# Azure AI

> For AI agents: a documentation index is available at [/llms.txt](/llms.txt). Append `.md` to any page URL for markdown, or send `Accept: text/markdown`.

Statsig offers SDKs for integrating Azure AI models into server applications. These SDKs simplify the implementation of features like completions and embeddings in your server application. They provide easy-to-use APIs and automatically track metrics such as latency, token length, and model details, which you can use for optimization and experimentation. Use cases include:

- Implement Azure AI Models in your code with a [single lightweight framework](https://docs.statsig.com/integrations/azureai/model-client)
- [Stream completions](https://docs.statsig.com/integrations/azureai/completions) and [generate embeddings](https://docs.statsig.com/integrations/azureai/embeddings)
- [Capture invocation and usage metrics](https://docs.statsig.com/integrations/azureai/capturing-metrics) with no extra work
- [Run A/B tests on parameters](https://docs.statsig.com/integrations/azureai/running-experiments) like model, prompt, temperature and more

![Azure AI integration architecture diagram](https://docs.statsig.com/images/integrations/azureai/introduction/b23c79c3-8501-4390-a3f3-3496970eb272.png)

## Supported SDKs

- Node JS: https://github.com/statsig-io/azureai-nodejs/
- Python: https://github.com/statsig-io/azureai-python/
- .Net: https://github.com/statsig-io/azureai-dotnet/