Update readme

README.md

@@ -1,33 +1,21 @@
 # ![logo](docs/media/favicon.ico) GreatAI
  
- > GreatAI helps you easily transform your prototype AI code into production-ready software.
-
 [![Sonar line coverage](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=coverage)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
-[![Sonar technical debt](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=sqale_index)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
 [![Sonar LoC](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=ncloc)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
 [![Test](https://github.com/schmelczer/great-ai/actions/workflows/test.yml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/test.yml)
-[![Publish on PyPI](https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml)
+[![PyPI version](https://badge.fury.io/py/great-ai.svg)](https://badge.fury.io/py/great-ai)
-[![Publish on DockerHub](https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml)
 [![Downloads](https://pepy.tech/badge/great-ai/month)](https://pepy.tech/project/great-ai)
+![Docker Pulls](https://img.shields.io/docker/pulls/schmelczera/great-ai)
 
-[Check out the documentation here](https://great-ai.scoutinscience.com/).
+GreatAI helps you easily transform your prototype AI code into production-ready software.
-
+[Check out the full documentation here](https://great-ai.scoutinscience.com).
-
-## Find `great-ai` on [DockerHub](https://hub.docker.com/repository/docker/schmelczera/great-ai)
-
-```sh
-docker run -p6060:6060 schmelczera/great-ai
-```
-
-Find the dashboard at [http://localhost:6060](http://localhost:6060/dashboard/).
-
-
-## Find `great-ai` on [PyPI](https://pypi.org/project/great-ai/)
 
 ```sh
 pip install great-ai
 ```
 
+> Create a new file called `main.py`
+
 ```python
 from great_ai import GreatAI
 
@@ -35,19 +23,46 @@ from great_ai import GreatAI
 def hello_world(name: str) -> str:
     return f"Hello {name}!"
 ```
-> Create a new file called `main.py`
 
-Deploy by executing `great-ai main.py`
+Start it by executing `great-ai main.py`, find the dashboard at [http://localhost:6060](http://localhost:6060/dashboard).
-> Or: `great_ai main.py`
 
-> Or: `python3 -m great_ai main.py`
+![dashboard](/docs/media/hello-world-dashboard.png)
 
-Find the dashboard at [http://localhost:6060](http://localhost:6060/dashboard/).
+That's it. Your GreatAI service is ready for production use. Many of the [SE4ML best-practices](https://se-ml.github.io) are configured and implemented automatically (of course, these can be customised as well).
 
-### Contribute
+## Why is this GREAT?
 
+![scope of GreatAI](docs/media/scope-simple.drawio.svg)
 
-#### Install
+GreatAI fits between the prototype and deployment phases of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:
+
+- **G**eneral: use any Python library without restriction
+- **R**obust: have error-handling and well-tested utilities out-of-the-box 
+- **E**nd-to-end: utilise end-to-end feedback as a built-in, first-class concept
+- **A**utomated: focus only on what actually requires your attention
+- **T**rustworthy: deploy models that you and society can confidently trust
+
+## Why GreatAI?
+
+There are other, existing solutions aiming to facilitate this phase. [Amazon SageMaker](https://aws.amazon.com/sagemaker) and [Seldon Core](https://www.seldon.io/solutions/open-source-projects/core) provide the most comprehensive suite of features. If you have the opportunity use those, do that because they're great.
+
+However, [research indicates](https://great-ai.scoutinscience.com) that professionals rarely use them. This may be due to their inherent setup and operating complexity. **GreatAI is designed to be as simple to use as possible.** Its clear, high-level API and sensible default configuration makes it extremely easy to start using. Despite its relative simplicity over Seldon Core, it still implements many of the [SE4ML best-practices](https://se-ml.github.io), and thus, can meaningfully improve your deployment without requiring prohibitively large effort.
+
+## Find `great-ai` on [DockerHub](https://hub.docker.com/repository/docker/schmelczera/great-ai)
+
+```sh
+docker run -p6060:6060 schmelczera/great-ai
+```
+
+## Learn more
+
+[Check out the documentation](https://great-ai.scoutinscience.com).
+
+## Contribute
+
+Contributions are welcome.
+
+### Install for development
 
 ```sh
 python3 -m venv --copies .env
@@ -56,8 +71,8 @@ python3 -m pip install flit
 python3 -m flit install --symlink --deps=all
 ```
 
-#### Documentation
+### Serve documentation
 
 ```sh
 mkdocs serve --dirtyreload
-```
+```

docs/index.md

@@ -4,12 +4,12 @@
 </div>
 
 [![Sonar line coverage](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=coverage)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
-[![Sonar technical debt](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=sqale_index)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
 [![Sonar LoC](https://sonar.scoutinscience.com/api/project_badges/measure?project=great-ai&metric=ncloc)](https://sonar.scoutinscience.com/dashboard?id=great-ai)
 [![Test](https://github.com/schmelczer/great-ai/actions/workflows/test.yml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/test.yml)
-[![Publish on PyPI](https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/publish.yaml)
+[![PyPI version](https://badge.fury.io/py/great-ai.svg)](https://badge.fury.io/py/great-ai)
-[![Publish on DockerHub](https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml/badge.svg)](https://github.com/schmelczer/great-ai/actions/workflows/docker.yaml)
 [![Downloads](https://pepy.tech/badge/great-ai/month)](https://pepy.tech/project/great-ai)
+![Docker Pulls](https://img.shields.io/docker/pulls/schmelczera/great-ai)
+
 
 Applying AI is becoming increasingly easier but many case studies have shown that these applications are often deployed poorly. This may lead to suboptimal performance and to introducing [unintended biases](https://en.wikipedia.org/wiki/Weapons_of_Math_Destruction){ target=_blank }. GreatAI helps fixing this by allowing you to ==easily transform your prototype AI code into production-ready software==.
 
@@ -42,6 +42,7 @@ Applying AI is becoming increasingly easier but many case studies have shown tha
 - [x] Deployable Jupyter Notebooks
 - [x] Dashboard for high-level overview and analysing traces
 - [ ] Support for direct file input
+- [ ] Support for PostgreSQL
 
 ## Hello world
 
@@ -85,7 +86,7 @@ great-ai hello-world.py
 
 ![scope of GreatAI](media/scope-simple.drawio.svg)
 
-GreatAI fits between the prototype and deployment phase of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:
+GreatAI fits between the prototype and deployment phases of your (or your organisation's) AI development lifecycle. This is highlighted with blue in the diagram. Here, a number of best practices can be automatically implemented aiming to achieve the following attributes:
 
 - **G**eneral: use any Python library without restriction
 - **R**obust: have error-handling and well-tested utilities out-of-the-box