> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mindlab.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Architecture Overview

> A high-level overview of the MindLab platform architecture.

The MindLab platform is designed to provide a robust, scalable, and governable environment for AI-driven workflows. The architecture is built around a clear flow of information and control, ensuring that every task is executed with precision and predictability.

### The Flow of Information

The core of the MindLab architecture is a logical flow that begins with a user's intent and ends with a verifiable outcome. This process can be broken down into the following steps:

<Steps>
  <Step title="Intent">
    The process begins when a user provides a high-level **Intent** to the **Orchestrator**. This intent is a description of the desired outcome, rather than a specific set of instructions.
  </Step>

  <Step title="Selection">
    The **Orchestrator** analyzes the intent, consults its knowledge base, and selects the most appropriate **Capsule(s)** from the marketplace to fulfill the request.
  </Step>

  <Step title="Planning">
    The **Orchestrator** reads the **CADANCE™ Spec** (the manifest) of the selected Capsule to understand its capabilities, constraints, and workflow structure. It then generates a specific, executable plan (a DAG) based on the user's intent and the Capsule's playbook.
  </Step>

  <Step title="Execution">
    This plan is handed off to the **Flow Engine** for execution. The Flow Engine calls upon the specific agents defined in the Capsule and leverages its own durability features to ensure the successful completion of the workflow.
  </Step>
</Steps>