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vizro-core/README.md

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+#### Vizro is a low-code toolkit for building high-quality data visualization apps
 
 [![Python version](https://img.shields.io/badge/python-3.9%20%7C%203.10%20%7C%203.11%20%7C%203.12%20%7C%203.13-blue.svg)](https://pypi.org/project/vizro/) [![PyPI version](https://badge.fury.io/py/vizro.svg)](https://badge.fury.io/py/vizro) [![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/mckinsey/vizro/blob/main/LICENSE.md) [![Documentation](https://readthedocs.org/projects/vizro/badge/?version=stable)](https://vizro.readthedocs.io/) [![OpenSSF Best Practices](https://www.bestpractices.dev/projects/7858/badge)](https://www.bestpractices.dev/projects/7858)
 
+[Documentation](https://vizro.readthedocs.io/en/stable/) | [Get Started](https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/) | [Vizro examples gallery](http://vizro.mckinsey.com/)
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+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_spash_teaser.gif" width="600"/>
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+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/logo_watermarks.svg" width="300">
 </div>
 
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+## What is Vizro?
+
+Vizro is an open-source Python-based toolkit.
+
+Use it to build beautiful and powerful data visualization apps quickly and easily, without needing advanced engineering or visual design expertise.
 
-<a href="https://vizro.readthedocs.io/en/stable/" target="_blank">Documentation </a> | <a href="https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/" target="_blank">Get Started </a> | <a href="http://vizro.mckinsey.com/" target="_blank">Vizro examples gallery</a>
+Then customize and deploy your app to production at scale.
 
+<div align="center">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="100%"/>
+Use a few lines of simple low-code configuration, with in-built visual design best practices, to assemble high-quality
+multi-page prototypes.
 </div>
+<br>
 
----
+The benefits of the Vizro toolkit include:
 
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-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_spash_teaser.gif" width="600"/>
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-<b>
-Visual Intelligence. Beautifully engineered
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-Vizro is a toolkit for creating modular data visualization applications
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-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/tech_logos.png" width="270"/>
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+<div align="center">
+<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/infographic.svg" width="800"/>
+</div>
+<br>
 
-## What is Vizro?
+Visit our ["How-to guides"](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for a more detailed explanation of Vizro features.
+
+## Why use Vizro?
+
+Vizro helps you to build data visualization apps that are:
+
+**Quick and easy**
 
-<p align="left">
-<font size="+1">
-Rapidly self-serve the assembly of customized dashboards in minutes - without the need for advanced coding or design experience - to create flexible and scalable, Python enabled data visualization applications
-</font>
-</p>
+Build apps in minutes. Use a few lines of simple configuration (via Pydantic models, JSON, YAML, or Python dictionaries) in place of thousands of lines of code.
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/code_dashboard.png" width="1300"/>
-</p>
+**Beautiful and powerful**
 
-Use a few lines of simple configuration to create complex dashboards, which are automatically assembled utilizing libraries such as [**Plotly**](https://github.com/plotly/plotly.py) and [**Dash**](https://github.com/plotly/dash), with inbuilt coding and design best practices
+Build high-quality multi-page apps without needing advanced engineering or visual design expertise. Use powerful features of production-grade BI tools, with in-built visual design best practices.
 
-Define high level categories within the configuration, including:
+**Flexible**
 
-- **components:** create charts, tables, input/output interfaces, and more
-- **controls**: create filters, parameter inputs, and custom action controllers
-- **pages, layouts and navigation**: create multiple pages, with customizable layouts and flexible navigation across them
-- **actions and interactions**: create interactions between charts, and use pre-defined or customized actions (such as exporting)
+Benefit from the capabilities and flexibility of open-source packages. Use the trusted dependencies of Plotly, Dash, and Pydantic.
 
-Configuration can be written in multiple formats including **Pydantic models**, **JSON**, **YAML** or **Python dictionaries** for added flexibility of implementation
+**Customizable**
 
-Optional high-code extensions allow almost infinite customization in a modular way, combining the best of low-code and high-code - for flexible and scalable, Python enabled data visualization applications
+Almost infinite control for advanced users. Use Python, JavaScript, HTML and CSS code extensions.
 
-(Visit the ["Why Vizro"](https://vizro.readthedocs.io/en/latest/pages/explanation/why_vizro/) section to see a more detailed explanation of Vizro use cases)
+**Scalable**
 
-<br/>
+Rapidly prototype and deploy to production. Use the in-built production-grade capabilities of Plotly, Dash and Pydantic.
 
-## Key benefits of Vizro
+Visit ["Why should I use Vizro?"](https://vizro.readthedocs.io/en/stable/pages/explanation/faq/#why-should-i-use-vizro) for a more detailed explanation of Vizro use cases.
 
-<br/>
+## When to use Vizro?
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/value_prop_icons.png" width="900"/>
-</p>
+Use Vizro when you need to combine the speed and ease of low-code Python tools, with production capabilities of JavaScript and BI tools, and the freedom of open source:
 
-<br/>
+- Have an app that looks beautiful and professional by default.
+- Enjoy the simplicity of low-code, plus the option to customize with code almost infinitely.
+- Rapidly create prototypes which are production-ready and easy to deploy at scale.
 
-## Vizro examples gallery
+## How to use Vizro?
 
