Case Study // eparchi

E-Parchi

Full-stack medical RAG pipeline and hospital management system.

RecognitionFinalist

EventUDBHAV

LogicRAG

SecurityHIPAA

DEMO_RECORDING

[ VIDEO ASSET REQUIRED ]

02 // Architecture Execution

Built a scalable medical log system with a RAG (Retrieval-Augmented Generation) pipeline. Used Firebase for real-time patient-doctor data synchronization and Next.js for a clean, intuitive clinical dashboard.

01 // The Problem Context

Digital prescription management is often fragmented. The goal was to build a system that allows doctors to manage patient logs while using AI to retrieve relevant medical history.

System Stack

Next.jsFirebasePythonLangChain

core_module.ts

// Medical RAG Retrieval Logic
def get_patient_context(patient_id):
    docs = vector_store.similarity_search(patient_id)
    chain = load_qa_chain(llm, chain_type='stuff')
    return chain.run(input_documents=docs, question='Summary of history?')

Launch Demo