Quick start

This tutorial aims to help developers and IT professionals build and deploy GenAI agents with Alan AI and evaluate the platform 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 AI agent 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 AI agent you will be creating.

Sign up for Alan AI Studio

Create an account in Alan AI Studio and set up a project for the AI agent.

Create a static corpus

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

Create a dynamic corpus

Integrate dynamic data sources to enable the AI agent 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 AI agent into the sample app using the Alan AI Plugin and Alan AI SDK.

Customize the AI agent look and feel

Modify the appearance and style of the AI agent to align with the app branding and design.

Add actionable links

Design an AI agent that leverages the app context and UI.

Analyze user queries

Review conversational analytics to understand how users interact with the AI agent.