I will make ai chatbot with rag on your documents

I
ibraheem0786
I
ibraheem0786
Ibraheem

About this gig

You have documents. Reports. Manuals. PDFs full of valuable information. And right now your team is either searching through them manually or not using them at all.

I build AI chatbots that read your documents and answer questions from them accurately using RAG (Retrieval Augmented Generation), not hallucination.

The difference between a good RAG system and a bad one is not the AI model. It's the pipeline. Chunking strategy, embedding quality, retrieval accuracy, reranking. I've built this in production. I know where it breaks and how to make it not break.

WHAT YOU GET:

Your documents uploaded and indexed into a vector database (Qdrant)

Semantic search that finds the right chunk, not just keyword matches

AI that answers from your actual content and says "I don't know" when the answer isn't there

FastAPI backend with clean /chat endpoint ready to integrate

Optional: full chat UI (Standard and Premium)

Optional: deployed and live (Standard and Premium)

WORKS WITH:

  • Company knowledge bases
  • Legal documents
  • Product manuals and documentation
  • Research papers
  • Internal SOPs and policies
  • Insurance reports and claims (my specialty see WizeDraft in portfolio)


Get to know Ibraheem

Ibraheem

Full Stack AI Engineer

  • FromPakistan
  • Member sinceJan 2023
  • Languages

    English
I build AI systems that work in production, not just in demos. Over the past year I've shipped two real AI products: WizeDraft — an AI report generation tool used by insurance adjusters to process claims, and WizeNews — a multi-agent news intelligence platform with hybrid retrieval. When you hire me you're not getting someone who learned LangChain last week. You're getting someone who has debugged RAG pipelines, built LangGraph agent loops, and shipped full products with real users. I'm now taking client work full-time. Let's build something that actually works.

My Portfolio