App name: ScholarPair Category: Marketplace What it does:

ScholarPair connects scholarship applicants with mentors who have already won the exact scholarship they're applying for, through paid one-on-one mentorship.

Students browse scholarships, filter by type and program level, and rank up to three scholarships they're personally targeting 1st, 2nd, and 3rd choice. From there, they can view verified mentor profiles (scholarship won, university, bio, expertise, and a credibility tier) and send a mentorship request. Mentors set their own monthly rate and can guide up to five students at a time; once full, new requests join a waitlist instead of being turned away. Once a mentor accepts, the student pays to unlock in-app messaging.

The core mechanic is an automated credibility engine: when a mentee reports winning one of their target scholarships, the mentor earns points weighted by how high that scholarship ranked on the student's list. Those points build into a tier Standard, Top Rated, or Elite and that tier is the only thing ever shown publicly. The tier also sets the platform's withdrawal fee on the mentor's side, so a mentor's actual track record directly lowers what they pay to access their own earnings. Admins approve mentor profiles before they go live, manage the scholarship catalog, and oversee platform-wide analytics.

How I built on top of the AI-generated base:The initial Bubble AI prompt generated the core structure: sidebar navigation, the scholarship discovery page with working filters, the full database schema (mentor profiles, mentorship requests, scholarships, messages, payments, target scholarships), and the basic request and outcome-tracking workflows. From there, I built the credibility-points-to-tier automation, the five-mentee cap with waitlist logic on top of the AI-generated request flow, payment-gated access to in-app chat, and refined the admin approval and account management views. Live app: https://matirehmandev-60722.bubbleapps.io/version-test/?tab=Discover