Build a website-powered customer support chatbot with Decodo, Pinecone and Gemini

Categories: Business Automation, Customer Support, AI, Knowledge Management

This comprehensive workflow enables businesses to build and deploy a custom-trained AI Chatbot in minutes. By combining a sophisticated data scraping engine with a RAG-based (Retrieval-Augmented Generation) chat interface, it allows you to transform website content into a high-performance support agent. Powered by Google Gemini and Pinecone, this system ensures your chatbot provides accurate, real-time answers based exclusively on your business data.

Benefits

Instant Knowledge Sync - Automatically crawls sitemaps and URLs to keep your AI up-to-date with your latest website content. Embeddable Anywhere - Features a ready-to-use chat trigger that can be integrated into the bottom-right of any website via a simple script. High-Fidelity Retrieval - Uses vector embeddings to ensure the AI "searches" your documentation before answering, reducing hallucinations. Smart Conversational Memory - Equipped with a 10-message window buffer, allowing the bot to handle complex follow-up questions naturally. Cost-Efficient Scaling - Leverages Gemini’s efficient API and Pinecone’s high-speed indexing to manage thousands of customer queries at a low cost.

How It Works

1. Dual-Path Ingestion: The process begins with an n8n Form where you provide a sitemap or individual URLs. The workflow automatically handles XML parsing and URL cleaning to prepare a list of pages for processing. 2. Clean Content Extraction: Using Decodo, the workflow fetches the HTML of each page and uses a specialized extraction node to strip away code, ads, and navigation, leaving only the high-value text content. SignUp using: [dashboard.decodo.com/register?referralcode=55543bbdb96ffd8cf45c2605147641ee017e7900](dashboard.decodo.com/register?referralcode=55543bbdb96ffd8cf45c2605147641ee017e7900). 3. Vectorization & Storage: The cleaned text is passed to the Gemini Embedding model, which converts the information into 3076-dimensional vectors. These are stored in a Pinecone "supportbot" index for instant retrieval. 4. RAG-Powered Chat Agent: When a user sends a message through the chat widget, an AI Agent takes over. It uses the user's query to search the Pinecone database for relevant business facts. 5. Intelligent Response Generation: The AI Agent passes the retrieved facts and the current chat history to Google Gemini, which generates a polite, accurate, and contextually relevant response for the user.

Requirements

n8n Instance: A self-hosted or cloud instance of n8n. Google Gemini API Key: For text embeddings and chat generation. Pinecone Account: An API key and a "supportbot" index to store your knowledge base. Decodo Access: For high-quality website content extraction.