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$
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I will build a rag chatbot trained on your documents
churamani p.
About this gig
Your support team answers the same questions over and over, buried in documents nobody has time to search. I build custom AI chatbots powered by RAG (Retrieval-Augmented Generation) your chatbot doesn't guess, it reads your own documents to give accurate, source-grounded answers.
Unlike a generic ChatGPT integration that can hallucinate, a RAG chatbot searches your actual content in real-time before responding so customers get answers that are actually correct.
WHAT I OFFER:
- Custom AI chatbot trained on YOUR documents (PDFs, manuals, FAQs)
- ChatGPT integration, or your choice of Claude/Gemini
- Retrieval-Augmented Generation for hallucination-free answers
- Website chatbot widget, styled to your brand
- Clean handoff docs so your team can maintain it
PERFECT FOR:
- Customer support automation
- Internal knowledge base assistant
- Document Q&A for manuals or reports
Built with Python/Typescript, LangChain, and vector databases production-ready, not a fragile prototype.
Message me before ordering if your use case needs custom scoping.
Get to know churamani p.
churamani p.
FullStack Developer, FastAPI Django Backends, RAG and ML Model Deployment
- FromNepal
- Member sinceMar 2022
- Last delivery10 months
Languages
English
Software developer, 4+ yrs building AI-powered web apps & SaaS platforms. Full-stack: Next.js, React, Django, FastAPI.
Tech: Django · FastAPI · Next.js · React · Python
AI/ML: RAG chatbots · ML model deployment (XGBoost, FinBERT) · LLM integration
Cloud: AWS · Fly.io · Supabase · Docker
Deliver:
✓ Scalable web apps & SaaS platforms
✓ RAG chatbots & ML models as production APIs
✓ REST APIs & databases for web/mobile
✓ Dashboards & internal tools
10+ projects delivered · production-ready code · reliable support.
My Portfolio
FAQ
What's the difference between a RAG chatbot and a regular ChatGPT integration?
A regular ChatGPT integration answers from its general training data, which can be outdated or generic. A RAG chatbot searches your actual documents in real-time before answering, so responses are grounded in your specific, current content.
What kind of documents can I use?
PDFs, Word docs, FAQs, product manuals, policies, or website content. If you have a source I haven't listed, message me before ordering and I'll confirm it's supported.
Which AI model do you use?
I can build with OpenAI (ChatGPT), Claude, or Gemini depending on your preference or existing setup. If you're not sure which fits best, I'll recommend one based on your use case.
Can I update the chatbot's knowledge later?
Yes. The system is built so you can add or update documents as your content changes, without needing to retrain the whole chatbot from scratch.
Do I need any technical knowledge to use this?
No. You'll receive a working chatbot with clear handoff documentation. If your team wants to make future updates independently, the docs cover exactly how.
