--- title: "AI Assistant Azure model provider | Nutrient" canonical_url: "https://www.nutrient.io/guides/ai-assistant/service-configuration/model-providers/azure-provider/" md_url: "https://www.nutrient.io/guides/ai-assistant/service-configuration/model-providers/azure-provider.md" last_updated: "2026-06-09T10:22:07.527Z" description: "Azure OpenAI is a great option if you’re looking to use the OpenAI model but you need more advanced configuration options and enhanced data privacy." --- # Azure model provider Azure OpenAI is a great option if you’re looking to use the OpenAI model but you need more advanced configuration options and enhanced [data privacy](https://learn.microsoft.com/en-us/legal/cognitive-services/openai/data-privacy). With this advanced configuration comes more [complexity in setup](https://learn.microsoft.com/en-us/azure/ai-services/openai/quickstart?tabs=command-line%2Cpython-new&pivots=rest-api), so choose wisely. The Azure OpenAI service can be used in a HIPAA-compliant manner. To use Azure OpenAI with AI Assistant, you’ll need set up the API key and reference the correct deployments in the AI Assistant service configuration file. ### Environment variables - `AZURE_API_KEY` — The API key for the Azure OpenAI service. You can retrieve your keys once you’ve created an instance. See the [Azure quickstart](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart?tabs=command-line%2Ctypescript%2Cpython-new&pivots=rest-api#retrieve-key-and-endpoint) guide for more information: ```yaml services: ai-assistant: environment: - AZURE_API_KEY=your-azure-api-key... ``` Refer to the [configuration options](https://www.nutrient.io/guides/ai-assistant/service-configuration/docker-configuration.md) guide for all the configurable environment variables. ### Service configuration file To specify the Azure OpenAI models used by AI Assistant, you’ll need to create a service configuration file, as explained in the [model-provider configuration](https://www.nutrient.io/guides/ai-assistant/service-configuration/ai-configuration.md) guide. Our current chat model suggestion for the Azure OpenAI model is `gpt4o-mini`, along with an embedding model of `text-embedding-3-small`. Here’s an example YAML configuration file using the Azure OpenAI setup: ```yaml version: "2" providers: - name: "azure" instanceName: "your-instance-name" apiKey: "your-azure-api-key" # Optional models: - model: "azure:your-model-deployment-name" labels: ["default-llm"] - model: "azure:your-embedding-model-deployment-name" labels: ["default-embedding"] ``` - **`providers`**: - **`name`** — The name of the provider. Set this to `azure`. - **`instanceName`** — The name of your Azure OpenAI instance. Follow the [Azure OpenAI instance](https://learn.microsoft.com/en-us/azure/ai-services/multi-service-resource) guide to set up your instance. - **`apiKey`** — The API key for the Azure OpenAI service. You can retrieve your keys once you’ve created an instance. See the [Azure quickstart](https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart?tabs=command-line%2Ctypescript%2Cpython-new&pivots=rest-api#retrieve-key-and-endpoint) guide for more information. - **`models`**: - **`model`** — The model deployment in `provider:model` format. - **`labels`** — Use `default-llm` for your chat deployment and `default-embedding` for your embedding deployment. ## Pricing As you’re providing your own OpenAI API key, you’ll be subject to all the costs related to using the OpenAI or Azure OpenAI service. We’ve created an interactive [LLM spend calculator](https://www.nutrient.io/sdk/ai-assistant/) to help you estimate your monthly costs. ## What determines your monthly cost? AI Assistant usage is priced in three main categories, outlined below. ### Document ingestion Each new document added to AI Assistant goes through an [ingestion](https://www.nutrient.io/guides/ai-assistant/document-ingestion/overview.md) process, which enables search, summarization, and Q&A. Documents are only ingested once, even if multiple users access them later. Calculator inputs: - **Number of new documents ingested per month** - **Average document size** (for example, small invoices vs. large manuals) ### User interactions Costs are also based on how users interact with documents — whether through summarization, Q&A, or deep research conversations. Calculator inputs: - **Number of active users** - **Documents viewed by each user per month** - **Level of engagement**: - **None** — No chat usage - **Low** — Occasional summaries or simple queries - **Medium** — Regular in-document conversations - **High** — Frequent follow-ups and deeper context - **Deep** — Analytical, multipart sessions ### Redaction (if enabled in your license) If you’ve licensed the Redaction component, AI Assistant can help redact sensitive content from documents using LLMs. Calculator inputs: - **Number of documents redacted per month** Redaction can be used on its own or in combination with other AI Assistant capabilities. ## Why use the LLM spend calculator? Rather than estimate these costs manually, we highly recommend using our calculator to: - Accurately factor in current OpenAI pricing - Automatically apply the correct token estimates - Get a detailed monthly cost breakdown - Model different usage scenarios You can find the calculator on the [AI Assistant overview](https://www.nutrient.io/sdk/ai-assistant/) page. --- ## Related pages - [AWS Bedrock model provider](/guides/ai-assistant/service-configuration/model-providers/bedrock-provider.md) - [OpenAI model provider](/guides/ai-assistant/service-configuration/model-providers/openai-provider.md) - [OpenAI API-compatible provider](/guides/ai-assistant/service-configuration/model-providers/openai-api-compatible-providers.md) - [Anthropic model provider](/guides/ai-assistant/service-configuration/model-providers/anthropic-provider.md)