Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline …

Your AI chatbot is only as good as the data behind it. This n8n template from our friends at @apify shows you how to wire up a RAG pipeline using Apify + Pinecone + Gemini so your chatbot can answer questions grounded in your actual website content, not just what the model knows. How it works: → Apify's Website Content Crawler scrapes your site on a schedule → Content gets chunked and indexed into Pinecone as vector embeddings → Gemini retrieves the right context and generates accurate answers The result: a support chatbot that stays current automatically, with no manual data wrangling. 🔗 @n8n_io template: https://n8n.io/workflows/14157-build-a-company-website-rag-chatbot-using-apify-pinecone-and-gemini/ And if you want to go deeper on the data layer, Apify's blog post covers the full approach (linked in the replies).

Source: Pinecone (X) | 2026-06-05