add azure tutorials for API v2

fern/pages/tutorials/cohere-azure-ai-foundry.mdx

@@ -52,6 +52,6 @@ Models that are offered by Cohere are billed through the Azure Marketplace. For
 
 ## Conclusion
 
-This chapter introduced Azure AI Foundry, a fully managed service by Azure that you can deploy Cohere's models on. We also went through the steps to get set up with Azure AI Foundry and deploy a Cohere model.
+This page introduces Azure AI Foundry, a fully managed service by Azure that you can deploy Cohere's models on. We also went through the steps to get set up with Azure AI Foundry and deploy a Cohere model.
 
-In the coming sections, we will go through the various use cases of using Cohere's Command, Embed, and Rerank models on Azure AI Foundry.
+In the next sections, we will go through the various use cases of using Cohere's Command, Embed, and Rerank models on Azure AI Foundry.

fern/pages/v2/tutorials/cohere-azure-ai-foundry.mdx

@@ -0,0 +1,57 @@
+---
+title: Introduction to Cohere on Azure AI Foundry
+slug: /v2/docs/cohere-on-azure/cohere-on-azure-ai-foundry
+
+description: "An introduction to Cohere on Azure AI Foundry, a fully managed service by Azure (API v2)."
+image: "../../../assets/images/f1cc130-cohere_meta_image.jpg"  
+keywords: "Cohere, Command models, Embed models, Rerank models, Azure AI Foundry"
+---
+
+## What is Azure AI Foundry
+
+Azure AI Foundry is a trusted platform that empowers developers to build and deploy innovative, responsible AI applications. It offers an enterprise-grade environment with cutting-edge tools and models, ensuring a safe and secure development process.
+
+The platform facilitates collaboration, allowing teams to work together on the full lifecycle of application development. With Azure AI Foundry, developers can explore a wide range of models, services, and capabilities to build AI applications that meet their specific goals.
+
+Hubs are the primary top-level Azure resource for AI Foundry. They provide a central way for a team to govern security, connectivity, and computing resources across playgrounds and projects. Once a hub is created, developers can create projects from it and access shared company resources without needing an IT administrator's repeated help.
+
+Your new project will be added under your current hub, which provides security, governance controls, and shared configurations that all projects can use. Project workspaces that are created using a hub inherit the same security settings and shared resource access. Teams can create project workspaces as needed to organize their work, isolate data, and/or restrict access.
+
+## Azure AI Foundry Features
+
+- Build generative AI applications on an enterprise-grade platform.
+- Explore, build, test, and deploy using cutting-edge AI tools and ML models, grounded in responsible AI practices.
+- Collaborate with a team for the full life-cycle of application development.
+- Improve your application's performance using tools like tracing to debug your application or compare evaluations to hone in on how you want your application to behave.
+- Safegaurd every layer with trustworthy AI from the start and protect against any risks.
+
+With AI Foundry, you can explore a wide variety of models, services and capabilities, and get to building AI applications that best serve your goals.
+
+## Cohere Models on Azure AI Foundry
+
+To get the most updated list of available models, visit the [Azure AI Foundry documentation here](https://learn.microsoft.com/en-us/azure/ai-studio/how-to/deploy-models-cohere-command?tabs=cohere-command-r-plus-08-2024&pivots=programming-language-python).
+
+## Pricing Mechanisms
+
+Cohere models can be deployed to serverless API endpoints with pay-as-you-go billing. This kind of deployment provides a way to consume models as an API without hosting them on your subscription, while keeping the enterprise security and compliance that organizations need.
+
+To get the most updated list of available models, visit the [Azure marketplace here](https://azuremarketplace.microsoft.com/en-us/marketplace/apps?page=1&search=cohere).
+
+## Deploying Cohere's Models on Azure AI Foundry. 
+
+To deploy Cohere's models on Azure AI Foundry, follow the steps described in [Azure AI Foundry  documentation here](https://learn.microsoft.com/en-us/azure/ai-studio/how-to/deploy-models-serverless?tabs=azure-ai-studio).
+
+In summary, you will need to:
+
+1. Set up AI Foundry Hub and a project
+2. Find your model and model ID in the model catalog
+3. Subscribe your project to the model offering
+4. Deploy the model to a serverless API endpoint
+
+Models that are offered by Cohere are billed through the Azure Marketplace. For such models, you're required to subscribe your project to the particular model offering.  
+
+## Conclusion
+
+This page introduces Azure AI Foundry, a fully managed service by Azure that you can deploy Cohere's models on. We also went through the steps to get set up with Azure AI Foundry and deploy a Cohere model.
+
+In the next sections, we will go through the various use cases of using Cohere's Command, Embed, and Rerank models on Azure AI Foundry.