---
title: n8n
description: "### What is n8n? n8n is an open-source workflow automation tool that allows users to create custom workflows by connecting different apps, services, and APIs. It simplifies automating tasks without needing to write code, using a visual drag-and-drop interface. ###…"
url: "https://anesthesiabraintrust.org/docs/n8n/"
updated: "2025-02-20"
category: Knowledge Home / Repo Lab / Automated Workflow
---

# n8n

### What is n8n?

n8n is an open-source workflow automation tool that allows users to create custom workflows by connecting different apps, services, and APIs. It simplifies automating tasks without needing to write code, using a visual drag-and-drop interface.

### Key Features:

- **Workflow Creation**: Build workflows that automate tasks by linking apps and services.
- **Wide Integrations**: It supports over 200 integrations (e.g., Google Sheets, Slack, APIs).
- **Open Source**: Free to use and can be self-hosted for more control over your data.
- **Triggers & Actions**: Automate tasks based on specific events or schedules.
- **Error Handling**: Automatically retries or sends alerts when a task fails.

### Example Use Cases with **Retrieval-Augmented Generation (RAG)**:

1. **RAG for Enhancing Search and Retrieval in AI Models**:
   - **RAG** is a technique used in AI models that combines retrieval from external data sources with generative capabilities (like GPT models) to produce more accurate and contextually relevant outputs. n8n can help automate workflows where this model is involved.
   **Example Workflow**:
   - Trigger: A user submits a query (e.g., through a chatbot or form).
   - Action: n8n retrieves relevant data from a database, knowledge base, or search engine.
   - Action: The retrieved data is then fed into a generative model (e.g., GPT) to generate a response based on both the retrieved data and the model’s capabilities.
2. **Medicine**: Automating the Use of RAG for Medical Knowledge Retrieval
   - **RAG** can be used to enhance clinical decision support systems by retrieving relevant medical information (e.g., drug interactions, research papers) and generating tailored recommendations.
   **Example Workflow**:
   - Trigger: A new patient case is logged into a system.
   - Action: n8n retrieves relevant research papers, clinical guidelines, or similar patient cases from a medical database.
   - Action: The retrieved information is passed to a language model that generates recommendations for treatment options, which are then reviewed by medical professionals.
3. **Veterinary Medicine**: Using RAG for Pet Health Queries
   - n8n can automate workflows that retrieve medical data related to specific pet conditions and generate advice for pet owners.
   **Example Workflow**:
   - Trigger: A pet owner submits a question about a specific condition (e.g., dog allergy symptoms).
   - Action: n8n retrieves the most relevant medical information about the condition from veterinary databases or research papers.
   - Action: The information is processed by a language model, which generates a comprehensive response with treatment suggestions.

### Benefits:

- **Automation of Data Retrieval**: n8n can integrate multiple data sources (databases, APIs) to feed into AI models.
- **Efficiency**: Helps save time by automating the retrieval and generation of complex information.
- **Customization**: Tailor workflows to automate specific retrieval and generation tasks for industries like healthcare and veterinary medicine.
- **Open Source**: n8n is free and customizable, offering full control over the data and workflow logic.

In summary, **n8n** can be extremely useful for automating tasks around **Retrieval-Augmented Generation (RAG)** in industries like healthcare and veterinary medicine. It helps automate the process of retrieving relevant data, passing it through generative models, and providing more accurate and context-specific outputs to users.