# What is Tailer Platform?

## :airplane\_departure: Introduction

Retail companies need to handle ever-growing amounts of data. To do so, they require a simple, scalable and easy-to-implement solution offering instant performance at an affordable cost.

Tailer aims at helping all members of B2C companies that need to make sense of huge amounts of sales, inventory, operational, or customer data, to promote their data-driven transformation.

"Tailer" is an anagram of "Retail". As a high tech haute couture solution, it allows you to tailor your data, e-commerce, and sales predictions to your needs.

## :sparkles: What makes Tailer special?

Easy to use, and quick to get up and running, Tailer allows you to achieve your business objectives faster.

As an Open Source solution, Tailer aims at gathering and federating a community of retail industry actors. Thanks to this, and the use of Google Cloud’s affordable resources, it has a particularly low TCO.

Easy to integrate, Tailer can be deployed in only 24h to 48h, and runs inside your own cloud environment.

Tailer is really agile, as its data flows adapt to all contexts. Being DevOps-ready, it allows you to adopt an iterative approach, and a Git branching strategy.

## :tools: Main features

Tailer offers the following features:

* Accessing and securing data
* Gathering and organizing data
* Transforming and enriching data
* Using data for analysis and predictions

## :busts\_in\_silhouette: Who is Tailer intended for?

### **Data engineers**

With Tailer, data engineers can take advantage of a data-centric, collaborative development environment to implement complex real-time big data workflows.

### **Data scientists**

Data scientists can use Tailer to work directly within the company data lake without any technical restriction, and implement predictive models in one click.

### **Decision makers**

Decision makers can take advantage of the better, quicker business insights achieved thanks to Tailer Platform to boost the data-driven transformation of their company.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.tailer.ai/readme.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.