I will build custom llm applications with rag

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hami95
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AbdurRehman

About this gig

Need a RAG system that actually works on your real data not just on a toy dataset?


I build production-grade RAG pipelines that let your team query thousands of documents with fast, accurate, contextual answers powered by the best LLMs.


WHAT'S INCLUDED:

Document ingestion pipeline (PDF, DOCX, CSV, TXT, web URLs)

Embedding generation + vector store setup (Pinecone, pgvector, Chroma)

LLM integration (OpenAI GPT-4, Claude, Gemini, or open-source)

FastAPI endpoint + LangSmith monitoring + Docker-ready deployment

Full documentation and post-launch support


Message me first I will review your use case and confirm the right package.

Get to know AbdurRehman

AbdurRehman

Senior AI Engineer

  • FromPakistan
  • Member sinceDec 2018
  • Languages

    English, Urdu, Punjabi, Spanish, German, French, Italian
With over 5 years of experience, I have built production-ready AI systems and enterprise RAG pipelines using LangChain, LangGraph, Pinecone, pgvector, FastAPI, Docker, OpenAI API, Claude API, and LangSmith. I help businesses create scalable AI infrastructure, internal knowledge search, AI automation workflows, compliance retrieval systems, document analysis tools, and KPI dashboards. Every project includes clean architecture, vector DB integration, monitoring, documentation, and long-term scalability, built for real production use, not just demos.

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