> ## 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.

# Introduction

<Warning>This content is currently WIP. Diagrams, content, and structure are subject to change.</Warning>

## Introduction

The C3 AI Reliability application is designed to help organizations predict and prevent equipment failures, optimize maintenance schedules, and improve overall operational efficiency. By leveraging advanced analytics, machine learning, and AI capabilities, the application provides actionable insights to reduce downtime and maintenance costs.

## Key Features in Version 8.6

* **Basic Risk Alert Calculations**: Algorithms for risk assessment
* **Simple Anomaly Detection**: Detection of potential issues
* **User Interface**: Standard dashboards and visualization tools
* **ML Model Support**: Support for basic machine learning models
* **Standard Reports**: Basic reporting capabilities

## Key Reliability Terms

| Term                     | Definition                                                        |
| ------------------------ | ----------------------------------------------------------------- |
| Asset                    | Physical equipment or component that is monitored for reliability |
| Sensor                   | Device that collects data from assets for analysis                |
| Failure Mode             | Specific way in which an asset can fail                           |
| Risk Alert               | Notification of potential failure based on data analysis          |
| Time-to-Event Prediction | Forecast of when a failure might occur                            |

## Getting Started

To get started with the C3 AI Reliability application, see the following sections:

* [Data Model Overview](./data-model/overview)
* [Setting Up a Test App](./setup/test-app)
* [Application Logic](./application-logic/risk-alert-calculations)