Back to Portfolio
Tech Stack & Tools
FastAPISupabase VectorReactPythonCI/CD
Built a scalable RAG engine parsing complex PDFs to provide instant, personalized academic support for 250+ students.
Architected a scalable RAG system powered by FastAPI and Supabase, implementing a custom RRF algorithm to support 200+ students with instant academic context.
Engineered advanced context-handling logic (Query Condensing and Map-Reduce), optimized through rigorous testing to handle complex, multi-turn conversations.
Automated CI/CD pipelines for data ingestion, decreasing deployment time from 6h to 30 min.
Investor Pitchdeck
Interact with DeckUnlocks Scroll