I will build a custom rag chatbot trained on your documents and data
Informazioni su questo servizio
Struggling to find a chatbot that actually knows YOUR business?
I build custom RAG chatbots trained on your own documents, PDFs, websites, or databases so it answers accurately, every time.
Unlike generic ChatGPT wrappers, I build production-grade RAG systems with LangChain, OpenAI GPT-4, and FAISS vector search. Your chatbot will retrieve real answers from your actual data not hallucinated responses.
What you get:
- RAG chatbot trained on your PDFs, docs, or website
- LLM-powered with GPT-4, Claude, or open-source models
- FastAPI or Flask backend with clean REST API
- FAISS or Pinecone vector database integration
- Deployed on your server or AWS EC2
- Source citations in every answer
- Full handover with clean documentation
Perfect for:
- law firms
- clinics
- SaaS products
- e-commerce
- HR teams
- Any business drowning in documents
I have built production RAG systems achieving 90%+ answer relevance. This is not a no-code tool this is real Python, real LangChain, real deployment.
Message me before ordering!
I want to understand your exact use case and guarantee the right solution for you.
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FAQ
What do you need from me to start?
Your PDFs (or sample set), what users should be able to ask, and any privacy constraints. If the bot must run fully in your environment, say so upfront.
Will the chatbot include citations?
Yes—when using RAG, I can return answers with citations/snippets pointing to the relevant sources, so users can verify.
Can you deploy it in my cloud or server?
Yes. I can containerise the service (Docker) and provide deployment guidance. If you want me to deploy, you’ll provide the target environment details.
Can it work with a local LLM?
Yes. If you prefer local inference, I can design the pipeline for a local model (subject to your hardware constraints).
Which file formats do you support?
PDFs by default; DOCX/Markdown/HTML can be added. If you have unusual formats, include a sample for validation first.
How do you reduce hallucinations?
By grounding answers in retrieved passages and enforcing answer rules (e.g., “answer only from context”). No system can guarantee zero hallucinations, but RAG dramatically improves groundedness.
Is my data kept private?
Your safest option is running ingestion and inference inside your infrastructure. If any third‑party API is used, we’ll align on what data is sent and what must remain local.
Do you build a UI too?
This Gig can include a simple demo UI (e.g., Streamlit) or API-only delivery. Website integration is available in higher packages
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R rams92

Regno Unito
Talha is a dedicated individual who consistently goes above and beyond to help.
Fino a 50 USD
$
2 giorni
Tempo
Utile?
1 recensioni per questo servizio
| (0) | ||
| (1) | ||
| (0) | ||
| (0) | ||
| (0) |
Valutazione dettagliata
- Livello di comunicazione del venditore
- Qualità della consegna
- Valore della consegna
Ordina per
R rams92

Regno Unito
Talha is a dedicated individual who consistently goes above and beyond to help.
Fino a 50 USD
$
2 giorni
Tempo
Utile?

