Connect Azure AI Foundry

With Azure AI Foundry as the model provider, Faustine calls the Claude models deployed in your Foundry resource. Analysis, updates, the Advanced editor and chat all run there, and Azure bills the usage.

Before you begin

An Azure AI Foundry resource with a deployment for each Claude model Faustine requires. See Use Claude models in Microsoft Foundry in the Microsoft documentation.
The resource's name and one of its API keys.
The name of each deployment. A deployment name is one you chose in Azure, and it is often not the model's ID.
For knowledge, an embeddings deployment on an Azure OpenAI resource, or an OpenAI API key.

Enter the credentials

In the portal, go to Settings > Model Provider and select Configure a provider.
In Provider, select Azure AI Foundry.
In Foundry resource, enter the resource name. It is the first part of the resource's endpoint, <RESOURCE>.services.ai.azure.com. Enter the name only, with letters, digits and hyphens.
In API key, enter the resource's key.
Select Continue.

Map the models

In Model names on your provider:

For each model under Required for analysis & code generation, enter the name of its deployment in Azure.
To offer more models for chat, select Add a chat model… and enter its deployment name.
Select Test connection. Each row shows whether the deployment answered.
Select Continue when every required model is reachable.

Faustine cannot derive deployment names, so every required row needs a value.

Set embeddings and save

In Embeddings, select one:
- Azure OpenAI. Enter the Base URL of your Azure OpenAI endpoint, the Deployment name and the API key. This endpoint is a different resource from the Foundry one.
- OpenAI API key. Enter the Model and the API key.
- Not configured.
Select Continue.
In Review & save, select Test connection, then Save & activate.

The tab shows the Azure AI Foundry card with an Active badge and a Foundry resource row.

What the validation checks

Check	How
Credentials	A request of one token to the resource's Anthropic endpoint. A 401 or 403 means the key was rejected, and the configuration is not saved.
Each model	One real request of one token to the deployment in its row.
Embeddings	One embeddings request, when embeddings are configured.

Troubleshooting

Symptom	Cause	Fix
`foundry.resource must be a resource name (letters, digits and hyphens only)`	Foundry resource holds a URL or a domain.	Enter the resource name only.
`Azure Foundry rejected the API key`	The key does not belong to that resource.	Copy the key of the resource named in Foundry resource.
A model shows Not found with `No deployment with this name on the Foundry resource`	The value is the model's ID, not the deployment's name.	Enter the deployment name as it appears in Azure.

Next steps

Model providers: status, test and the other providers.
Choose an embeddings provider: the embeddings options on Azure.
Choose the chat model: pick among the models you mapped.