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

# Application/Bot Use Cases

Most of the applications/bots that our customers build ingest data from either **Tickets** (that are created when agents communicate with customers) or from **Knowledge Base Articles** or similar documents that contain useful information for customers.

Therefore, common use cases for bots created with the Aisera Gen AI platform include actions performed on Ticket data or Knowledge Article data:

[**Agent Assist**](https://docs.aisera.com/agent-assist/agent-assist-use-case-map) - Comparing new ticket information in real time (while agents are working with customers) with existing similar tickets.

[**Ticket Concierge**](https://docs.aisera.com/aisera-platform/ticket-operations/ticket-concierge-tc-with-event-studio) - Sorting tickets into categories.

[**Generating Knowledge from Tickets**](https://docs.aisera.com/aisera-platform/generative-ai-learning/ticket-learning/set-up-ticket-learning) - Creating Knowledge Articles from ingested Ticket Data.

[**Generating Knowledge from Ticket Comments**](https://docs.aisera.com/aisera-platform/content-generation/kb-article-generation-from-ticket-comments) - Creating Knowledge Articles from ingested Ticket Comment fields.

[**Generating Knowledge from Conversations**](https://docs.aisera.com/aisera-platform/content-generation/creating-requests-and-tickets-from-conversations) - You can create Incidents or Requests automatically

[**Knowledge Learning**](https://docs.aisera.com/aisera-platform/tenant-setup/aisera-platform-configuration/tenant-configuration-settings/knowledge-learning) - Using LLM models to provide answers based on ingested Knowledge Articles.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.aisera.com/application-bot-use-cases/application-bot-use-cases.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.