# For Developers

> “Being provider-agnostic used to mean maintaining multiple complex integrations. With WorkflowAI, we can seamlessly switch between LLM providers without any extra integration effort or overhead—saving us engineering time and headaches.”
>
> \~ Aymeric Beaumet, CTO at M1

## Why Software Engineers like WorkflowAI:

### Our [Python SDK](/python-sdk/get-started.md)

Stop wasting time maintaining separate integrations for every LLM. WorkflowAI gives you unified, seamless access to all models through a single, clean API.

### Structured outputs

WorkflowAI ensures your AI responses always match your defined structure, simplifying integrations, reducing parsing errors, and making your data reliable and ready for use.

### Write code only when you want to

WorkflowAI gives you flexibility: quickly prototype new AI features via our intuitive web interface, or dive directly into code whenever you need deeper customization and control.

### Proudly [open-source](https://github.com/WorkflowAI/workflowai)

WorkflowAI is fully open-source with flexible deployment options. Run it self-hosted on your own infrastructure for maximum data control, or use the managed [WorkflowAI Cloud](/workflowai-cloud/introduction.md) service for hassle-free updates and automatic scaling.

### Model-agnostic

Works with all major AI models including OpenAI, Anthropic, Claude, Google/Gemini, Mistral, DeepSeek, Grok with a unified interface that makes switching between providers seamless.

### [Streaming supported](https://github.com/WorkflowAI/documentation/blob/main/docs/features/code/README.md#streaming)

Enables real-time streaming of AI responses for low latency applications, with immediate validation of partial outputs

## How to get started:

Read our [AI Features Playbook](/ai-features-playbook/introduction.md) to learn how to build your first AI feature in minutes in our web-app, or learn more about our [Python SDK](/python-sdk/get-started.md) to build features programmatically.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.workflowai.com/getting-started/for-developers.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
