> ## 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

C3 AI Reliability enables organizations to monitor critical equipment, detect emerging risks, and reduce unplanned downtime. It connects real-time telemetry, maintenance history, and machine learning models to provide early warnings and guide corrective actions.

Designed for enterprises managing complex assets across facilities or fleets, Reliability brings AI-driven insights directly into daily operations, helping teams move faster, prioritize smarter, and continuously improve system health.

## What C3 AI Reliability provides

C3 AI Reliability focuses on five core capabilities that work together to drive predictive maintenance and operational excellence:

* **Risk Detection**: Machine learning models automatically identify anomalies in sensor and process data, highlighting risks before they escalate into failures.

* **Prioritized Decision Support**: Risk scoring and AI-generated recommendations focus attention on the most critical operational issues, reducing noise and improving efficiency.

* **Root Cause Investigation**: When alerts are triggered, the system links anomalies to likely causes, supporting faster, more traceable investigations.

* **Continuous Learning**: Reliability models evolve based on new telemetry and user feedback, improving accuracy and adapting to operational changes.

* **Workflow Integration**: Teams can manage alerts, cases, and work orders directly within the application, connecting detection with resolution seamlessly.

The Reliability application surfaces these capabilities through an intuitive, operationally-focused interface. For example, the Alerts page allows users to quickly review asset risks, prioritize cases, and launch investigations:

![C3 AI Reliability Alerts Overview](https://mintlify.s3.us-west-1.amazonaws.com/devdocs-shaunak-branch/apps/reliability/8.8/user-interface/img/rel_user_all_alerts.png)
To explore the Reliability application in more detail — including how alerts, cases, models, and assets are organized — continue to the [User Interface Overview](user-interface/overview).

## How users and developers work together in Reliability

C3 AI Reliability is designed to support long-term operations by readily supporting ongoing updates, extensions, and maintenance.
Users and developers work together to ensure the application remains aligned with real-world asset behavior and operational needs.

This is how that process looks:

```mermaid
flowchart LR
    A[Developer Configures Application] --> B[User Monitors Assets and Alerts]
    B --> C[User Creates Cases and Work Orders]
    B --> D[User Requests Model or Asset Updates]
    D --> E[Developer Updates Application Configuration]
    E --> B
```

1. Developers, typically C3 AI Solutions Engineers, do so by configuring an asset hierarchy, connecting sensor data streams, training machine learning models, and setting up alert workflows. The [Developer Guide](developer-guide/introduction) provides details on these configuration tasks.

2. After setup, users operate Reliability through the [User Interface](user-interface/overview), where they monitor asset health, review AI-generated alerts, investigate emerging risks, and create cases or work orders. Day-to-day workflows are explained in the [User Guide](user-guide/introduction).

3. Over time, users may request updates to the application as operational needs change. These updates could involve retraining models, updating asset hierarchies, or adjusting alert logic.

## Navigate based on your stage

Depending on where you are in your Reliability journey, the following resources will guide your next steps:

| Stage of Application Development | Description                                                                                                      | Link to Next Step                                                                                |
| :------------------------------- | :--------------------------------------------------------------------------------------------------------------- | :----------------------------------------------------------------------------------------------- |
| Setting Up the Application       | Build asset hierarchies, connect telemetry, and configure models for deployment.                                 | [Developer Guide: Configuring the Application](developer-guide/configuring-application/overview) |
| Using the Application            | Monitor alerts, investigate risks, create cases and work orders, and manage operational health.                  | [User Guide: Monitoring Alerts and Creating Work Orders](user-guide/overview)                    |
| Maintaining the Application      | Monitor model performance, retrain models, and update assets or sensor mappings.                                 | [Developer Guide: Maintaining the Application](developer-guide/maintaining-application/overview) |
| Extending the Application        | Add advanced modules like GeoSpatial analysis, Generative AI insights, Diagram Parsing, or Spare Parts tracking. | [Developer Guide: Extending the Application](developer-guide/extending-application/overview)     |