Shipped: SAFE : AI Powered Preventive Health Monitoring

Introducing SAFE, Symptoms Analysis and Forecasting Engine.

I've been building SAFE as an AI powered preventive health monitoring platform that brings machine learning, generative AI, and cloud native engineering together.

The idea is to move beyond passive symptom tracking towards more personalized and proactive health engagement.
Some of the key components I've built:

• Hybrid ML based risk estimation using Random Forest and deterministic fallback logic.

• Gemini powered conversational health assistant with session memory.

• Risk adaptive email reminders using Celery Beat.

• Asynchronous emergency alert pipeline.

• Five service Docker Compose architecture using Django, PostgreSQL, Redis, and Celery.

The prototype has been tested with 65 user contributed profiles, and I've documented the architecture and preliminary evaluation in a research preprint on Zenodo.

SAFE is currently an independently developed project, and I'm exploring technical collaborations, integrations, research partnerships opportunities.

Interested in connecting with people working in AI, HealthTech, ML infrastructure, and cloud native systems.

research paper: zenodo.org/records/21380627