> For the complete documentation index, see [llms.txt](https://docs.jetadmin.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.jetadmin.io/user-guide/integrations/reducto.md).

# Reducto

Reducto is an AI-powered document processing platform that helps organizations transform unstructured documents into structured, usable data. It can classify documents, parse complex layouts, extract fields, split multi-document files, and edit documents programmatically. Reducto is designed for AI workflows, document automation, and Retrieval-Augmented Generation (RAG) applications.

## Connecting Reducto

To connect your Reducto account:

1. Open the **Data** tab from the left sidebar.
2. Click **Add Resource**.
3. Select **Reducto** from the list of available resources.
4. Authenticate your Reducto account.

arcade

{% hint style="info" %}
Once connected, the Reducto resource becomes available anywhere JetAdmin supports external resources.
{% endhint %}

## What can it do?

The Reducto integration gives JetAdmin access to advanced document processing capabilities.

From JetAdmin, you can:

* Upload documents for processing
* Classify documents by type
* Parse documents into structured content
* Extract specific fields into JSON
* Split large documents into logical sections
* Edit supported documents programmatically
* Use document data inside AI Agents and workflows

Reducto supports a wide range of document types including PDFs, images, spreadsheets, presentations, and scanned documents.

## Where to use it?

Reducto is most useful whenever your application needs **document understanding**, **data extraction**, or **AI-ready document processing**.

You can use it in:

| JetAdmin feature   | Common use cases                                                                          |
| ------------------ | ----------------------------------------------------------------------------------------- |
| **AI Agents**      | Analyze documents, answer questions from files, extract structured information            |
| **Workflows**      | Automate document processing, route files, extract business data, process uploads         |
| **Internal tools** | Build document review tools, contract analyzers, invoice processors, or knowledge systems |

Typical business use cases include:

* Invoice processing
* Contract analysis
* Document classification
* Data extraction
* Knowledge base ingestion
* RAG pipelines
* Financial document processing
* Customer onboarding workflows

## Available tools (Actions)

| Action                | Description                                                                                         |
| --------------------- | --------------------------------------------------------------------------------------------------- |
| **Upload File**       | Upload a document for processing by Reducto.                                                        |
| **Classify Document** | Categorize documents into predefined document types.                                                |
| **Parse Document**    | Convert documents into structured, AI-ready content including text, tables, and layout information. |
| **Extract Data**      | Extract specific fields and return structured JSON based on a defined schema.                       |
| **Split Document**    | Divide large documents into logical sections or separate documents.                                 |
| **Edit Document**     | Modify supported documents programmatically using instructions or structured inputs.                |

## Example prompts for AI Agents

#### Extract invoice data

```
Upload this invoice to Reducto and extract the invoice number, vendor name, invoice date, and total amount.
```

#### Classify uploaded files

```
Classify all uploaded documents as invoices, contracts, bank statements, or tax documents.
```

#### Parse a contract

```
Parse this contract and summarize the key obligations, renewal terms, and termination clauses.
```

#### Build structured JSON

```
Extract customer information, billing details, and payment terms from this document and return them as structured JSON.
```

#### Split a document package

```
Split this 150-page PDF into separate documents based on document type and provide the page ranges for each section.
```

#### Process onboarding documents

```
Analyze the uploaded onboarding package and extract all customer details required for CRM creation.
```

## Example

This example demonstrates how an AI Agent can process an uploaded document with Reducto and extract structured information.

arcade

> 💡 **Recommended use case**
>
> A great demo for this integration is an **Invoice Processing Agent**:
>
> * Upload an invoice PDF
> * Classify it automatically
> * Extract invoice fields
> * Return structured JSON
> * Create a record in your database
>
> This showcases nearly every Reducto capability in a single workflow.


---

# 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.jetadmin.io/user-guide/integrations/reducto.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.