Generate Structured Dutch Company Descriptions with Bedrijfsdata RAG & OpenAI

This workflow automates the creation of structured synthetic company content by integrating live web data from the Bedrijfsdata.nl API with Retrieval-Augmented Generation (RAG) and an OpenAI language model. Users input a company domain or Bedrijfsdata.nl ID via a flexible trigger, and the workflow retrieves relevant website content and search engine data. It then processes this information through RAG mechanisms to feed into the LLM, producing ready-to-use, Dutch-language descriptions in a consistent JSON format.

Key benefits include time-saving automation for generating accurate, up-to-date company profiles without manual research. The structured output—featuring company_description, products_and_services, and target_audience—ensures seamless integration into downstream systems like CRMs, sales pipelines, or marketing tools. Error handling and modular design make it reliable and extensible for self-hosted n8n instances with community nodes.

Ideal use cases span sales lead enrichment, marketing content creation, and business intelligence for Dutch markets. For example, sales teams can qualify prospects by auto-generating audience insights (e.g., industry, location, company size), while agencies use it for client reports or SEO content. The workflow supports high-volume processing, delivering professional outputs like: {"company_description": "Bedrijfsdata.nl B.V. is een Nederlands bedrijf...", "products_and_services": "API-toegang tot bedrijfsprofielen...", "target_audience": "Nederlandse MKB's..."}.

Requirements include a self-hosted n8n with community nodes for Bedrijfsdata RAG. It's perfect for Dutch-focused B2B automation, reducing research time from hours to seconds.