Build a RAG app in under 5 minutes

Quickly create a retrieval-augmented generation app with Scout

Scout makes building AI apps simple. With intuitive drag-and-drop functionality, you can easily build apps that leverage LLMs, APIs, your data, and your custom logic.

In this guide, we’ll show you how to build a RAG app in Scout in under 5 minutes. Scout provisions all the underlying infrastructure, and our free tier doesn’t require a credit card. Let’s get started!

Architecture for our 5 minute RAG app. First we'll integrate our data, then we'll configure and test our AI workflow.
1

Integrate your data

Scout stores your data in collections, which are groups of documents. Each document can contain metadata and text content. The text content is chunked and used for vector search. The metadata can be used to filter and sort the documents. Scout abstracts all of this complexity and provides a simple process to upload documents as outlined below:

2

Configure your workflow

Workflows consist of inputs, composable blocks which represent different actions, and outputs. They can be created from scratch, cloned from an existing workflow, or started with a template. Each block is designed with its own set of configurations. In this guide, we’ll create a workflow that uses an input, a collection search, an LLM, and then output:

3

Run your workflow

There are a variety of ways to run workflows; Slackbots, Scout’s embeddable Copilot, SDKs, API, directly from the Console in the Scout workflow UI, and many more.

In this guide, we’ll keep it simple and test the output directly from the Console in the Scout workflow UI:

Voila! And there you have it; we built a RAG app in under 5 minutes that can guide you in building more powerful and complex AI apps on Scout!

Want to keep building? Check out our free Workflow Templates which can help jumpstart your use case!