Mukhraj

Project Overview: Built a specialized Retrieval-Augmented Generation (RAG) platform designed to provide accurate Islamic rulings and answers by querying a massive archive of Quran, Tafsir, and Hadith texts.

Technical Implementation: Architected a high-precision vector search engine using Pinecone and GPT Embeddings, enabling semantic retrieval across millions of religious texts with near-instant latency.

AI Safety & Alignment: Engineered strict prompt tuning and guardrails to ensure the LLM answers exclusively from the retrieved source material, preventing hallucinations or unauthorized content generation.

Impact: Delivered a trustworthy, verified knowledge assistant that allows users to navigate complex theological archives and receive citation-backed answers instantly.