03 — Web Platform & Automation
Manarah
A premium Islamic mentorship platform with an integrated 1-on-1 application form, backed by a database and load-tested for concurrent submissions.

Manarah is an Islamic mentorship platform designed to help Muslims strengthen their relationship with Allah, build discipline, find clarity, and work toward their personal goals through Islamic guidance, accountability, and 1-on-1 mentorship. The website is a single-page premium landing page with the application form built directly into the page. The application collects the applicant's background, current struggles, goals, commitment, financial readiness, and expectations from mentorship, and stores every submission in a PostgreSQL database via Supabase.
Overview
Manarah is an Islamic mentorship platform designed to help Muslims strengthen their relationship with Allah, build discipline, find clarity, and work toward their personal goals through Islamic guidance, accountability, and 1-on-1 mentorship. The website is a single-page premium landing page with the application form built directly into the page. The application collects the applicant's background, current struggles, goals, commitment, financial readiness, and expectations from mentorship, and stores every submission in a PostgreSQL database via Supabase.
The Challenge
Manarah needed a calm, premium web presence that reflects a luxury Islamic aesthetic while reliably collecting detailed mentorship applications — without the overhead of user accounts, logins, or an admin portal.
The Solution
We designed a dark, minimal landing page with gold accents, elegant typography, Islamic geometric patterns, and smooth animations, with the application form embedded directly in the page and submissions stored in Supabase as the central source of information.
What We Built
A fully responsive single-page site (desktop, tablet, and mobile) with an integrated application flow: Landing Page → Application Form → Database → Application Review → 1-on-1 Mentorship. The interface was manually refined to eliminate issues such as horizontal scrolling on smaller devices. A future pipeline is in development: Supabase → Python → AI Applicant Evaluation → Qualification Status → Excel/CSV Report → Email.
Tech Stack
Skills / Capabilities
Result / Outcome
Load-tested with k6 using 50 concurrent virtual users, the application processed 5,388 submissions with a 100% success rate and an average response time of approximately 276 ms.
