Generate structured company descriptions with Bedrijfsdata Web RAG & OpenAI
This workflow contains community nodes that are only compatible with the self-hosted version of n8n.
This template generates structured synthetic company content using live web data from the Bedrijfsdata.nl API combined with an LLM. Provide a company domain (directly or via a Bedrijfsdata.nl ID) and the workflow retrieves relevant website and search engine content, then produces ready-to-use descriptions of the company, its offerings, and its target audience.
✨ Features
- Create high-quality Dutch-language company descriptions on demand
- Automatically pull live web content via Bedrijfsdata.nl RAG Domain & RAG Search
- Structured JSON output for consistent downstream use (e.g., CRM updates, lead qualification)
- Flexible trigger: run from ProspectPro ID, domain input, or another workflow
- Secure, modular, and extendable structure (error handling included)
🏢 Example Output The workflow produces structured content fields you can directly use in your sales, marketing, or enrichment flows:
- company_description – 1-2 paragraph summary of the company
- products_and_services – detailed overview of offerings
- target_audience – specific characteristics of ideal customers (e.g., industry, location, company size, software usage)
Example:
{
"company_description": "Bedrijfsdata.nl B.V. is een Nederlands bedrijf dat uitgebreide data levert over meer dan 3,7 miljoen bedrijven in Nederland...",
"products_and_services": "Het bedrijf biedt API-toegang tot bedrijfsprofielen, sectoranalyses, en SEO-gegevens...",
"target_audience": "Nederlandse MKB's die behoefte hebben aan actuele bedrijfsinformatie voor marketing- of salesdoeleinden..."
}
⚙ Requirements
- n8n instance or cloud workspace
- Install the Bedrijfsdata.nl n8n Verified Community Node
- OpenAI API credentials (tested with gpt-4.1-mini and gpt-3.5-turbo)
- Bedrijfsdata.nl developer account (14-day free trial, 500 credits)
🔧 Setup Instructions
1. Trigger configuration
- Use Bedrijfsdata.nl ID (default) or provide a domain directly
- Can be called from another workflow using “Execute Workflow”
2. Configure API credentials
-
Bedrijfsdata.nl API key
-
OpenAI API key
3. Customize Output (Optional)
- Adjust prompt in the LLM node to create other types of synthetic content
- Extend structured output schema for your use case
4. Integrate with Your Stack
- Example node included to update HubSpot descriptions
- Replace or extend to match your CRM, database, or messaging tools
🔐 Security Notes
- Input validation for required domain
- Dedicated error branches for invalid input, API errors, LLM errors, and downstream integration errors
- RAG content checks before running the LLM
🧪 Testing
- Run workflow with a Bedrijfsdata.nl ID linked to a company with a known website
- Review generated JSON output
- Verify content accuracy before production use
📌 About Bedrijfsdata.nl Bedrijfsdata.nl operates the most comprehensive company database in the Netherlands. With real-time data on 3.7M+ businesses and AI-ready APIs, we help Dutch SMEs enrich their CRM, workflows, and marketing automation. Built on 25+ years of experience in data collection and enrichment, our technology brings corporate-grade data quality to every organisation.
Website: https://www.bedrijfsdata.nl Developers: https://developers.bedrijfsdata.nl API docs: https://docs.bedrijfsdata.nl
📞 Support Email: klantenservice@bedrijfsdata.nl Phone: +31 20 789 50 50 Support hours: Monday–Friday, 09:00–17:00 CET
Generate Structured Company Descriptions with Bedrijfsdata Web-RAG & OpenAI
This n8n workflow automates the process of generating structured company descriptions. It leverages an external trigger to initiate the process, uses an AI model (likely OpenAI) to process information, and then conditionally updates a HubSpot CRM.
What it does
This workflow performs the following key steps:
- Triggers on External Execution: The workflow starts when it's explicitly called by another n8n workflow.
- Processes with AI (LangChain & OpenAI): It uses a "Basic LLM Chain" combined with an "OpenAI Chat Model" to process input data.
- Parses Structured Output: A "Structured Output Parser" is used, indicating that the AI is expected to return data in a predefined, structured format (e.g., JSON).
- Conditional Logic: An "If" node evaluates a condition based on the processed data.
- Updates HubSpot (Conditional): If the condition in the "If" node evaluates to
true, the workflow proceeds to update a HubSpot CRM with the generated information. - No Operation (Conditional): If the condition in the "If" node evaluates to
false, the workflow performs a "No Operation," effectively ending that branch without further action. - Code Execution: A "Code" node is present, suggesting custom JavaScript logic is executed at some point in the flow, likely for data manipulation or preparation.
- Sticky Note: A "Sticky Note" is included, which typically serves as a comment or documentation within the workflow itself.
Prerequisites/Requirements
To use this workflow, you will need:
- n8n Instance: A running n8n instance.
- OpenAI API Key: For the "OpenAI Chat Model" node. This will need to be configured as an n8n credential.
- HubSpot Account: If you intend to use the HubSpot integration, you'll need a HubSpot account and the corresponding n8n credential configured.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Configure Credentials:
- Set up your OpenAI API Key as a credential in n8n.
- Set up your HubSpot API Key or OAuth credential in n8n.
- Activate the workflow: Ensure the workflow is active in your n8n instance.
- Trigger the workflow: This workflow is designed to be triggered by another workflow. You will need to call the "Execute Workflow Trigger" node from another n8n workflow, passing in the necessary input data for company descriptions.
- Review and Customize:
- Examine the "Basic LLM Chain" and "OpenAI Chat Model" nodes to understand the prompts and models used for generating descriptions. Customize them as needed for your specific use case.
- Inspect the "Structured Output Parser" to understand the expected output schema from the AI.
- Adjust the "If" node's condition to match your business logic for when HubSpot should be updated.
- Modify the "HubSpot" node to specify which HubSpot object (e.g., Company, Contact) and properties should be updated with the generated data.
- Review and modify the "Code" node if custom data processing is required.
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