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AI-Powered Care Navigation & Healthcare Financing for India

From first symptom to financing approval — guided by AI, every step of the way.

---

What is MedPath AI?

MedPath AI is a full-stack conversational healthcare navigation platform built for the Indian market. Describe your symptoms in plain language — the AI figures out what procedure you need, finds the right hospitals in your city, shows a personalised cost breakdown adjusted for your medical history, and walks you through applying for a Poonawalla Fincorp medical loan. All in one chat.

No phone calls. No clinic hopping. No guesswork.

---

Features

• Conversational clinical intake — Gemini 2.5 Flash extracts procedure, city, urgency, and ICD-10 codes from plain language
• Emergency bypass — detected at ≥85% confidence, skips clarification entirely and surfaces hospitals immediately with a red alert banner
• Intelligent hospital ranking — scored by cost match, quality rating, NABH/JCI accreditation, wait time, and GPS distance
• Personalised cost breakdowns — comorbidity multipliers (diabetes, cardiac, kidney, etc.) applied on top of procedure base costs
• PFL loan pre-qualification — instant GREEN / YELLOW / RED eligibility decision based on CIBIL, income, FOIR, and loan multiple
• Gemini document extraction — upload your salary slip or CIBIL report and the AI fills in your financial profile automatically
• Real-time loan tracking — patient app polls loan status every 3 seconds; sees the officer's decision the moment it's made
• 5-step registration wizard — health profile, comorbidities, insurance, financials, and emergency contact
• Spectator-safe officer dashboard — completely separate Vite build for PFL officers; ships zero patient code

Coming Soon

• AI second opinion — challenge a hospital recommendation with a follow-up question
• User profiles — persistent health history and past consultation summaries
• Real PFL API — live Poonawalla Fincorp loan disbursement integration

---

Tech Stack

┌──────────────────────────────────────────────────────────┐
│                React 19 + Vite (Frontend)                │
│        React Router 7 · Tailwind v4 · Zustand 5          │
└─────────────────────┬────────────────────────────────────┘
                      │ HTTP + REST
         ┌────────────┴────────────┐
         │                         │
┌────────▼────────┐      ┌─────────▼──────────┐
│  FastAPI 0.115  │      │  Supabase (Postgres) │
│  LangGraph      │◀────▶│  + Storage Bucket    │
│  Pipeline       │      │  9 tables            │
└────────┬────────┘      └─────────────────────┘
         │
    ┌────┴──────────────────────────┐
    ▼            ▼                  ▼
 INTENT       PROVIDER           COST + RESPONSE
 Gemini       Pure Python        Formula Engine
 2.5 Flash    Hospital           + Gemini
 Clinical     Scoring            2.5 Flash
 Intake       Engine

Layer	Technology
Frontend	React 19, Vite 8, Tailwind CSS v4, React Router 7
State	Zustand 5, custom hooks (useChat, useLoan, useDocuments)
Backend	FastAPI 0.115, Uvicorn 0.30, Pydantic v2
AI Pipeline	LangGraph 0.2.28, Gemini 2.5 Flash
Clinical Intake	gemini-2.5-flash (intent extraction, ICD-10 mapping)
Relevance + Scoring	Pure Python, Pandas, Haversine distance
Document Extraction	gemini-2.5-flash (PDF/image → structured JSON)
Database	Supabase Postgres + Supabase Storage

---

Getting Started

Prerequisites

• Node.js 20+
• Python 3.11+
• A Supabase project (free tier works)
• A Google Gemini API key (Gemini 2.5 Flash access required)

1. Clone the repo

git clone https://github.com/yourusername/MedPathAI.git
cd MedPathAI

2. Backend — Python environment

python -m venv venv
source venv/bin/activate          # Windows: venv\Scripts\activate
pip install -r requirements.txt

3. Backend — environment variables

Create a .env file inside backend/:

SUPABASE_URL=https://<your-project>.supabase.co
SUPABASE_KEY=<your-supabase-anon-or-service-key>
GEMINI_API_KEY=<your-gemini-api-key>
DOCUMENT_BUCKET=medical-documents
DOCUMENT_EXTRACTION_ENABLED=false

4. Run the backend

python ./backend/main.py   # → http://localhost:8000

5. Frontend

cd medpathai
npm install
npm run dev         # → http://localhost:5173 (patient app)
npm run dev:pfl     # → http://localhost:5174 (PFL officer dashboard)

6. Verify everything is running

• http://localhost:5173 → Patient chat app
• http://localhost:5174 → PFL officer dashboard
• http://localhost:8000 → {"status": "MedPath AI is running 🚀"}
• http://localhost:8000/docs → FastAPI Swagger UI (test /api/chat here)

On first run the backend loads hospital, procedure, and city data from Supabase into memory. Seed CSVs are in backend/data/.

