> For the complete documentation index, see [llms.txt](https://docs.autommate.com/userguide/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.autommate.com/userguide/start-here/use-cases.md).

# Worked examples and use cases

These guides show how to assemble an Autom Mate solution around a specific operational task. Use them as implementation patterns: select the available template or actions, connect your systems, map your fields and test the outcome in your environment.

## Start with a small exercise you can verify

These three routes include current presales screenshots and observations from 13 October 2026. Each starts with synthetic data and gives you a specific result to check. Use a unique copy in your own approved training environment.

### 1. Build and run a Hyperflow

Start with [Build a Hyperflow](/userguide/build-automations/build-a-hyperflow.md). Create Docs - Request intake, configure String Assign, run it manually, and inspect the output.

Expected output: REQ-DEMO-001 | VPN access | Maya Chen. Observed: the standalone flow completed successfully and its Inspector showed that exact string. The exercise does not create a ticket or provision VPN access.

### 2. Build a knowledge-answering AI agent

Follow [Configure an agent](/userguide/ai-agent-composer/configure-an-agent-in-ai-agent-composer.md) → [Add knowledge](/userguide/ai-agent-composer/add-knowledge-to-an-agent.md) → [Test in Playground and review Logs](/userguide/ai-agent-composer/test-in-playground-and-review-logs.md). Use the three-sentence synthetic onboarding policy.

Expected: employees receive a laptop and headset, contractors receive a headset, an unspecified laptop model is acknowledged, and an order request is not claimed as completed. Observed: three conversation turns passed these four checks and appeared as six messages in Logs. Application skills and external channels remain separate exercises.

### 3. Connect a Work Item to a service lifecycle

Begin with the [local Work Item exercise](/userguide/service-automation/run-a-local-work-item-and-inspect-its-logs.md), then [define the request-intake service](/userguide/service-automation/define-a-service.md), [prepare a deployment](/userguide/service-automation/prepare-a-service-for-deployment.md) and [inspect its Service Case](/userguide/operate-and-troubleshoot/read-service-case-status-and-result.md).

Expected: the configured Work Item prepares the same request summary, and you compare action inputs, Work Item result and case result. Observed: Work Item v1.0.1 completed a direct run with Return result true. The separate Service v1.0.0 case SC-3 displayed Success while its Return action input was false; the guide uses this as a result-mapping investigation. Service v1.1.0 was configured but its deployment and runtime were not verified.

Use the observed records to understand the screens and evidence, then reproduce the documented steps in your own environment. A saved configuration, a trigger acknowledgement and a verified business outcome are different checkpoints.

## Choose an example

| What you want to deliver                                         | Start here                                                                                             | System that owns the business record                      |
| ---------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------ | --------------------------------------------------------- |
| Conversational incident and knowledge access                     | [ServiceNow AI Agent](/userguide/start-here/use-cases/servicenow-agent-example.md)                     | ServiceNow                                                |
| Conversational requests, notes and knowledge                     | [Xurrent AI Agent](/userguide/start-here/use-cases/xurrent-agent-example.md)                           | Xurrent                                                   |
| Self-service requests and knowledge with user-specific filtering | [ManageEngine ServiceDesk Plus AI Agent](/userguide/start-here/use-cases/servicedesk-agent-example.md) | ServiceDesk Plus                                          |
| Create and correlate records across two service platforms        | [Jira–Xurrent bidirectional integration](/userguide/start-here/use-cases/jira-xurrent-sync.md)         | Both systems, with an explicit correlation                |
| Coordinate HR, identity, collaboration and equipment tasks       | [Employee onboarding](/userguide/start-here/use-cases/employee-onboarding-example.md)                  | The relevant HR, directory and service-management systems |

## Build one complete, narrow outcome first

For a support agent, begin with one read operation and one permitted write, such as finding knowledge and creating a request. For an integration, begin with one event type and one target record. For onboarding, start with a test identity and a small set of approved provisioning actions.

{% code collapsedlinecount="10" %}

```mermaid
flowchart LR
  A[User request or system event] --> B[Validate input and identity]
  B --> C[Select configured skill or Hyperflow]
  C --> D[Execute permitted system action]
  D --> E[Check the returned result]
  E --> F[Return the record ID or next action]
```

{% endcode %}

The implementation patterns in the example table describe configuration and expected behaviour. The practical exercises above also include explicitly scoped presales observations. Neither establishes performance, compliance certification or a completed customer deployment. Availability of templates, actions and authentication methods depends on the installed library and connected system.

## What to record before release

Record the trigger, input mapping, credential owner, required permissions, duplicate-event behaviour, success evidence and failure route. Test missing input and denied access as well as the successful path. A model's answer should be grounded in the retrieved data and actual action result.

When the same outcome needs to be delivered repeatedly for customers or departments, use the [Service Automation model](/userguide/service-automation/understand-the-service-model.md) to organise the reusable Work Items and deployment configuration. The [Academy](/userguide/start-here/academy-learning-path.md) provides training for the underlying Hyperflow and integration tasks.