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You will get RAG System — Chat with Your Documents (PDF, CSV, Notion)

Omar H.Status: Offline
Omar H.
Preview image

Let a pro handle the details

Buy Other Databases services from Omar, priced and ready to go.
Omar H.Status: Offline
Omar H.
Preview image

Let a pro handle the details

Buy Other Databases services from Omar, priced and ready to go.

Project details

I'll build a Retrieval-Augmented Generation (RAG) system that lets you ask natural language questions over your own documents — PDFs, CSVs, Word files, Notion pages, or websites. No more ctrl+F — just ask, and get accurate answers with source references.
Uses LangChain or LlamaIndex with FAISS or ChromaDB for vector storage, and your choice of LLM. Ideal for knowledge bases, internal documentation, legal docs, or research corpora.
Database Type
MySQL, Oracle, PostgreSQL, MongoDB, LevelDB

What's included $150

These options are included with the project scope.

$150
  • Delivery Time 6 days
  • Number of Revisions 2
    • Source Code
Optional add-ons You can add these on the next page.
Fast 5 Days Delivery
+$40
Additional Revision
+$20
Omar H.Status: Offline

About Omar

Omar H.Status: Offline
AI & Machine Learning | Artificial Intelligence, Generative AI
Cairo, Egypt - 10:08 am local time
I'm an AI & LLM Engineer based in Berlin, specializing in building production-grade AI systems, from RAG pipelines and LLM-powered chatbots to Python automation and secure multi-agent architectures.
Currently completing my M.Sc. in Artificial Intelligence & Security at GIU Berlin, with a thesis focused on adversarial robustness and prompt injection defense for LLMs. I combine deep AI knowledge with real engineering experience.

What I build for clients:
• RAG systems that actually work, not toy demos, but reliable retrieval pipelines with FAISS/Chroma and LangChain/LlamaIndex
• AI chatbots and agents powered by OpenAI, Anthropic, or open-source models
• Python automation scripts that save hours of manual work
• REST APIs and backends in Python (FastAPI/Flask) or Java (Spring Boot)
• LLM security audits and prompt injection testing

I've built LLM backends during my internship at Deloitte, and I deliver clean, documented, production-ready code. I communicate clearly in English and turn projects around fast.

If you need an AI engineer who can hit the ground running — let's talk.

Steps for completing your project

After purchasing the project, send requirements so Omar can start the project.

Delivery time starts when Omar receives requirements from you.

Omar works on your project following the steps below.

Revisions may occur after the delivery date.

Requirements call

confirm document types, questions, and output format

Ingest and chunk documents into vector store

Review the work, release payment, and leave feedback to Omar.