> ## Documentation Index
> Fetch the complete documentation index at: https://devdocs-shaunak-branch.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview

Configuring the application maps your real-world operations into the C3 AI Reliability platform.

You define your asset structure, connect sensor telemetry, train machine learning models, and prepare the application to generate alerts, cases, and reports. Configuration is the foundation of every Reliability deployment — it ensures the platform reflects your equipment, your data, and your organizational needs.

<Tip>
  This page will help you understand what configuration covers, how to approach it, and where to go next for each major setup area.
</Tip>

## Before you begin

Before configuring Reliability, we recommend reviewing the following:

* [Developer Guide Overview](../introduction) — explains what configuration, extension, and maintenance mean in Reliability
* [Reliability Architecture Overview](../architecture) — diagrams and explains the core components you will configure

These two pages will help you understand *why* configuration matters and what you're trying to achieve.

## What configuration means

Configuration is about using out-of-the-box features to tailor Reliability to your environment. You are not building new functionality — you're defining how the existing platform maps to your:

* Equipment (asset hierarchy)
* Telemetry (sensor data integration)
* Predictive models (ML configuration)
* Operational workflows (alerts, cases, reports)
* Access rules (user scoping)
* User interface (UI configuration)

This is distinct from extension, which involves building **new** models, UI components, or integration logic. Most teams start with configuration before deciding if they need extensions.

## Configuration workflow

We recommend configuring Reliability in the following order:

| Step                          | Description                                                                   | Where to Go                                                   |
| ----------------------------- | ----------------------------------------------------------------------------- | ------------------------------------------------------------- |
| 1. Asset Hierarchy            | Define maintainable assets (turbines, gearboxes), facilities, and hierarchies | [Asset Hierarchy Configuration](asset-hierarchy/overview)     |
| 2. Data Integration           | Map historical and real-time telemetry to those assets                        | [Data Integration](data-integration/historical-data)          |
| 3. ML Implementation          | Validate data, train models, and assign them to assets                        | [Machine Learning Implementation](ml-implementation/overview) |
| 4. Access Management          | Control user access to assets, facilities, and workflows                      | [Facility Access Management](security/facility-access)        |
| 5. Optional: UI Configuration | Customize the application interface for operators                             | [UI Configuration](ui-configuration/pages)                    |

Each of these areas builds on the one before it. You can link sensor telemetry to assets *only after* you define the asset hierarchy. You can train models *only after* you ingest and validate your data.

## Where to go next

* Just getting started? Go to the [Quickstart Guide](../quick-start)
* Want to begin configuration? Start with [Asset Hierarchy Configuration](asset-hierarchy/overview)