Quick start

This tutorial helps developers and IT professionals build and deploy AI‑driven interfaces using Alan AI and to evaluate the platform’s capabilities.

The tutorial offers a set of self-guided exercises to become familiar with Alan AI. Each exercise provides a brief explanation of a feature, use case description, step-by-step procedure and tips on how to validate the exercise results.

Note

This tutorial focuses on common use cases to help you get started. For information on advanced use cases, check the See also section in each exercise.

To understand how Alan AI works and get an Agentic Interface up and running quickly and efficiently, follow these steps:

Review the project scope

Review the project goals, features and functionality of the sample app and Agentic Interface you will be creating.

Create a static corpus

Create a static data corpus of documents and pages that the Agentic Interface will use to answer user queries.

Create a dynamic corpus

Integrate dynamic data sources to enable the Agentic Interface to interact with dynamic data.

Understand AI reasoning

Learn how Alan AI processes data, makes decisions and generates output.

Adjust AI reasoning and output

Customize the AI reasoning instructions and output to meet the requirements of the project.

Integrate with the app

Embed the Agentic Interface into the sample app using the Alan AI Browser Plugin and Alan AI SDK.

Customize the Agentic Interface look and feel

Modify the appearance and style of the Agentic Interface to align with the app branding and design.

Add actionable links

Design an Agentic Interface that leverages the app context and UI.

Analyze user queries

Review Agentic Interface Analytics to understand how users interact with the Agentic Interface.