Azure AI Foundry

Recommended path. Deploy a model in your Azure AI Foundry project and connect it to Mosaic.

Mosaic connects to a model you've deployed in your own Azure AI Foundry project. Inference happens in your Azure subscription, your billing, your governance.

Prerequisites

• An Azure subscription with permission to create AI Foundry resources

• Familiarity with the Azure AI Foundry portal

• A Tenant Admin account in Mosaic

Steps

1

Create or open an Azure AI Foundry project

In the Azure AI Foundry portal, create a project (or open an existing one). The project is the unit Mosaic will connect to.

If you don't already have a project: + Create project → choose a hub → name it (e.g., mosaic-inference) → create.

2

Deploy a model

Inside the project: Models + endpoints → Deploy model → pick a model. Mosaic works well with:

• Claude (Sonnet or Opus) — best for the agent flows used by Variance Commentary, Sales Pulse, etc.

• GPT-4 / GPT-4o — strong general-purpose default

• Mistral / Llama — open-weight options if your governance prefers them

Give the deployment a name you'll recognise (e.g., claude-sonnet-prod).

3

Copy the endpoint URL and key

Once the deployment is running:

• Endpoint URL — visible on the deployment detail page (e.g., https://<project>.openai.azure.com/)

• API Key — under Keys and endpoint for the project

Copy both. The API key is sensitive — do not share or commit to source control.

4

Connect Mosaic to your Foundry endpoint

In Mosaic:

1. Admin → AI Configuration

2. Add provider → Azure AI Foundry

3. Paste:

   • Endpoint URL

   • API Key

   • Deployment name (the one from step 2)

4. Click Test connection — Mosaic sends a tiny test prompt and verifies the response

5. Click Save

Mosaic now uses your Foundry endpoint for all AI inference across the tenant.

5

Verify

Open a Mosaic chat and ask any question. The agent reasoning should stream as expected. Check Admin → AI Sessions — the model name shown for the new session should match your Foundry deployment name.

Recommended Foundry settings

• Content filter: Microsoft's default (Strict / Default / Off). Strict reduces false positives from analyst questions about sensitive topics; Default is the safer baseline for most tenants.

• TPM (tokens per minute) quota: start at 100 K TPM and scale based on usage. Foundry shows usage trends in its monitoring dashboards.

• Region: pick the region closest to your users. Mosaic's app servers are in India; latency is acceptable from any global Foundry region but lower from nearby ones.

Switching models

You can change the deployed model in your Foundry project at any time. Mosaic re-uses whatever the deployment-name resolves to. There's no Mosaic-side switch; just update Foundry.

What's next

Mosaic App Configurations →