---

How It Works

1. Register with your health profile, comorbidities, insurance details, and financials
2. Upload financial documents — salary slip, ITR, CIBIL report (Gemini extracts the data automatically)
3. Open the chat and describe your symptoms or the procedure you need
4. The AI asks up to 3 targeted clarifying questions — then commits to a recommendation
5. Get a ranked list of hospitals in your city with personalised cost breakdowns
6. Select a hospital and apply for a Poonawalla Fincorp medical loan in one click
7. The AI runs an instant eligibility check and submits your application
8. Track your loan status live — the PFL officer's decision appears in seconds

---

ML Scoring Pipeline

Every argument — sorry, every argument in the chat — runs through four stages in the LangGraph pipeline:

Node	Model / Engine	Role
Intent	Gemini 2.5 Flash	Extracts procedure, city, budget, urgency, emergency flag, ICD-10 hint
Provider	Pure Python + Pandas	Scores hospitals by cost, quality, accreditation, wait time, GPS distance
Cost	Formula Engine	Personalised breakdown with comorbidity multipliers + PFL loan options
Response	Gemini 2.5 Flash	Generates warm, clinically-phrased summary or emergency alert

Comorbidity multipliers: Kidney Disease +22% · Cardiac +18% · Diabetes +12% · Obesity +10% · Hypertension +8% · Asthma +6%

PFL eligibility tiers: CIBIL ≥700, income ≥₹15k/month, FOIR ≤50%, loan ≤10× income → GREEN (instant approval) · soft flags → YELLOW · hard failure → RED (alternatives suggested)

---

Project Structure

MedPathAI/
├── backend/                        # FastAPI + LangGraph server
│   ├── main.py                     # All HTTP endpoints (15 routes)
│   ├── graph.py                    # LangGraph StateGraph definition
│   ├── loan_engine.py              # PFL credit policy + EMI calculator
│   ├── db.py                       # Supabase client + all DB helpers
│   ├── data_loader.py              # Hospital search + cost formulas
│   ├── nodes/
│   │   ├── intent.py               # Gemini clinical intake node
│   │   ├── provider.py             # Hospital scoring node (pure Python)
│   │   ├── cost.py                 # Cost breakdown + loan options node
│   │   └── response.py             # Gemini response generation node
│   └── data/                       # Seed CSVs (hospitals, procedures, cities)
│
└── medpathai/                      # React 19 + Vite frontend
    ├── src/
    │   ├── screens/
    │   │   ├── Chats/              # Main chat arena + hospital cards
    │   │   ├── Documents/          # Upload + Gemini extraction UI
    │   │   ├── Loans/              # Loan history + status tracking
    │   │   ├── Login/              # Auth screen
    │   │   └── Registrations/      # 5-step onboarding wizard
    │   ├── components/             # AppShell, Sidebar, EmergencyBanner
    │   ├── hooks/                  # useChat, useLoan, useDocuments, useGeolocation
    │   ├── store/                  # Zustand: chatStore, userStore, uiStore
    │   └── api/                    # Axios helpers per domain
    └── officer/                    # PFL dashboard (separate Vite build)

---

Roadmap

• Conversational AI intake via LangGraph + Gemini
• Hospital discovery + multi-factor scoring
• Personalised cost breakdowns with comorbidity multipliers
• PFL medical loan pre-qualification engine
• Gemini-powered document extraction
• Real-time loan status tracking
• PFL officer approval dashboard (separate build)
• Emergency detection + bypass flow
• 5-step registration wizard
• Admin analytics dashboard
• AI second opinion mode
• User profile settings screen
• Real Poonawalla Fincorp API integration

---

_{Built with 🏥 by KIIT0001}