Build RAG-Powered Mobile App for Localized College DataBuild RAG-Powered Mobile App for Localized College Data
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The Solution: I am building Corex AI, a mobile application that uses a Retrieval-Augmented Generation (RAG) architecture to ground AI models (OpenAI, Gemini, Claude) directly in localized college data.
How it Works:
Users upload their specific course materials, such as syllabus notes for CTE 323 or Electronics II, into the "Department Files" module [source: 1].
The system chunks and stores these documents in a vector database for semantic search.
When a user queries the "Math Solver" feature, the backend retrieves the precise formula methodologies from their lecturer's notes [source: 1].
The LLM generates a step-by-step calculation—like the Laplace Transform solution showcased in the interface—mirroring the exact grading rubric expected by the department [source: 1].
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The network for creativity
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