Mohamed Essam

• Built Automatio System to calculate the quantities and save more than 3 millions Riyals are wasted in calcu
lating incorrect quantities.
• Created predicted system for pricing quantities with more than 400 million Riyal

• Architected a production-grade HR Agent (LangChain, RAG, PostgreSQL, Azure) for Qatar Financial Markets
Authority, automating leave management, salary inquiries, and ERP actions; reduced HR response time by
80% and currently serving 500+ employees in production
• Developed a real-time voice-enabled chatbot for Ministry of Sports and Youth using LangChain, Redis, and
speech-to-text, enabling instant citizen inquiries and improving service accessibility by 60%
• Engineered an investor insights agent for Qatar Free Zone Authority, simulating application workflows and
delivering real-time license, lease, and investor analytics; accelerated investor onboarding decisions by 45%
• Conducted data analysis for Kawader national recruitment platform, generating workforce insights for Qatar
Civil Services, Government Development Bureau, and Ministry of Labor; informed hiring strategies impacting
10, 000+ government positions

Architected a production-grade HR Agent (LangChain, RAG, PostgreSQL, Azure) for Qatar Financial Markets
Authority, automating leave management, salary inquiries, and ERP actions; reduced HR response time by
80% and currently serving 500+ employees in production
• Developed a real-time voice-enabled chatbot for Ministry of Sports and Youth using LangChain, Redis, and
speech-to-text, enabling instant citizen inquiries and improving service accessibility by 60%
• Engineered an investor insights agent for Qatar Free Zone Authority, simulating application workflows and
delivering real-time license, lease, and investor analytics; accelerated investor onboarding decisions by 45%
• Conducted data analysis for Kawader national recruitment platform, generating workforce insights for Qatar
Civil Services, Government Development Bureau, and Ministry of Labor; informed hiring strategies impacting
10, 000+ government positions

• Contributed to a conversational AI system for Ministry of Municipalities and Housing (Saudi Arabia) with
Saudi dialect TTS and STT

• Mentored 20 students through ML/DL projects; facilitated training for 70 interns on neural networks and
real-world applications

• Constructed high-accuracy ML models (90-95%) for customer clustering and sentiment analysis; accelerated
classification speeds by 15%

• Pioneered Road Vision app for road damage detection (90%+ accuracy); slashed reporting time by 60% and
secured 70, 000 SAR Misk Foundation funding