docs

docs/docs/25-form-recognizer-studio/10-intro-form-recognizer.md

@@ -1,6 +1,6 @@
-# Form recognizer studio
+# Document Intelligence Studio
 
-Form recognizer studio is a web-based tool that allows you to create custom models. You can use it to label your training documents and train your custom model.
+Document Intelligence Studio is a web-based tool that allows you to create custom models. You can use it to label your training documents and train your custom model.
 
 ## Custom Form Recognizer models
 

docs/docs/25-form-recognizer-studio/25-upload-training-data.md

@@ -1,14 +1,14 @@
 # Upload training data
 
-This topic describes how to upload your training data to [Form Recognizer Studio](https://learn.microsoft.com/azure/applied-ai-services/form-recognizer/concept-form-recognizer-studio?WT.mc_id=aiml-77396-cxa).
+This topic describes how to upload your training data to [Document Intelligence Studio](https://learn.microsoft.com/azure/applied-ai-services/form-recognizer/concept-form-recognizer-studio?WT.mc_id=aiml-77396-cxa).
 
 ## New patient registration form
 
 In this workshop, you'll create a _custom template model_ to recognize the fields in the new patient registration form. There are five forms in the training set, and each form contains the same fields, four of these forms have been labeled, the fifth form is unlabeled. As part of this workshop, you'll label the fifth form.
 
 This workshop includes a *New Patient Registration Form* and matching label data you need to upload to an Azure storage container.
 
-The label data describes the location of the fields on the forms and was created for the workshop using Form recognizer Studio. The label data is in a JSON file that is named the same as the form file. For example, the label data for the form named `form1.pdf` is in the file named `form1.pdf.json`. The label data is in the same folder as the form files.
+The label data describes the location of the fields on the forms and was created for the workshop using Document Intelligence Studio. The label data is in a JSON file that is named the same as the form file. For example, the label data for the form named `form1.pdf` is in the file named `form1.pdf.json`. The label data is in the same folder as the form files.
 
 <!-- ## Create a storage container
 
@@ -25,7 +25,7 @@ The label data describes the location of the fields on the forms and was created
 
 ## Configure CORS
 
-[CORS (Cross Origin Resource Sharing)](https://docs.microsoft.com/rest/api/storageservices/cross-origin-resource-sharing--cors--support-for-the-azure-storage-services?WT.mc_id=aiml-77396-cxa) needs to be configured on your Azure storage account for it to be accessible from the Form Recognizer Studio. To configure CORS in the Azure portal, you'll need access to the CORS tab of your storage account.
+[CORS (Cross Origin Resource Sharing)](https://docs.microsoft.com/rest/api/storageservices/cross-origin-resource-sharing--cors--support-for-the-azure-storage-services?WT.mc_id=aiml-77396-cxa) needs to be configured on your Azure storage account for it to be accessible from the Document Intelligence Studio. To configure CORS in the Azure portal, you'll need access to the CORS tab of your storage account.
 
 1. Select the CORS tab for the storage account.
 
@@ -47,7 +47,7 @@ The label data describes the location of the fields on the forms and was created
 
 1. Select the save button at the top of the page to save the changes.
 
-CORS should now be configured to use the storage account from Form Recognizer Studio. -->
+CORS should now be configured to use the storage account from Document Intelligence Studio. -->
 
 ## Upload new patient registration form training data
 

docs/docs/25-form-recognizer-studio/30-create-project.md

@@ -1,8 +1,8 @@
 # Create a project
 
-The Form Recognizer Studio provides and orchestrates all the API calls required to complete your dataset and train your model.
+The Document Intelligence Studio provides and orchestrates all the API calls required to complete your dataset and train your model.
 
-1. Start by navigating to [Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio).
+1. Start by navigating to [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio).
 
 1. Select the **Custom models** tile, on the custom models page.
 

docs/docs/25-form-recognizer-studio/50-train-model.md

@@ -29,11 +29,11 @@ With your training forms labeled, you're now ready to train your model. Follow t
 
 Once the model training is complete, you can test your model by selecting the model on the models list page.
 
-1. Select **Test** from the Form Recognizer Studio menu.
+1. Select **Test** from the Document Intelligence Studio menu.
 1. Browse for a file or drag and drop a file into the *Test model* page. Select a .jpeg or .pdf file from the **contoso_new_patient_assets/training_labeled** folder that matches the language you used to train your model.
 1. With a file selected, choose the **Analyze** button to test the model.
 1. The model results are displayed in the main window and the fields extracted are listed in the right navigation bar on the *fields* tab.
 1. Validate your model by evaluating the results for each field.
 1. The right navigation bar also includes sample code to invoke your model and the JSON results from the API.
 
-Congratulations you've trained a custom model in the Form Recognizer Studio! Your model is ready for use with the patient registration app.
+Congratulations you've trained a custom model in the Document Intelligence Studio! Your model is ready for use with the patient registration app.

docs/docs/30-create-new-patient-app/20-upload-doc.md

@@ -6,7 +6,7 @@ Complete a new patient registration form and upload it to the patient registrati
 
 You can print the document and then fill it out by hand, or you can open the document in a PDF reader and edit the document. 
 
-Use the `contoso_new_patient_assets/forms/new_patient_information_<language>.pdf` document that matches the language you used to label and train the model in Form Recognizer Studio.
+Use the `contoso_new_patient_assets/forms/new_patient_information_<language>.pdf` document that matches the language you used to label and train the model in Document Intelligence Studio.
 
 ### Fill out the form by hand