IntegrAI
A microservices architecture for maternal health decision support using LLMs and RAG.
Overview
IntegrAI is a modern healthcare decision-support platform designed to assist health professionals in monitoring maternal health. The system combines structured clinical data, automated risk prediction, and AI-generated summaries (RAG + LLM) into a unified, scalable solution.
Architecture Highlights
The platform is built on a microservices architecture, fully containerized with Docker, ensuring modular maintenance and simplified deployment.
- Django & FastAPI: Powering the core logic and AI services.
- Asynchronous Processing: Utilizing Redis and RQ Worker to handle long-running AI tasks without blocking the UI.
- RAG (Retrieval-Augmented Generation): Powered by Qdrant vector database to provide contextualized and accurate clinical explanations.
- Scalability: Orquestrated via Docker Compose with Nginx as a reverse proxy.
Technical Workflow
- Clinical Entry: Professional fills the clinical form via the web interface.
- Synchronous Prediction: The Prediction API immediately returns the clinical risk level.
- Asynchronous Insights: A background job triggers MarIA (LLM service), which performs a RAG search to generate clinical summaries and educational “pills.”
- Feedback Loop: Results are persisted in PostgreSQL and displayed to the user via polling.
Tech Stack
| Category | Technologies |
|---|---|
| Backend | Django, FastAPI |
| AI & NLP | External LLMs (Gemini/OpenAI) + RAG |
| Databases | PostgreSQL (Relational), Qdrant (Vector) |
| Messaging | Redis + RQ |
| DevOps | Docker, Nginx |
Team & Contact
This project is developed by the LambdaGEO team at Universidade Federal do Maranhão (UFMA), in collaboration with the Postgraduate Program in Collective Health.
| Role | Name |
|---|---|
| Project Coordination | Prof. Cecília C. C. Ribeiro |
| Backend Development, Microservices & Deployment | Sergio S. Costa |
| Prompt Engineering | Pedro A. F. França, João D. S. de Almeida, João O. B. Diniz |
| Research & Health Domain | Rafaela V. P. Sá, Silas Alves-Costa, Poliana C. de A. F. Viola, Bruno F. de Souza |
For collaborations or inquiries, reach out at sergio.costa@ufma.br.