---
title: "Reasoning Fields in Rossum"
slug: "reasoning-fields"
updated: 2025-08-14T08:47:30Z
published: 2025-08-14T08:47:30Z
canonical: "knowledge-base.rossum.ai/reasoning-fields"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://knowledge-base.rossum.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Reasoning Fields in Rossum

> [!NOTE]
> This feature is in Limited Availability. Existing customers who are interested in accessing this feature should reach out to our support team for assistance – [support@rossum.ai](mailto:support@rossum.ai)

Reasoning fields are used to **extract specific values from other fields’ content**.

## Overview

Rossum’s standard AI engines can extract values exactly as they appear in documents. Formula fields allow you to manipulate those values using predefined rules. Reasoning fields go a step further: it enables the AI to interpret the document context and generate new values based on your instructions.

With reasoning fields, you can define **what the AI should infer and what information it may use to do so**. Our AI can either generate a new value from context or select one from a predefined list.

Importantly, reasoning fields **can learn from your manual corrections within a queue**, helping the AI improve its accuracy over time: If it makes a mistake once, it won’t repeat it.

## How to create a Reasoning Field

You can add a reasoning field in the **Field Settings** of a queue by selecting a **Reasoning Value Source**.

![](https://cdn.document360.io/1bb6f6bc-c04c-4ace-a1e8-8c4cfd3fbc98/Images/Documentation/Reasoning%2001.png)

A dedicated section allows you to define the **reasoning context**, the data available to the AI for making inferences. This includes:

- **Relevant fields**: Input fields that the reasoning field will consider for its answer.

**Relevant properties** (*optional*): Additional information (Label, Description) that can give reasoning more context about your task.
- **Instructions** (*optional*): Label and relevant fields are often enough. If the output isn’t accurate, you can provide a more detailed task description.

![](https://cdn.document360.io/1bb6f6bc-c04c-4ace-a1e8-8c4cfd3fbc98/Images/Documentation/Reasoning%2002v2.png)

### How to write instructions?

- Be specific, precise, and unambiguous.
- Always mention field_ids in your instructions.
- Say what to ignore or exclude
- Include clear examples to illustrate the expected output. (1-3 are often enough.)
- Define the exact output format, provide a fallback.
- Ask another AI assistant to suggest improvements to your instructions.

### Example

**Bad instructions**:

Return the country code, based on the address.

**Good instructions**:

Return the ISO 3166-1 alpha-3 country code (e.g., CZE, AUT, NOR) for the given address.

- Output: 3 uppercase letters only
- If the country is missing, infer from context (city, postal code, language, etc.)
- If unclear, return "UNK"

Example: "Křižíkova 148/34, 186 00 Karlín" → CZE

### Testing your setup

Before saving, test your reasoning field using the built-in testing tools:

1. View **real documents** from your queue in the testing section.
2. Use the preview row to test with **custom values**.
3. Click **Update values** after making changes to refresh the test results.

![](https://cdn.document360.io/1bb6f6bc-c04c-4ace-a1e8-8c4cfd3fbc98/Images/Documentation/Reasoning%2003.png)

## Common use cases

- Extract **early payment discounts**. Often, the early payment discount can come in various shapes and languages. Reasoning gets you covered!
- **Convert unstructured line items** into a structured format. (For example, calculate total amounts from complex item descriptions)
- Extract **header fields from email bodies**. (Create a new [formula field](/help/docs/formula-fields-in-rossum). Ask it to “extract email body“. Then feed it into reasoning.)
- **Analyze email sentiment**. (Identify dissatisfaction or urgency in document delivery emails.)
- **Categorize** the goods in line items.

## Reasoning vs Formula Fields

- Use **formula fields** when you can clearly express the transformation logic. (For example, remove all spaces from the IBAN field or calculate sum from all items in a table.)
- Use **reasoning fields** when the task involves ambiguity, variability, or contextual interpretation.

Note: Formula fields are generally faster and more cost-efficient.

## Requirements

- The user must have access to Queue Settings. (typically available to administrators or managers).
- Formula fields must be enabled.
- Reasoning fields must be enabled.