> For the complete documentation index, see [llms.txt](https://ordino-ai.gitbook.io/ordino-ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ordino-ai.gitbook.io/ordino-ai/getting-started/ordino-ai.md).

# Ordino AI

### Overview

**Ordino AI** is an intelligent orchestration platform designed to simplify and modernize software quality engineering. It integrates and coordinates fragmented testing tools, automates routine testing processes, and leverages agent-based architectures to streamline test design, execution, monitoring, and reporting.

By connecting diverse systems across the SDLC, Ordino AI enables engineering teams to:

🚀 **Unified Orchestration**

Provides a unified orchestration platform that integrates various testing tools into a single layer, enhancing efficiency and collaboration.

🔐 **Manage Auth**

Managed authentication and access control across connected external mcp-tools and agents

🤖 **Intelligent Agent System**

Intelligent agents to oversee workflows and ensure smooth operations, significantly reducing the necessity for manual interventions.

### Discover the platform

{% columns %}
{% column width="50%" %}

#### Create a seamless experience between your codebase and ecosystem

Ordino AI offers an enterprise test automation framework that bridges skills gaps, empowering teams—from startups to large enterprises—to contribute equally and efficiently.

{% endcolumn %}

{% column %}

<figure><img src="/files/c9tMCBOOilEIi3svYW8p" alt=""><figcaption></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

{% columns %}
{% column width="50%" %}

#### Simplify observability and control across your entire ecosystem

Ordino AI offers a unified dashboard for ecosystem management and observability, enabling real-time insights, control, and configurable AI-driven workflows to optimize testing activities.

{% endcolumn %}

{% column %}

<figure><img src="/files/nBo3wNtxzwOe7ah9HT1i" alt=""><figcaption></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

{% columns %}
{% column width="50%" %}

#### Orchestration platform for routing and coordinating external agents

Ordino Copilot enables secure orchestration and coordination of external MCPs and Agents through managed authentication. Eliminate fragmented integrations with a unified, intelligent control layer.

{% endcolumn %}

{% column %}

<figure><img src="/files/aQdMgVtCbZg77uUzZufT" alt=""><figcaption></figcaption></figure>
{% endcolumn %}
{% endcolumns %}

{% columns %}
{% column width="50%" %}

#### Agentic supervisory workers mirror your roles and responsibilities.

Ordino AI automates critical QA operations—like test coordination, inspection, and reporting—through supervisory agents that replicate the day-to-day responsibilities of your testers

{% endcolumn %}

{% column %}

<figure><img src="/files/TXsPqYUA8KP2NjtyhDW8" alt=""><figcaption></figcaption></figure>
{% endcolumn %}
{% endcolumns %}


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://ordino-ai.gitbook.io/ordino-ai/getting-started/ordino-ai.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.