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I will build ai chatbots, rag systems, and llm apps with langchain
Amjad Khan
About this gig
AI Chatbots & RAG Systems Built for Real-World Use
I build production-ready AI systems using RAG (Retrieval-Augmented Generation), LangChain, and LLMs (Gemini, OpenAI, Groq).
What I Build:
Document Q&A Chatbots
Chat with your PDFs, DOCX, or text files. Perfect for internal knowledge bases, legal documents, or research papers.
Website & Data Integration
Connect your chatbot to websites, databases, or APIs. Your data, your context, accurate answers.
Customer Support Chatbots
24/7 AI agents that handle support, leads, and bookings. Integrate with WhatsApp, Telegram, or your website.
AI Agents & Automation
Smart agents that research, respond, and take actions automatically. Business process automation.
RAG Systems (Retrieval-Augmented Generation)
Combine LLMs with your own data for accurate, context-aware responses. No hallucinations. Real answers.
Custom LLM Applications
Tailor-made solutions using Gemini API, OpenAI API, Groq API, or open-source models.
️ Tech Stack I Use:
LangChain RAG pipelines and agent workflows
Vector DBs Pinecone, Qdrant, ChromaDB,
LLMs Gemini, OpenAI GPT, Groq Llama, Claude
Frontend React.js, Next.js
Backend Python, FastAPI, Node.js
Get to know Amjad Khan
Amjad Khan
Full Stack Developer React Node MongoDB AI
- FromPakistan
- Member sinceSep 2022
Languages
Pashto, Urdu, English
Full-Stack Developer with 3+ years experience in MERN Stack, Next.js, and AI. Built 10+ production projects including SaaS platforms, e-commerce, and real-time video calling apps.
What I Offer:
✅ Custom Web Development (React, Next.js, Node.js, MongoDB)
✅ Bug Fixes & Feature Additions
✅ AI Integration (Gemini API, OpenAI API)
✅ Real-Time Apps (WebRTC, Socket.IO)
Why Choose Me:
• 10+ successful projects
• 3 internships (Arch Technologies, DevelopersHub Corp, Internee.pk)
• Fast delivery & clear communication
Tech: React, Next.js, Node.js, MongoDB, Python, Tailwind CSS, WebRTC, Socket.IO.
My Portfolio
FAQ
What is RAG and why do I need it?
RAG links an LLM to your private data. Instead of guessing, your chatbot answers using your real files, websites, or databases. This stops wrong facts and gives exact, helpful replies. It works great for support teams, company wikis, and document search tools.
What data sources can you connect?
I can connect PDFs, DOCX, TXT, websites (web scraping), databases (SQL, MongoDB), and APIs. Your chatbot will answer questions based on your actual data, not generic AI knowledge.
Do you provide source code?
Yes! I provide complete, well-documented source code with every project. You will own the code and can modify it as needed. Deployment assistance is included in the Premium package.
How long does it take to build a RAG chatbot?
A basic RAG system with 1-3 documents takes 3 days. A full custom system with multiple data sources, custom UI, and deployment takes 5-10 days depending on complexity.
Can you integrate the chatbot with my website or app?
Absolutely! I can integrate your chatbot with websites (React, Next.js, HTML), WhatsApp, Telegram, Slack, or custom APIs. This is included in the Standard and Premium packages.
