> For the complete documentation index, see [llms.txt](https://guap.gitbook.io/guap-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://guap.gitbook.io/guap-docs/master.md).

# Welcome aboard!

Nice to meet you - let's onboard on our journey to switch from algorithms outputs to business outcomes :)

## guap, you said?

![](https://3357777262-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-M_vHi1y3QuXkjxjH70Y%2F-MaY0kO6368m6ncdZg93%2F-MaYhQpQDcEp46cqNLvF%2Fbanner.png?alt=media\&token=c85f0d0b-d9ef-4431-9eee-9f2236e5a571)

**guap** is an open-source python package that helps data teams to get ML evaluation metrics everyone can agree on by converting your model output to business outcomes, a.k.a. profits.

We truly believe that **linking business to data science is the more critical aspect to achieve success in AI/ML.** So our mission is to align all stakeholders with measurable business outcomes and the trustworthiness of results by including the three core teams — business, data science, and IT — throughout the ML lifecycle. With a product, a data scientist AND an executive will love to use it.

* Make collaboration healthier and clearer between tech and non-tech people
* Make better decisions at every stage of the ML project lifecycle

And it starts with a simple way to estimate the expected profit/cost of a model based on its confusion matrix.

Convinced? Hit the next page to learn how to get started. Hurry up, money don't sleep 🤓

{% content-ref url="/pages/-M\_vKXcvLtxmpYbYa50M" %}
[Getting started](/guap-docs/getting-started/install-guap.md)
{% endcontent-ref %}