You will get I will build a RAG-based AI chatbot in n8n for your Website
Rising Talent
Rising Talent
Project details
This project delivers a fully functional AI-powered chatbot specifically built for e-commerce websites and other customer support websites. Leveraging Retrieval-Augmented Generation (RAG) architecture, the chatbot provides accurate, real-time answers based on your business knowledge base and live internal data. It integrates with various data sources such as Google Sheets, SQL databases, Supa base, PostgreSQL, MongoDB, and document repositories like Google Drive.
Built using n8n for automation, Pinecone for vector-based semantic search, and OpenAI’s chat models for natural conversation, this chatbot supports a wide range of customer queries—from product and policy questions to live order tracking. It is easily embeddable into any website and runs 24/7, offering scalable and intelligent customer support.
Built using n8n for automation, Pinecone for vector-based semantic search, and OpenAI’s chat models for natural conversation, this chatbot supports a wide range of customer queries—from product and policy questions to live order tracking. It is easily embeddable into any website and runs 24/7, offering scalable and intelligent customer support.
What's included $70
These options are included with the project scope.
$70
- Delivery Time 1 day
- Number of Revisions Unlimited
- Number of Pages 1
- Design Customization
- Content Upload
- Responsive Design
- Source Code
About Waqar
Agentic AI | AI Chatbots | n8n | Generative AI RAG Enginer | ML Expert
Gujranwala, Pakistan - 1:47 am local time
With 2+ years of experience, I build intelligent, production-ready AI systems that combine LLMs, real-time data, and workflow automation.
✅ What I Can Do for You
Build RAG pipelines and document Q&A chatbots
Develop voice AI agents and AI appointment booking systems
Create SaaS AI applications and interactive dashboards using HTML, CSS, JavaScript, React, Streamlit
Design end-to-end AI workflows using LangChain, LangGraph, CrewAI, LlamaIndex, and models from OpenAI, Gemini, Anthropic, plus open-source LLMs
I also build voice-enabled AI tools with:
OpenAI — Whisper, TTS/STT
Google — Speech-to-Text, Text-to-Speech, Vertex AI
Microsoft Azure — Cognitive Services, Azure OpenAI, Speech SDK
Amazon AWS — Transcribe, Polly, Rekognition, Bedrock
Meta — Llama, SeamlessM4T, Audiocraft, Detectron
✅ Automation & Data Pipelines
Automate data pipelines using n8n for no-code/low-code workflows and Python libraries such as Pandas, Airflow, Prefect, integrating APIs, CRMs, Google Sheets, and Telegram.
Build AI-powered chatbots, email automation, and data-management automation leveraging Python, LangChain, LlamaIndex, and n8n workflows.
Deploy end-to-end solutions on AWS, GCP, Heroku, Docker, combining Python-based scripts with n8n automation for scalable, real-world applications.
✅ Tech Stack
LLMs & AI Frameworks: LangChain, LangGraph, CrewAI, LlamaIndex, Hugging Face, OpenAI, Gemini
NLP Expertise: Document understanding, semantic search, chatbots, customer support automation, RAG applications
Vector Databases: FAISS, Pinecone, Qdrant, Weaviate, Milvus, Chroma, Redis Vector, Elastic Vector Search, Vespa, Vald
Backend: Python, FastAPI, Flask
Frontend: HTML, CSS, JavaScript, Bootstrap, React, Streamlit
Databases: MySQL, PostgreSQL, SQLite
Automation & Integration: n8n, REST APIs, Webhooks
Cloud & DevOps: Docker, AWS, GCP, Heroku
✅ What I Can Deliver
AI chatbots answering directly from your company documents
Smart RAG-based knowledge assistants
Email automation & AI workflow systems
AI Agents and SaaS AI applications
AI Voice Agents (Twilio or VAPI)
AI-based appointment booking and management systems
Fully automated workflows powered by AI & n8n
ML/NLP applications deployed to the cloud
Steps for completing your project
After purchasing the project, send requirements so Waqar can start the project.
Delivery time starts when Waqar receives requirements from you.
Waqar works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Gathering
Collect the business use cases (e.g., FAQs, order tracking, return/refund handling) Obtain access to your documents (Google Drive), spreadsheets (Google Sheets), or databases (SQL, Supabase, PostgreSQL, MongoDB)
Knowledge Base Preparation
Extract and preprocess company documents (e.g., policies, product info, support guides) Chunk and clean content for semantic search Store processed text in Pinecone as vector embeddings using OpenAI embeddings model