Software Engineer & Creator

Vortana Say

I build Android apps, and I write about what I'm learning — including a book that makes machine learning practical for mobile developers.

View My Work → Read My Book

Apps

Apps I've Built

Mobile apps designed to solve real problems with elegant, intuitive solutions.

Study for the 2025 U.S. citizenship civics test offline, at your own pace. Practice all 128 questions with mock interviews, flashcards, and reading and writing tasks in English, Spanish, or Hindi.

Mock Interview Flashcards Offline EN / ES / HI

Google Play

Professional teleprompter app for content creators, speakers, and video producers. Features smooth scrolling, customizable display, floating window mode, and more.

Teleprompter Floating Window Custom Themes Cloud Sync

Google Play

Books

Written for Builders

Practical guides for developers who learn by building real projects.

Machine Learning for Android Engineers

From Theory to On-Device Inference • 134 pages • 6 chapters

Build FinRisk — a complete credit risk assessment app running a trained ML model entirely on-device. No server, no API calls, no internet required. Train in Python, convert to TFLite, run inference in under 15ms on Android with Clean Architecture + Hilt + Compose.

Complete end-to-end project: Python training to Android inference
Models are 1.8 KB and 2.6 KB — smaller than most app icons
Every Kotlin class and Python function explained line by line
Production chapter: testing, crash reporting, feature flags, model updates

Gumroad Amazon Free Chapter 1

Articles

Recent Writing

Thoughts on Android development, machine learning, and building real products.

Medium

I Built an ML-Powered Android App in 1.8 KB — Here's Why I Turned It Into a Book

March 2026

The story behind building a credit risk classifier that runs on-device, and why I wrote a book to teach other Android engineers to do the same.

Read article → Towards AI

From CS230 Theory to Production Android: Building a Privacy-First Credit Risk Classifier

February 2026

Taking deep learning theory from Stanford's CS230 and applying it to a production Android app with on-device inference.

Read article → ProAndroidDev

Android Studio Journeys: From Demo to Enterprise-Scale Testing

September 2025

A deep dive into Android Studio's Journeys feature and how to scale it from simple demos to enterprise-grade test coverage.

Read article → Medium

Breaking the Monolith: A Step-by-Step Guide to Modularizing Your Android App

September 2025

A practical 4-part series on modularizing Android apps, from identifying module boundaries to migrating shared code.

Read series →

All articles on Medium All articles on Hashnode

About Me

I'm a software engineer specializing in Android development. I build apps and write about the craft — architecture, testing, modularization, and whatever I'm learning next.

Machine learning is one of those next things. I took courses, built with it, and wrote a book so other Android engineers can put on-device ML to work without a PhD. The best way I've found to learn is by shipping a real project, not just reading papers.

When I'm not coding, I'm writing — mostly about Android, sometimes about where mobile and ML meet.

Book Published

Apps on Play Store

10+

Articles Written

10K+

App Users

Contact

Let's Connect

Have questions, feedback, or want to collaborate? I'd love to hear from you.

sayvortana.itc@gmail.com