AI-Powered Corporate Research System for Animal Advocacy Campaigns

This n8n workflow provides a robust system for extracting structured information from unstructured text, specifically designed to support animal advocacy campaigns by analyzing corporate data. It leverages AI language models to identify key entities and relationships within text, transforming raw information into actionable data.

What it does

This workflow acts as a sub-workflow, designed to be called by another main workflow. Upon execution, it performs the following steps:

1. Receives Input: It is triggered when called by another n8n workflow, expecting unstructured text data as input.
2. Extracts Information with AI: It utilizes an AI-powered "Information Extractor" (likely based on LangChain) to parse the input text. This node is configured to identify and extract specific entities and relationships relevant to corporate research, such as company names, individuals, products, campaign targets, or related issues.
3. Processes with a Language Model: It uses a "Basic LLM Chain" which integrates with an "OpenRouter Chat Model". This chain likely refines the extracted information, performs further analysis, or structures the output according to predefined schemas. This could involve summarization, sentiment analysis, or linking identified entities.
4. Aggregates Data: The extracted and processed information is then aggregated, combining multiple pieces of data into a consolidated output.
5. Splits Out Data: Finally, the aggregated data is split out, potentially to prepare it for further processing or storage in a structured format (e.g., individual records for a database or spreadsheet).

Prerequisites/Requirements

To use this workflow, you will need:

• n8n Instance: A running n8n instance (cloud or self-hosted).
• AI Credentials:
  • OpenRouter API Key: For the "OpenRouter Chat Model" node to access various AI models.
• Understanding of LangChain Concepts: Familiarity with LangChain chains and information extraction principles will be beneficial for configuring the AI nodes.

Setup/Usage

1. Import the Workflow:
   • Download the provided JSON file.
   • In your n8n instance, go to "Workflows" and click "New".
   • Click the "Import from JSON" button and paste the workflow JSON or upload the file.
2. Configure Credentials:
   • Locate the "OpenRouter Chat Model" node.
   • Configure the credentials for OpenRouter by adding your API key.
3. Integrate as a Sub-workflow:
   • This workflow is designed to be called by an "Execute Workflow" node in a parent workflow.
   • In your main workflow, add an "Execute Workflow" node and configure it to call this specific workflow.
   • Ensure the data passed to this sub-workflow matches the expected input for the "Information Extractor" node.
4. Activate the Workflow: Once configured, activate the workflow. It will then be ready to process data when called by a parent workflow.

This sub-workflow provides a powerful, modular component for any larger system that requires intelligent extraction and processing of textual information, particularly useful for detailed corporate research in advocacy contexts.