MedIntel AI - Clinical Intelligence Platform with Multi-Agent RAG for Ethiopian Healthcare
# 🏥 MedIntel AI - Clinical Intelligence Platform
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## đź“– Table of Contents
1. Overview
2. The Problem To Solve
3. Solution
4. System Architecture
5. Multi-Agent System
6. Technology Stack
7. Database Design
8. Project Structure
9. Getting Started
10. Deployment
11. Success Metrics
12. Contributing
13. License
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## 🎯 Overview
**MedIntel AI** is a production-grade, privacy-first clinical intelligence platform that brings AI-powered medical decision support to healthcare workers in low-resource settings. Unlike generic AI assistants that hallucinate dangerous advice, MedIntel AI combines **multi-agent orchestration** with **Retrieval-Augmented Generation (RAG)** to deliver accurate, cited, and trustworthy medical answers—even without internet connectivity.
### 🏥 Who It's For
- **Doctors & Nurses** in Ethiopian clinics
- **NGOs** (Last Mile Health, MSF, WHO)
- **Ministry of Health** (policy and guideline dissemination)
- **Healthcare Researchers** (clinical data analysis)
- **Medical Students** (learning and reference)
### 🌟 What Makes It Different
- **Privacy-First:** Patient data never leaves the clinic (local Llama 3 deployment)
- **Offline Capable:** Works without internet using Ollama
- **Multi-Lingual:** Amharic, Oromo, Tigrinya, and English
- **Hallucination-Free:** Multi-agent evaluation with Orchestrator[Orchestrator Agent]
Orchestrator --> |Intent Analysis| Routing{Route Decision}
Routing --> |Medical| Retrieval[Medical Retrieval Agent]
Routing --> |Drug| Drug[Drug Agent]
Routing --> |Protocol| Protocol[Protocol Agent]
Retrieval --> |Documents| Synthesis[Synthesis Agent]
Drug --> |Drug Info| Synthesis
Protocol --> |Guidelines| Synthesis
Synthesis --> |Draft Answer| Evaluation[Evaluation Agent]
Evaluation --> |Check| LLM[Llama 3 LLM]
LLM --> |Verification| Evaluation
Evaluation --> |Score| SelfCorrect{Confidence |Yes| Expanded[Expand Query & Retry]
SelfCorrect --> |No| Response[Final Response]
Expanded --> Retrieval
Response --> User
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