Learn & Build a Powerful AI RAG Chatbot with n8n + Pinecone + OpenAI

Create your own no-code RAG-powered AI chatbot using n8n, Pinecone, OpenAI, and Google Drive. Get hands-on tutoring and deploy real use cases.

Key Features

Everything you need to run a professional HVAC service business online

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No-Code RAG System

Visual drag-and-drop workflow to build an AI chatbot using n8n without writing backend code.

📁

Google Drive Integration

Automatically upload documents and use them as knowledge base for your AI.

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Smart Document Splitting

Uses recursive chunking for accurate contextual splitting of large documents.

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Embedding & Vector Storage

Index documents using OpenAI embeddings and Pinecone vector database.

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Two Retrieval Modes

Supports both Q&A chain and vector retrieval logic for intelligent answers.

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One-on-One Tutoring

Includes 1-hour support call to help you build and deploy your own chatbot.

What's Included & How It Works

This RAG-based workflow is built in n8n with Pinecone and OpenAI, allowing you to create a fully functional, self-hosted AI chatbot that retrieves answers from your documents.

Visual No-Code Design

Visual No-Code Design

All components are built using n8n's visual editor—perfect for learners and business teams who want results without coding.

Embedding & Chunking Logic

OpenAI is used to create vector embeddings. Documents are smartly chunked using recursive split and stored in Pinecone for quick retrieval.

Embedding & Chunking Logic
Retrieval and Chat Agent Flow

Retrieval and Chat Agent Flow

When a user asks a question, the system pulls contextually relevant documents and sends them through OpenAI's chat model with memory support.

1

Connect Google Drive

Automatically trigger workflows when new documents are uploaded to a selected Drive folder.

2

Preprocess & Clean Data

Remove unnecessary content, extract text from PDFs, and prepare documents for chunking.

3

Chunk & Embed Content

Split documents using recursive logic and generate embeddings using OpenAI, storing them in Pinecone.

4

Configure Retrieval Logic

Set up vector search to fetch the most relevant document chunks based on user queries.

5

Integrate Chat Interface

Connect with a chat UI or API to accept user queries and stream AI responses with context.

6

Deploy Your AI Assistant

Host your chatbot on n8n Cloud or self-hosted instance and provide access to users securely.

Choose Your Learning Path

Standard – Basic Workflow

Download the complete workflow file and setup guide to start building your chatbot.

$20
  • Complete n8n workflow file (.json)
  • 1-O-1 Tutoring
  • Google Drive integration setup
  • PDF document upload automation
  • Basic Q&A retrieval logic
  • Email support
RECOMMENDED

Premium – With Video Tutorial

Everything in Standard plus comprehensive video tutorial and priority support.

$50
  • Everything in Standard
  • n8n set up on Google Cloud Platform
  • Advanced retrieval techniques
  • Vector store optimization guide
  • Pinecone setup walkthrough
  • Priority email support

Custom

Premium package plus 1-hour personalized session and custom deployment assistance.

  • Everything in Premium
  • 1-on-1 Zoom/Meet call (1 hour)
  • Custom deployment on GCP/AWS
  • API key security configuration
  • Tailored to your specific use case
  • Customomization + documentation support
  • Follow-up support session

What Our Customers Say

Real experiences from professionals using our platform

"I went from zero to chatbot in a day. The visual workflow made it so easy!"

AG

Aliyah Greene

Product Manager, DataSolve

"Finally understood how RAG actually works—this tutorial gave me a working AI use case!"

CD

Carlos D.

AI Learner

"Perfect if you want to build internal tools or chatbots for clients using their own data."

SB

Shreya Bansal

Founder, DeepAssist

Frequently Asked Questions

Find answers to common questions about the Complete HVAC Booking Website

Ready to Build Your Own AI Chatbot?

Create a no-code AI assistant trained on your documents in under an hour. Start your RAG journey now.