c
chnaumankamboh

Danish

@chnaumankamboh

Creating Smart AI, Levels and 3D Assets for Your Game

Pakistan
Spanish, French, English, Urdu
About me
Hi! I’m Danish, BS Intelligent Systems & Robotics graduate (CGPA 3.45) with hands-on experience building AI-powered desktop and web applications. I have shipped a full-stack POS system currently in active daily use at a restaurant, a real-time face recognition attendance platform deployed for university use, and a RAG-based document chatbot — all independently designed and built. My core strengths are Python, computer vision, LLM integration, and turning AI research into working software.... Read more

Skills

c
chnaumankamboh
Danish
Offline • 
Average response time: 1 hour

See my services

AI Websites & Software
I will build a custom ai chatbot that answers questions from your documents
AI Websites & Software
I will build an ai chatbot for your website or business

Work experience

Freelancing_Career

Freelancing Career

Freelance • 6 yrs 6 mos

Real-Time Face Recognition Attendance System Application for a University

May 2024 - Present2 yrs 2 mos

Developed a real-time face recognition desktop app with live camera feed, student enrollment, and automatic clock-in/out. Synced attendance records to Firebase for cloud storage and remote access. Built a multi-screen Tkinter GUI covering login, dashboard, live view, reports, and class management. Packaged the entire application as a standalone Windows executable using PyInstaller.

Moon Pizza House — POS System

May 2024 - Present2 yrs 2 mos

Built a full-featured desktop POS application currently in live daily use at a Lahore restaurant. Architected a custom REST API from scratch (no Express) with a lightweight JSON-based data store. Implemented role-based access (Owner / Cashier), daily & monthly sales reports, expense tracking, and Excel export. Network-accessible over WiFi so staff can use it on phones without installing anything.

RAG-Based Document Chatbot

May 2024 - Present2 yrs 2 mos

Built a document Q&A system that lets users upload PDFs and query them in natural language. Implemented OCR preprocessing for scanned documents and semantic retrieval using MiniLM embeddings. Served the pipeline through a FastAPI backend with a Streamlit frontend.