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MobileAI & ML
PROJECT CASE STUDY // TECHNICAL NARRATIVE
Nimma-Guru
Community Mentorship Directory Powered by Google Gemini 2.0 Flash
YOUR ROLE & SCOPEAndroid Lead Intern (MindMatrix)
TIMELINE3 Months (Internship Cycle)
CORE CONSTRAINTSDelivering responsive Android Material 3 UI with multi-dialect search support
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1. THE PROBLEM
Students in non-metropolitan towns struggle to find verified local mentors for career guidance, technical skills, and exam prep.
architecture
2. TECHNICAL APPROACH & DECISIONS
1Gemini 2.0 Flash Integration
✓ DECISION CHOSEN
Integrated Google Gemini 2.0 Flash API to handle natural language mentor matching and query intent extraction.
✕ REJECTED ALTERNATIVE
Regex/SQL tag filtering
Natural language intent matching allowed students to search with conversational queries like 'someone who can teach me coding in Kannada' rather than exact database tags.
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3. TRADE-OFFS & HONEST REFLECTION
Relied on cloud Firebase and Gemini endpoints, requiring active network connectivity, but unlocked advanced dialect search capabilities.
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4. CONCRETE OUTCOME & METRICS
Shipped 10+ responsive Material 3 Compose screens connecting students with domain mentors in a 3-month cycle.
Android Jetpack ComposePlatform
Gemini 2.0 FlashAI Model
Firebase Real-time DBSync Engine
Explore Project Sources
Review live deployment or inspect codebase on GitHub.