> For the complete documentation index, see [llms.txt](https://awsnotes.dendron.so/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://awsnotes.dendron.so/machine-learning/amazon-kendra/topics/tutorial-building-an-intelligent-search-solution.md).

# Tutorial: Building an intelligent search solution

{% hint style="info" %}
This page was generated from content adapted from the [AWS Developer Guide](https://github.com/awsdocs/amazon-kendra-developer-guide.git)
{% endhint %}

## Step 1: Adding documents

* **Important**\
  The name of an Amazon S3 bucket must be unique across all of AWS.
* **Note**\
  You must choose a region that supports both Amazon Comprehend and Amazon Kendra. You cannot change the region of a bucket after you have created it.

## Step 3: Formatting the metadata

* **Important**\
  For the metadata to be formatted correctly, the input values in steps 8-10 must be exact.
* **Note**\
  If you do not have Boto3 installed, run `pip3 install boto3` to install it.
* **Important**\
  For the metadata to be formatted correctly, the input values in steps 5-7 must be exact.

## Step 4: Creating an index and ingesting the metadata

* **Important**\
  Misspelled entity types will not be recognized by the index.


---

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