise

For organizations requiring advanced security, governance, and support.

Custom

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Introduction

Key features include:

AI and Agents: Agentic data workflows powered by leading LLMs.
Notebooks: Powerful environment for deep-dive analysis, supporting SQL, Python, and no-code approaches.
Data Apps: Build and share interactive dashboards and reporting.
Threads: AI-powered conversational self-serve for broad accessibility.
Context Curation: Semantic models and AI governance to build trust in data.
Collaboration: Real-time multiplayer editing, commenting, and versioning.

Alternatives

Databricks

It offers a unified data and AI platform with collaborative notebooks, Spark, and MLflow for end-to-end data science workflows.

Deepnote

This collaborative data science notebook platform provides a modern interface and real-time collaboration features for data analysis and machine learning.

JupyterLab

As a web-based interactive development environment, it allows users to work with notebooks, code, and data in a flexible and extensible manner.

Google Colaboratory

A free, cloud-based Jupyter notebook environment that enables collaborative data analysis and machine learning with zero setup.

Mode Analytics

It integrates SQL, Python/R notebooks, and interactive dashboards into a single platform for collaborative data exploration and reporting.

Dataiku

This end-to-end platform empowers data professionals to build, deploy, and manage AI solutions through a collaborative and visual interface.

Amazon SageMaker Studio

An integrated development environment (IDE) for machine learning on AWS, providing tools for building, training, and deploying models.

Domino Data Lab

An enterprise MLOps platform that offers a collaborative data science workbench for developing, deploying, and managing models at scale.

Count

This collaborative data analysis platform focuses on SQL and Python notebooks, facilitating interactive data exploration and storytelling within teams.

Microsoft Azure Machine Learning Studio

It provides a comprehensive set of tools and services for the entire machine learning lifecycle, from data preparation to model deployment on Azure.

Pricing

Pricing Model: Freemium

Community

For hobbyists completing small projects and showcasing work.

Free

Professional

For individuals accelerating data insights and solo workflows.

$36 per Editor / month

monthly

Team

For companies collaborating with data and automating manual work.

$75 per Editor / month

monthly

Enterprise

For organizations requiring advanced security, governance, and support.

Custom

Hex

Introduction

Alternatives

Databricks

Deepnote

JupyterLab

Google Colaboratory

Mode Analytics

Dataiku

Amazon SageMaker Studio

Domino Data Lab

Count

Microsoft Azure Machine Learning Studio

User Reviews

Pricing

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