# Welcome

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Welcome to RagaAI, a comprehensive AI testing platform that automatically detects issues, identifies root cause and empowers users to fix them effectively. This leads to a 3x acceleration in AI development lifecycle while reducing AI risk exposure by 90% in production.&#x20;

RagaAI is a multi-modal platform that supports testing for Generative AI, Discriminative AI and Agentic Application:

* RagaAI Catalyst: Automated Test and Fix platform for  LLM applications
* RagaAI Neo: Assess the performance, reliability, and effectiveness of Agentic AI systems
* RagaAI Prism: Multi-modal platform that supports testing for all compuster vision applications

### RagaAI Catalyst - Public Sandbox

RagaAI Catalyst  is an automated Test and Fix platform for  LLM applications. The RagaAI Catalyst Sandbox is publicly available [here](https://catalyst.raga.ai/signup)[.](https://catalyst.raga.ai/signup) The [Quickstart ](https://docs.raga.ai/ragaai-catalyst/user-quickstart)is  available to help you navigate the platform and see its capabilities firsthand.&#x20;

{% embed url="<https://www.youtube.com/watch?v=C-Gf4cb3QlE>" %}

### RagaAI Prism - Public Sandbox

The RagaAI Prism is a comprehensive AI testing platform for Computer Vision appplications that automatically detects issues, identifies root cause and empowers users to fix them effectively. The RagaAI Prism Sandbox is publicly available [here](https://docs.raga.ai/ragaai-prism). The [Quickstart](https://docs.raga.ai/ragaai-prism/quickstart) and the [Sandbox Guide](https://docs.raga.ai/ragaai-prism) are also available to help you navigate the platform and see its capabilities firsthand.&#x20;

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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.raga.ai/readme.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.
