# What You Can Do

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Allganize's API dashboard provides multiple features for Named Entity Recognition, Text Classification, Sentiment Analysis, and Review Analysis projects. 
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## Manage Data

Easily upload data for training and testing using API integration, file upload, or direct input. You can filter, find, and download uploaded data according to the conditions you want (duration, test/training data).

## Train Model

You can train and evaluate models to achieve better performance based on your goals and domain. 

## Manage Model

You can deploy, edit/delete, and manage versions of the model you want.

Refer to the Performance Metric for each Model

## Get Analyzed Result

You can get each NLU API's inference result by model.

## Get Analytics

You can get basic analytics report to get insights about model usage & analyzed text.

## Manage Project

You can set the project name and language, and if necessary, you can download and check activity logs performed on the project.


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# 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.allganize.ai/nlu-api-dashboard/overview/what-you-can-do.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.