System Architecture
A comprehensive look at the technical implementation, system design, and engineering decisions behind CuraSense's AI-powered healthcare platform.
Frontend
Next.js 14
Backend
FastAPI
AI Engine
Gemini Pro
Vector DB
ChromaDB
Layered Architecture
A modular, scalable architecture designed for reliability and maintainability
Presentation Layer
Next.js 14 Frontend
API Layer
FastAPI Backend
Intelligence Layer
Multi-Agent AI System
Data Layer
Storage & Retrieval
Multi-Agent Workflow
Specialized AI agents working in concert to deliver accurate medical insights
Document Analyzer
Extraction & Parsing
Extracts text, tables, and structured data from uploaded PDFs and images
Medical Expert
Clinical Interpretation
Provides expert-level medical interpretation and analysis
Drug Interaction
Safety Analysis
Checks for medication conflicts and provides safety recommendations
Report Generator
Output Synthesis
Compiles findings into comprehensive, readable reports
Processing Pipeline
async def process_medical_document(file: UploadFile):
"""Process uploaded medical document through AI pipeline."""
# Step 1: Extract content from PDF/Image
content = await extract_document_content(file)
# Step 2: Initialize multi-agent crew
crew = MedicalAnalysisCrew(
agents=[
document_analyzer,
medical_expert,
drug_interaction_checker,
report_generator
],
verbose=True
)
# Step 3: Stream results via SSE
async for update in crew.execute_async(content):
yield ServerSentEvent(update)
Built With Modern Stack
Frontend
Backend
AI/ML
Infrastructure
Enterprise Grade
HIPAA-Compliant Design
Session-based data isolation with 15-minute TTL ensures patient data privacy
Sub-30s Response Time
Optimized pipeline delivers comprehensive analysis in under 30 seconds
Real-time Streaming
Server-Sent Events provide live updates during AI processing
98.5% Accuracy
Multi-agent validation ensures high accuracy in medical analysis
Ready to explore more?
Check out the source code or try the live demo