Welcome

ZeyadDiaa

AI engineer building AI agents, retrieval systems, and LLM applications, from data pipelines to production deployment

About me

Building systems thathold up in production

I design and deploy AI systems that connect models to real workflows. My work spans retrieval-augmented generation (RAG), AI agents, document understanding, and backend engineering. I currently build enterprise AI solutions for HR and ERP operations, taking systems from the first data pipeline through deployment and helping teams use them

Experience

Backend foundations,AI in production

Jan 2026 — Present
Building enterprise AI agents and LLM systems that automate HR and ERP operations, from prototype through to production, and training the teams who use them
2024 — Present
Independent client work across AI and backend — LLM applications, APIs and services, workflow automation, and data pipelines and dashboards
Sep 2025 — Jan 2026
Applied AI across retrieval, document understanding and computer vision — building RAG pipelines, fine-tuning models, and automating the workflows around them
May 2024 — Aug 2025
Production backend engineering — designing microservices and REST APIs, and the data and search layers behind them

Selected Work

Systems I have built, end to end

PolySumm: Multimodal RAG for Scientific Paper Summarization
A multimodal RAG system that reads a scientific paper end to end — text, figures and tables — and writes a summary grounded in all three
Tech Stack
Detectron2
Concepts & Techniques
LoRA/PEFT
Repositoryfor PolySumm: Multimodal RAG for Scientific Paper SummarizationLive demo
Agentic Analysis: Multi-Agent AI Data Analyst
A crew of role-specialised agents that turns a raw spreadsheet into an executive-ready report, charts and all
Tech Stack
Concepts & Techniques
LLMs
Agentic AI
Prompt Engineering
Repositoryfor Agentic Analysis: Multi-Agent AI Data AnalystLive demo
Video RAG Assistant: Question Answering over Video
Ask a question about a video and get an answer back with the timestamp it came from
Tech Stack
Sentence Transformers
Concepts & Techniques
LLMs
RAG
Repositoryfor Video RAG Assistant: Question Answering over VideoLive demo
Large Route Optimization using Genetic Algorithms
A genetic algorithm that plans multi-truck delivery routes against cost, distance and deadlines at once
Tech Stack
Concepts & Techniques
Genetic Algorithms
Multi-Objective Optimization
Repositoryfor Large Route Optimization using Genetic Algorithms Live demofor Large Route Optimization using Genetic Algorithms
PDF Layout Grid Analysis
Tiles an architectural drawing into crops a vision model can read, and returns structured data
Tech Stack
Concepts & Techniques
Vision-Language Models
PDF Processing
Repositoryfor PDF Layout Grid AnalysisLive demo
PSO Clustering Variations Explorer
An interactive comparison of K-Means against six particle-swarm clustering variants
Tech Stack
Concepts & Techniques
Clustering
Repositoryfor PSO Clustering Variations Explorer Live demofor PSO Clustering Variations Explorer
Image Processing Algorithms
Classic computer-vision operators, implemented from scratch behind a live interface
Tech Stack
Concepts & Techniques
Computer Vision
Repositoryfor Image Processing Algorithms Live demofor Image Processing Algorithms

Expertise

How I can help,and what it takes

A chatbot that answers from your own documents — contracts, manuals, research — and shows you where each answer came from

Answers grounded in your files, not guesswork
Retrieval-augmented generation (RAG)
Citations back to the source page
Chat over documents, audio and video

Selected Writing

Things I’ve worked out,
written down

All posts

Loading writing…

Contact

Start withthe problem

Have a role, project, or technical challenge in mind? Share what you are building, where you need help, and any timeline. I will reply with practical next steps

Cairo, Egypt

Would rather talk it through?

Book a call

ZeyadDiaa

Building systems thathold up in production

Backend foundations,AI in production

Consultant AI Engineer

AI & Backend Engineer

AI Engineer

Junior .NET Developer

Systems I have built, end to end

PolySumm: Multimodal RAG for Scientific Paper Summarization

Agentic Analysis: Multi-Agent AI Data Analyst

Video RAG Assistant: Question Answering over Video

Large Route Optimization using Genetic Algorithms

PDF Layout Grid Analysis

PSO Clustering Variations Explorer

Image Processing Algorithms

How I can help,and what it takes

Things I’ve worked out,
written down

RAG Systems: A Deep Dive into Retrieval-Augmented Generation

AI Engineer vs ML Engineer vs Data Scientist: What's the Difference?

Reinforcement Learning for LLMs: RLHF, PPO, GRPO, DPO, RLAIF, and Reasoning

Start withthe problem

Things I’ve worked out,
written down

RAG Systems: A Deep Dive into Retrieval-Augmented Generation

AI Engineer vs ML Engineer vs Data Scientist: What's the Difference?

Reinforcement Learning for LLMs: RLHF, PPO, GRPO, DPO, RLAIF, and Reasoning

ZeyadDiaa

Building systems thathold up in production

Backend foundations,AI in production

Consultant AI Engineer

AI & Backend Engineer

AI Engineer

Junior .NET Developer

Systems I have built, end to end

PolySumm: Multimodal RAG for Scientific Paper Summarization

Agentic Analysis: Multi-Agent AI Data Analyst

Video RAG Assistant: Question Answering over Video

Large Route Optimization using Genetic Algorithms

PDF Layout Grid Analysis

PSO Clustering Variations Explorer

Image Processing Algorithms

How I can help,and what it takes

Things I’ve worked out,written down

RAG Systems: A Deep Dive into Retrieval-Augmented Generation

AI Engineer vs ML Engineer vs Data Scientist: What's the Difference?

Reinforcement Learning for LLMs: RLHF, PPO, GRPO, DPO, RLAIF, and Reasoning

Start withthe problem

Things I’ve worked out,written down

RAG Systems: A Deep Dive into Retrieval-Augmented Generation

AI Engineer vs ML Engineer vs Data Scientist: What's the Difference?

Reinforcement Learning for LLMs: RLHF, PPO, GRPO, DPO, RLAIF, and Reasoning

Things I’ve worked out,
written down

Things I’ve worked out,
written down