EduTask
From a dense academic syllabus to an actionable conversation.
The Problem
Academic syllabi contain crucial deadlines, grade weightings, exam dates, and course policies scattered across 15+ page documents. Students frequently miss submission dates or misunderstand policy nuances simply because relevant context is buried in prose.
EduTask was built to bridge this disconnect: providing an intelligent retrieval system that ingests unstructured document formats (PDFs, DOCXs) and enables users to ask precise questions like "What is the late submission policy?" or "Extract all homework deadlines into a list."
System Architecture
The system combines the Unstructured API for document element extraction, LangChain for vector orchestration and contextual retrieval, and a vector database for semantic chunk retrieval.
Recorded Demo
Recorded application walkthrough demonstrating document ingestion, semantic query answering, and automated task extraction.
Next Steps & Navigation
This experiment proved how domain-specific RAG pipelines can turn passive documentation into active, conversational knowledge bases.
Next project: Anime Recommender System →