ZHSF AI Claims Reconciliation automates healthcare claims reconciliation processes for the Zanzibar Health Sector Fund using AI-powered workflows
# ZHSF AI Claims Reconciliation
This repository contains a local, Docker‑Compose based stack to prototype and develop the ZHSF AI claims reconciliation workflow. It combines workflow automation (n8n), data services (Supabase/Postgres), vector search (Qdrant), OCR, and a frontend for review.
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## 1) What this project does
The goal is to automatically reconcile healthcare claims by:
- ingesting claim documents (PDF/images),
- extracting text with OCR,
- normalizing the data,
- matching claims against reference records,
- writing reconciliation results to a database,
- and providing a UI for review and audit.
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## 2) Quick start (local)
### Prerequisites
- Docker + Docker Compose
- Node.js (only needed if you want to run the frontend locally outside Docker)
### Step‑by‑step
1. **Configure environment**
- Copy `.env.template` to `.env` and update values as needed.
2. **Start the stack**
- Run: `make start`
3. **Verify services**
- n8n:
localhost
- Supabase Studio:
localhost
- Qdrant:
localhost
4. **Stop the stack**
- Run: `make stop`
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## 3) Services & Ports
| Service | Purpose | Port |
|---------|---------|------|
| n8n | Workflow automation & orchestration | 5678 |
| n8n-postgres | n8n internal database | 5432 |
| Supabase Studio | DB management UI | 3000 |
| Supabase (Postgres/API/Auth/Storage) | Core data services | internal |
| Qdrant | Vector search / similarity | 6333 |
| PaddleOCR | Document text extraction | internal |
| Frontend | Review UI | 3000 (if run locally) |
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## 4) Repository map (what to look at first)
- `docker-compose.yml` → all services and networking.
- `n8n/` → workflows, credentials template, and reference rules.
- `supabase/` → database development assets and local setup.
- `qdrant/` → vector DB configuration.
- `paddleocr/` → OCR service.
- `frontend/` → UI for reviewing reconciliation results.
- `init-test-db/` → SQL seed data for local testing.
- `training-onboarding-zhsf.md` → full …