-You can see Vizro in action by clicking on the following image or by visiting [the examples gallery at vizro.mckinsey.com](https://vizro.mckinsey.com).
+### [Vizro framework](https://vizro.readthedocs.io/en/stable/)
 
-<a href="http://vizro.mckinsey.com/">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/vizro_examples_gallery.png" width="550">
-</a>
+**Low-code framework for building dashboards**
 
-## Visual vocabulary
+The Vizro framework underpins the entire Vizro toolkit. It is a Python package (called `vizro`).
 
-Our visual vocabulary dashboard helps you to select and create various types of charts. It helps you decide when to use each chart type, and offers sample Python code to create these charts with [Plotly](https://plotly.com/python/) and embed them into a Vizro dashboard.
+Visit the [documentation](https://vizro.readthedocs.io/en/stable/) for more details.
 
-<a href="https://vizro-demo-visual-vocabulary.hf.space">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/visual_vocabulary.png" width="550">
-</a>
+### [Visual vocabulary](https://vizro-demo-visual-vocabulary.hf.space/)
 
-## Dashboard screenshots
+**Chart examples**
 
-<p align="center">
-<img src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/dashboard_examples.png" width="1300"/>
-</p>
+The visual vocabulary helps you to decide which chart type to use for your requirements, and offers sample code to create these charts with Plotly or embed them into a Vizro dashboard.
 
-## Installation
+Visit the [visual vocabulary](https://vizro-demo-visual-vocabulary.hf.space/) to search for charts or get inspiration.
+
+<img width="600" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_visual_vocabulary.png">
+
+### [Vizro examples gallery](https://vizro.mckinsey.com/)
+
+**Dashboard examples**
+
+The dashboard examples gallery enables you to explore Vizro in action by viewing interactive example apps. You can copy the code to use as a template or starter for your next dashboard.
+
+Visit the [dashboard examples gallery](https://vizro.mckinsey.com/) to see the dashboards in action.
+
+<img width="600" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_dashboard_examples.png">
+
+### [Vizro-AI](https://vizro.readthedocs.io/projects/vizro-ai)
+
+**LLM generated charts and dashboards**
+
+Vizro-AI is a separate package (called `vizro_ai`) that extends Vizro to incorporate LLMs. Use it to build interactive Vizro charts and dashboards, by simply describing what you need in plain English or other languages.
+
+Visit the [Vizro-AI documentation](https://vizro.readthedocs.io/projects/vizro-ai/) for more details.
+
+<img width="600" src="https://raw.githubusercontent.com/mckinsey/vizro/main/.github/images/toolkit_vizro_ai.gif">
+
+## Installation and first steps
 
 ```console
 pip install vizro
 ```
 
-See the [Install guide](https://vizro.readthedocs.io/en/stable/pages/user_guides/install/) for more information
-
-Please note this repository is a monorepo and the core `vizro` package can be found in [/vizro-core](https://github.com/mckinsey/vizro/tree/main/vizro-core)
+See the [installation guide](https://vizro.readthedocs.io/en/stable/pages/user-guides/install/) for more information.
 
-## Getting started
+The [get started documentation](https://vizro.readthedocs.io/en/stable/pages/tutorials/first-dashboard/) explains how to create your first dashboard.
 
-See the [Tutorials](https://vizro.readthedocs.io/en/stable/pages/tutorials/first_dashboard/) for creating your first dashboard
+## Packages
 
-## Documentation
+This repository is a monorepo containing the following packages:
 
-See the [Documentation](https://vizro.readthedocs.io/en/stable/) for more details
+|           Folder           |                                           Version                                           |                          Documentation                           |
+| :------------------------: | :-----------------------------------------------------------------------------------------: | :--------------------------------------------------------------: |
+| [vizro-core](./vizro-core) |    [![PyPI version](https://badge.fury.io/py/vizro.svg)](https://badge.fury.io/py/vizro)    |      [Vizro Docs](https://vizro.readthedocs.io/en/stable/)       |
+|   [vizro-ai](./vizro-ai)   | [![PyPI version](https://badge.fury.io/py/vizro-ai.svg)](https://badge.fury.io/py/vizro-ai) | [Vizro-AI Docs](https://vizro.readthedocs.io/projects/vizro-ai/) |
 
-## Community and Development
+## Community and development
 
-We encourage you to ask and answer technical questions via the [GitHub Issues](https://github.com/mckinsey/vizro/issues). This is also the place where you can submit bug reports or request new features.
+We encourage you to ask and discuss any technical questions via the [GitHub Issues](https://github.com/mckinsey/vizro/issues). This is also the place where you can submit bug reports or request new features.
 
-## Contributing
+## Want to contribute to Vizro?
 
-To learn more about making a contribution, please see the [contributing guide](https://vizro.readthedocs.io/en/stable/pages/development/contributing/) for more information
+The [contributing guide](https://vizro.readthedocs.io/en/stable/pages/explanation/contributing/) explains how you can contribute to Vizro.
 
-You can also view current and former [contributors](https://vizro.readthedocs.io/en/stable/pages/development/authors/)
+You can also view current and former contributors [here](https://vizro.readthedocs.io/en/stable/pages/explanation/authors/).
 
-## Reporting a Security Vulnerability
+## Want to report a security vulnerability?
 
-Please see our [security policy](https://github.com/mckinsey/vizro/security/policy)
+See our [security policy](https://github.com/mckinsey/vizro/security/policy).
 
 ## License
 
-`vizro` is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+`vizro` is distributed under the terms of the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).