01 / 03 · 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.
SOLO · END TO ENDLIVE ON THE APP STORE
AI-NATIVE MAXIMISER
I direct frontier AI systems, verify their output and ship useful products end to end.
British citizen · Fluent Arabic & English · Open to relocation

SELECTED WORK
My selected work.
Three systems I designed, directed and shipped across product, AI and data.
01 / 03 · 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.
SOLO · END TO ENDLIVE ON THE APP STORE
02 / 03 · FINAL-YEAR COMPUTER-SCIENCE PROJECT
UNIVERSITY OF LIVERPOOL · COMP390
A support-triage system combining deterministic checks, structured AI analysis and explicit human-approval gates.
47 PASSING TESTSHUMAN APPROVAL BY DESIGN
03 / 03 · RELATIONAL DATA SYSTEM
SYNTHETIC DATASET · REPRODUCIBLE SQL
A relational commerce data system designed around typed constraints, analytical views and reproducible SQL queries.
8 CONNECTED TABLES2 ANALYTICAL VIEWS
Revenue by category: delivered orders, net of discounts
SELECT p.category,
ROUND(SUM(oi.quantity * oi.unit_price_at_purchase
- oi.discount_amount), 2) AS net_revenue
FROM order_items AS oi
JOIN orders AS o ON o.id = oi.order_id
JOIN products AS p ON p.id = oi.product_id
WHERE o.status = 'delivered'
GROUP BY p.category
ORDER BY net_revenue DESCVERIFIED OUTPUT
Books6,857.80
Clothing6,324.86
Toys5,839.44
SYNTHETIC DATASET · GBP
SHIPPED QUERY · LIVE-VERIFIED OUTPUT · 8 TABLES · 2 VIEWS
ABOUT
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.
BSc Computer Science
72% · First Class