# Use Amazon Augmented AI with Amazon Textract
Amazon Textract enables you to add document text detection and analysis to your applications. Amazon Augmented AI (Amazon A2I) directly integrates with Amazon Textract's `AnalyzeDocument` API operation. You can use `AnalyzeDocument` to analyze a document for relationships between detected items. When you add an Amazon A2I human review loop to an `AnalyzeDocument` request, Amazon A2I monitors the Amazon Textract results and sends a document to one or more human workers for review when the conditions specified in your flow definition are met. For example, if you want a human to review a specific key like `Full name:` and their associated input values, you can create an activation condition that starts a human review any time the `Full name:` key is detected or when the inference confidence for that key falls within a range that you specify.
The following image depicts the Amazon A2I built-in workflow with Amazon Textract. On the left, the resources that are required to create an Amazon Textract human review workflow are depicted: and Amazon S3 bucket, activation conditions, a worker task template, and a work team. These resources are used to create a human review workflow, or flow definition. An arrow points right to the next step in the workflow: using Amazon Textract to configure a human loop with the human review workflow. A second arrow points right from this step to the step in which activation conditions specified in the human review workflow are met. This initiates the creation of a human loop. On the right of the image, the human loop is depicted in three steps: 1) the worker UI and tools are generated and the task is made available to workers,2) workers review input data, and finally, 3) results are saved in Amazon S3.
![\[Use Amazon Augmented AI with Amazon Textract\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/a2i/diagrams/product-page-diagram_A21-Components_Textract@2x.png)
You can specify when Amazon Textract sends a task to a human worker for review when creating a human review workflow or flow definition by specifying *activation conditions*.
You can set the following activation conditions when using the Amazon Textract task type:
+ Initiate a human review for specific form keys based on the form key confidence score.
+ Initiate a human review when specific form keys are missing.
+ Initiate human review for all form keys identified by Amazon Textract with confidence scores in a specified range.
+ Randomly send a sample of forms to humans for review.
When your activation condition depends on form key confidence scores, you can use two types of prediction confidence to initiate human loops:
+ **Identification confidence** – The confidence score for key-value pairs detected within a form.
+ **Qualification confidence** – The confidence score for text contained within key and value in a form.
In the image in the following section, **Full Name: Jane Doe** is the key-value pair, **Full Name** is the key, and **Jane Doe** is the value.
You can set these activation conditions using the Amazon SageMaker AI console when you create a human review workflow, or by creating a JSON for human loop activation conditions and specifying this as input in the `HumanLoopActivationConditions` parameter of `CreateFlowDefinition` API operation. To learn how specify activation conditions in JSON format, see [JSON Schema for Human Loop Activation Conditions in Amazon Augmented AI](a2i-human-fallback-conditions-json-schema.md) and [Use Human Loop Activation Conditions JSON Schema with Amazon Textract](a2i-json-humantaskactivationconditions-textract-example.md).
**Note**
When using Augmented AI with Amazon Textract, create Augmented AI resources in the same AWS Region you use to call `AnalyzeDocument`.
## Get Started: Integrate a Human Review into an Amazon Textract Analyze Document Job
To integrate a human review into an Amazon Textract text detection and analysis job, you need to create a flow definition, and then use the Amazon Textract API to integrate that flow definition into your workflow. To learn how to create a flow definition using the SageMaker AI console or Augmented AI API, see the following topics:
+ [Create a Human Review Workflow (Console)](a2i-create-flow-definition.md#a2i-create-human-review-console)
+ [Create a Human Review Workflow (API)](a2i-create-flow-definition.md#a2i-create-human-review-api)
After you've created your flow definition, see [Using Augmented AI with Amazon Textract](https://docs.aws.amazon.com/textract/latest/dg/a2i-textract.html) to learn how to integrate your flow definition into your Amazon Textract task.
## End-to-End Example Using Amazon Textract and Amazon A2I
For an end-to-end example that demonstrates how to use Amazon Textract with Amazon A2I using the console, see [Tutorial: Get Started in the Amazon A2I Console](a2i-get-started-console.md).
To learn how to use the Amazon A2I API to create and start a human review, you can use [Amazon Augmented AI (Amazon A2I) integration with Amazon Textract's Analyze Document [Example]](https://github.com/aws-samples/amazon-a2i-sample-jupyter-notebooks/blob/master/Amazon%20Augmented%20AI%20(A2I)%20and%20Textract%20AnalyzeDocument.ipynb) in a SageMaker Notebook instance. To get started, see [Use SageMaker Notebook Instance with Amazon A2I Jupyter Notebook](a2i-task-types-general.md#a2i-task-types-notebook-demo).
## A2I Textract Worker Console Preview
When they're assigned a review task in an Amazon Textract workflow, workers might see a user interface similar to the following:
![\[Example review task in the A2I Textract worker console.\]](http://docs.aws.amazon.com/sagemaker/latest/dg/images/a2i-textract-example.png)
You can customize this interface in the SageMaker AI console when you create your human review definition, or by creating and using a custom template. To learn more, see [Create and Manage Worker Task Templates](a2i-instructions-overview.md).