ScholarshipMatch AI

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  student_profile

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  Scholarship_matcher_ai

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  Scholarship_matcher_ai

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  Scholarship_matcher_ai

Inspiration Many students miss scholarships and welfare schemes they qualify for, because the information is scattered and the eligibility rules are confusing.

What it does A student enters their income, marks, course, state, category and entrance exam. ScholarshipMatch AI filters out schemes they clearly don’t qualify for, then Gemini ranks the rest with a match score, a plain-language explanation, and the next step. Every result links to the official source.

How we built it Python and Streamlit for the interface, transparent Python rules for first-pass eligibility filtering, and the Gemini API to rank and explain the matches. If Gemini is unavailable, the app falls back to the rule-based ranking, so it keeps working.

Challenges we ran into Handling model deprecations and API errors, keeping AI explanations tied to the supplied scheme data, and making sure the app never shows invented scholarships.

What we learned Combining deterministic rules with an LLM gives results that are both explainable and easy to understand.

What’s next More schemes and states, deadline reminders, Tamil and Hindi support, and automatic checks against official sources.

Built With

• gemini
• github
• python
• streamlit