AqsA Baig
FlaskVue.jsAWSAIHealthcareRedis

FalcoVita — Building an AI Healthcare Platform with Flask, Vue.js & AWS

A technical deep-dive into FalcoVita's architecture: Flask REST APIs, Vue.js frontend, Redis task queues with Celery, and AWS deployment.

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12 min read1,800 views

FalcoVita is a scalable healthcare platform I built to demonstrate how AI and cloud-native architecture can be applied to a domain where reliability and security are non-negotiable.

Architecture Overview

The backend is a Flask REST API serving a Vue.js 3 (Composition API) frontend. Heavy ML inference tasks run asynchronously via Celery workers backed by Redis as the message broker. This keeps the UI responsive while long-running tasks complete in the background.

OpenAI API Integration

FalcoVita uses the OpenAI API to generate natural language summaries of patient data. Prompts are carefully engineered to produce clinically appropriate language, and all API calls go through a rate-limited middleware layer to control costs.

Multi-Layer Security

Data is encrypted at the field level using Fernet symmetric encryption before being stored in the database. Transport-level TLS is enforced at the AWS Application Load Balancer. JWT-based RBAC controls access to patient records with audit logging on every sensitive operation.

20+ Data Visualizations

Chart.js powers over 20 interactive charts — trend lines, risk heatmaps, demographic breakdowns — all rendered client-side from aggregated, anonymized data served by the Flask API.

"In healthcare software, security is not a feature — it's the foundation."
Tags:FlaskVue.jsAWSAIHealthcareRedis

Written by AQSA ZAM ZAM MIRZA JOHAR BAIG

AI/ML Engineer & Full-Stack Developer

B.Tech CSE (AI/ML) at VIIT Pune (CGPA 8.77) and BSc Data Science at IIT Madras. AWS Certified Cloud Practitioner. Writes about DSA, ML, AWS, and full-stack engineering.

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