edit pass: data-manager-for-agri-concepts

Author: ShawnJackson

articles/data-manager-for-agri/concepts-llm-apis.md

@@ -1,6 +1,6 @@
 ---
-title: Using generative AI in Data Manager for Agriculture
-description: Provides information on using generative AI feature in Azure Data Manager for Agriculture 
+title: Generative AI in Azure Data Manager for Agriculture
+description: Learn how to use generative AI features in Azure Data Manager for Agriculture. 
 author: gourdsay
 ms.author: angour
 ms.service: data-manager-for-agri
@@ -9,41 +9,41 @@ ms.date: 3/19/2024
 ms.custom: template-concept
 ---
 
-# Generative AI in Data Manager for Agriculture
+# Generative AI in Azure Data Manager for Agriculture
 
-The copilot templates for agriculture enable seamless retrieval of data stored in Data Manager for Agriculture so that farming-related context and insights can be queried in conversational context. These capabilities enable customers and partners to build their own agriculture copilots.
+The copilot templates for agriculture enable seamless retrieval of data stored in Azure Data Manager for Agriculture so that farming-related context and insights can be queried in a conversational context. These capabilities enable customers and partners to build their own agriculture copilots.
 
-Customers and partners can deliver insights to users around disease, yield, harvest windows and more, using actual planning, and observational data. While Data Manager for Agriculture isn't required to operationalize copilot templates for agriculture, the Data Manager enables customers to more easily integrate generative AI scenarios for their users.
+Customers and partners can deliver insights to users around disease, yield, harvest windows, and more, by using actual planning and observational data. Although Azure Data Manager for Agriculture isn't required to operationalize copilot templates for agriculture, it enables customers to more easily integrate generative AI scenarios for their users.
 
-Many customers have proprietary data outside of our data manager, for example Agronomy PDFs, market price data etc. These customers can benefit from our orchestration framework that allows for plugins, embedded data structures, and sub processes to be selected as part of the query flow.
+Many customers have proprietary data outside Azure Data Manager for Agriculture; for example, agronomy PDFs or market price data. These customers can benefit from an orchestration framework that allows for plugins, embedded data structures, and subprocesses to be selected as part of the query flow.
 
-Customers with farm operations data in our data manager can use our plugins that enable seamless selection of APIs mapped to farm operations today. In the time to come we'll add the capability to select APIs mapped to soil sensors, weather, and imagery type of data. Our data manager focused plugin allows for a combination of results, calculation of area, ranking, summarizing to help serve customer prompts.
+Customers who have farm operations data in Azure Data Manager for Agriculture can use plugins that enable seamless selection of APIs mapped to farm operations. These plugins allow for a combination of results, calculation of area, ranking, and summarizing to help serve customer prompts.
 
-Our copilot templates for agriculture make generative AI in agriculture a reality.
+The copilot templates for agriculture make generative AI in agriculture a reality.
 
 > [!NOTE]
-> Azure might include preview, beta, or other prerelease features, services, software, or regions offered by Microsoft for optional evaluation. Previews are licensed to you as part of [your agreement](https://azure.microsoft.com/support) governing use of Azure, and are subject to terms applicable to previews.
+> Azure might include preview, beta, or other prerelease features, services, software, or regions offered by Microsoft for optional evaluation. Previews are licensed to you as part of [your agreement](https://azure.microsoft.com/support) governing the use of Azure, and are subject to terms applicable to previews.
 >
 > The preview of Azure Data Manager for Agriculture and related Microsoft generative AI services are subject to [additional terms](https://azure.microsoft.com/support/legal/preview-supplemental-terms/). These additional terms supplement your agreement governing your use of Azure. If you don't agree to these terms, don't use the previews.
 
 ## Prerequisites
 
 - An instance of [Azure Data Manager for Agriculture](quickstart-install-data-manager-for-agriculture.md)
-- An instance of [Azure OpenAI](../ai-services/openai/how-to/create-resource.md) created in your Azure subscription
-- You need [Azure Key Vault](../key-vault/general/quick-create-portal.md)
-- You need [Azure Container Registry](../container-registry/container-registry-get-started-portal.md)
+- An instance of [Azure OpenAI Service](../ai-services/openai/how-to/create-resource.md) created in your Azure subscription
+- [Azure Key Vault](../key-vault/general/quick-create-portal.md)
+- [Azure Container Registry](../container-registry/container-registry-get-started-portal.md)
 
 ## High-level architecture
 
-The customer has full control as key component deployment is within the customer tenant. Our feature is available to customers via a docker container, which needs to be deployed to the customers Azure App Service.
+You have full control because deployment of key components is within your tenant. The copilot templates for agriculture are available via a Docker container, which is deployed to your Azure App Service instance.
 
-:::image type="content" source="./media/concepts-llm-apis/high-level-architecture.png" alt-text="Screenshot showing high level feature architecture.":::
+:::image type="content" source="./media/concepts-llm-apis/high-level-architecture.png" alt-text="Screenshot that shows the high-level feature architecture.":::
 
-We recommend that you apply content and safety filters on your Azure OpenAI instance. Taking this step ensures that the generative AI capability is aligned with guidelines from Microsoft's Office of Responsible AI. Follow instructions on how to use content filters with Azure OpenAI service at this [link](../ai-services/openai/how-to/content-filters.md) to get started.
+We recommend that you apply content and safety filters on your Azure OpenAI instance. Taking this step helps ensure that the generative AI capability is aligned with guidelines from Microsoft's Office of Responsible AI. To get started, follow the [instructions on how to use content filters with Azure OpenAI](../ai-services/openai/how-to/content-filters.md).
 
-## Current farm operations related uses cases
+## Use cases for farm operations
 
-We support seamless selection of APIs mapped to farm operations today. This enables use cases that are based on tillage, planting, applications, and harvesting type of farm operations. Here's a sample list of queries that you can test and use:
+Azure Data Manager for Agriculture supports seamless selection of APIs mapped to farm operations. This support enables use cases that are based on tillage, planting, applications, and harvesting types of farm operations. Here's a sample list of queries that you can test and use:
 
 - Show me active fields
 - What crop was planted in my field (use field name)
@@ -57,7 +57,7 @@ We support seamless selection of APIs mapped to farm operations today. This enab
 - What is the average yield for my field (use field name) with crop (use crop name)
 - What is the effect of planting dates on yield for crop (use crop name)
 
-These use cases help input providers to plan equipment, seeds, applications, and related services and engage better with the farmer.
+These use cases can help input providers to plan equipment, seeds, applications, and related services and engage better with the farmer.
 
 ## Next steps