AI AND AUTOMATION BUILDER

TAREK
ABDELDAYEM

I direct frontier AI systems, verify their output and ship useful products end to end.

British citizen · Fluent Arabic & English · Open to relocation

Portrait of Tarek Abdeldayem in profile, looking upward, in a white shirt against a bright studio wall

Selected work

SELECTED WORK

My selected work.

Selected projects across product, AI, data and automation, from live apps to tools built for real administrative work.

Project 01 of 05: RUKNA

01 / 05 · LIVE IOS PRODUCT

SHIPPED JULY 2026

A live iOS product that turns photographed local timetables into editable schedules, adds anomaly checks and supports dependable daily tracking.

103 DAYS TO THE APP STORE~500K ORGANIC LAUNCH VIEWS

Rukna camera screen scanning a printed mosque timetable, with extracted times pinned as calloutsRukna home screen with the day's five prayers logged and a 40-day streak

SCAN → LIVE SCHEDULE · APP STORE SCREENS · DEMO DATA

Project 03 of 05: COMMERCELENS

03 / 05 · RELATIONAL DATA SYSTEM

SYNTHETIC DATASET · REPRODUCIBLE SQL

Project 04 of 05: N8N HIGHLIGHTS

04 / 05 · PRODUCTION AUTOMATION

TWO SHIPPED FLOWS · GRAVITURE

Two shipped n8n systems behind my agency: a research pipeline that turns raw search results into typed, evidence-bound lead records, and a proposal pipeline that turns a brief into a client-ready deck.

TWO PRODUCTION FLOWSNO INVENTED FIELDS

Project 05 of 05: FIELDWORK SYSTEMS

05 / 05 · CLIENT WORK · UNIVERSITY FIELDWORK

REGISTRATION + HEALTH WORKFLOW

Two tools built for a university lecturer, turning field-course administration into structured rosters, visible follow-ups and ready-to-use documents.

TWO COMPLETE WORKFLOWSLOCAL HEALTH-DATA PROCESSING

ABOUT

I use AI as a production system, not as a substitute for judgment.

I am a computer science graduate who works across product direction, AI orchestration, data, testing, design and distribution. I do not treat model output as finished work: I set the brief, shape the context, inspect failures and keep iterating until the result is coherent and usable.

Rukna is the clearest proof of that approach: I took it from a conversation to a live App Store product, owning the product direction, interface, extraction workflow, backend, testing, launch and early distribution. My support-triage project taught me to constrain and evaluate AI rather than trust it blindly. CommerceLens strengthened the relational data foundations beneath that work.

The current chapter is AI automation. Inside Maker School I completed a six-hour n8n course and now build automations for Graviture, my own AI agency, including a lead intelligence engine that turns scraped prospect data into typed, evidence-bound sales intelligence and an LLM pipeline that converts it into personalised client proposals. I also delivered two tools for a university lecturer, covering field-course group registration and local health-document processing. Alongside that I am studying persuasion through Northwestern's Leadership Through Social Influence course.

University of Liverpool

BSc Computer Science

72% · First Class

  • British citizen
  • Fluent Arabic and English
  • Open to relocation