case://study-002
AI / Full-Stack
Project 002

HealthFlow AI

HealthFlow AI is a hospital intelligence platform that combines admissions forecasting, precomputed daily predictions, and AI-generated operational guidance for smarter planning.

7 Days
Forecast
DB-first
Serving
Full Stack
Stack
AI / Full-Stack
Category
The Problem

What Wasn't Working

Hospital teams need early visibility into admissions trends, but real-time model inference inside request handlers can increase latency and make prediction delivery harder to scale reliably.

The Solution

How I Fixed It

I built a pipeline around historical inflow plus external signals, generated forecasts ahead of time, stored them in PostgreSQL, and served them through a Next.js + Flask architecture with AI advisory responses for explanations and staffing guidance.

Stack

Technologies Used

LightGBM
Next.js 14
PostgreSQL
Flask
Groq LLM
Vercel
Results

Key Outcomes

7-day admissions forecasting workflow
Precomputed predictions instead of runtime inference
Database-first serving for lower request overhead
AI-generated trend and staffing recommendations

Want something like this?

Let's build it. I ship fast and I ship clean.