You will get I will build a custom RAG AI system using Python and LLMs
Project details
You'll get a fully working RAG (Retrieval-Augmented Generation) system that lets you ask questions about your own documents and get accurate, cited answers — not generic AI guesses. I built and tested this approach on a real 22-question evaluation set, achieving 100% Hit Rate and 0.977 MRR by combining semantic search with keyword search and fixing real retrieval failures along the way.
I'm self-taught — I don't come from a traditional CS background, but I've spent the past year building working AI systems from scratch by identifying real problems and solving them step by step. I care about correctness, not just getting something that looks like it works. Every system I deliver is documented, tested against real questions, and built to actually be used — not just demoed once and forgotten.
If you have documents piling up that your team keeps searching through manually, I can turn them into something you can just ask.
I'm self-taught — I don't come from a traditional CS background, but I've spent the past year building working AI systems from scratch by identifying real problems and solving them step by step. I care about correctness, not just getting something that looks like it works. Every system I deliver is documented, tested against real questions, and built to actually be used — not just demoed once and forgotten.
If you have documents piling up that your team keeps searching through manually, I can turn them into something you can just ask.
Programming Languages
Python, TypeScriptCoding Expertise
Performance Optimization, SecurityWhat's included
| Service Tiers |
Starter
$60
|
Standard
$180
|
Advanced
$400
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 18 days |
Number of Revisions | 2 | 3 | 5 |
Number of Pages | 10 | 50 | 200 |
Design Customization | - | - | - |
Content Upload | - | ||
Responsive Design | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$25 - $100
Additional Revision
+$20
Additional Page
(+ 1 Day)
+$10Frequently asked questions
About Ibrahim
AI/Python Developer | RAG Systems, FastAPI & Automation
Baku, Azerbaijan - 6:35 am local time
WHAT I BUILD
I specialize in Retrieval-Augmented Generation (RAG) systems — tools that let you ask questions about your own documents and get accurate, cited answers instead of generic AI guesses. My main project combines semantic search with keyword search (hybrid retrieval), and I tested it properly against a 22-question evaluation set: 100% Hit Rate, 0.977 MRR. When I found a real case where hybrid search was underperforming, I diagnosed it and fixed it — I don't just build things that look like they work, I measure them.
I also build backend automation: FastAPI services, PDF/document data extraction with OCR, and third-party integrations (I've built a Zapier integration from scratch, including debugging real API payload mismatches in production).
WHY WORK WITH ME
- I'm honest about what I know and don't know. If something is outside my current skill set, I'll tell you upfront rather than overpromise.
- I document everything. Every project I deliver comes with clear documentation so you're not locked into needing me forever.
- I care about correctness. I go back and fix what's actually broken, not just what's easy to fix.
- I'm new to freelancing, which means I'm motivated to earn trust through real results, not reviews I don't have yet.
WHAT I CAN HELP WITH
- RAG / document Q&A systems
- Python backend development (FastAPI, Flask)
- PDF/document data extraction and OCR automation
- API integrations (Zapier, REST APIs, webhooks)
- LLM integration (OpenAI, Anthropic, Google, Groq, Ollama)
All of my projects are documented on GitHub — happy to share links and walk you through the code before you hire me. Let's talk about what you're trying to build.
Steps for completing your project
After purchasing the project, send requirements so Ibrahim can start the project.
Delivery time starts when Ibrahim receives requirements from you.
Ibrahim works on your project following the steps below.
Revisions may occur after the delivery date.
Review documents & clarify scope
I review your documents and clarify what kinds of questions the system needs to answer, then confirm the technical approach before starting development.
Build & test the retrieval pipeline
I build the document chunking, embedding, and hybrid search pipeline, then test it against real sample questions to verify accuracy before delivery.