The system scans university scholarship pages, checks eligibility against a student's profile, and sends matches.
It branches. Any that apply are taken; runs once per one per university checked.
Pattern: Multiple Instances with a priori Design-Time Knowledge (13) · Multi-Choice (6)
Searching every university's scholarship page by hand and checking each one against a student's grades, citizenship, and major takes hours you don't have, especially with dozens of students. Deadlines and eligibility rules change constantly, so it's easy to miss opportunities students actually qualify for.
School counselors and financial aid offices supporting students applying for scholarships.
Students get a personalized list of scholarships they actually qualify for, pulled straight from university pages.
The hard question is not how to build it. It is whether this is the right thing to build first.
That is what a Fractional Chief AI Officer figures out with you, before anyone writes a line of code.
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