I will build custom ai chatbots with rag and langchain


About this gig
A ChatGPT wrapper with your FAQ pasted into a prompt isn't a business chatbot.
It hallucinates, it can't cite sources, and it breaks the moment someone asks
something specific.
I build RAG (Retrieval-Augmented Generation) chatbots that actually read your
documents PDFs, Word files, spreadsheets, knowledge bases and answer from
them, with sources.
WHAT I BUILD
RAG chatbots over your own document set
Customer support bots that answer from your real policies and docs
Internal knowledge assistants for your team
Document Q&A systems (contracts, manuals, reports)
OpenAI API integration into your existing app or website
AI agents that take actions, not just answer questions
TECH I USE
Python, OpenAI API, LangChain, vector embeddings, FastAPI, Streamlit.
Supports PDF, DOCX, XLSX, CSV, TXT and Markdown sources.
QUALITY CHECK
I validate retrieved context against source documents and test accuracy across
a query set before delivery so you know what it gets right and where its
limits are, before it goes in front of customers.
️ Message me first with
Get to know Imad Ud Din
AI and Odoo ERP Engineer With Automation, RAG Chatbots and Web Scraping
- FromPakistan
- Member sinceDec 2019
- Last delivery3 years
Languages
Urdu, English, Pashto
My Portfolio
FAQ
What's the difference between this and a ChatGPT wrapper?
A wrapper puts your text into a prompt and hopes it fits. RAG indexes your documents and retrieves only the relevant parts per question — which means it handles large document sets and can cite where an answer came from.
Who pays for the OpenAI API usage?
You do, via your own API key — so you keep full control and can revoke it anytime. Typical usage for a small business bot is a few dollars a month.
What file formats can it read?
PDF, DOCX, XLSX, CSV, TXT and Markdown. Scanned PDFs need OCR — I can handle that as an extra.
Can it be embedded on my website?
Yes, from the Standard package up — as a widget or via a REST API endpoint.
How do you know it's accurate?
I test it against a set of real questions from your use case and check retrieved sources against your documents. You get the results before delivery.
