KYKirlos Yousef
All work

Applied AI · Health & fitness

Plot My Calories — AI Food Scanner

A camera-first nutrition product that uses vision-based AI to turn a meal photo into an immediately useful nutritional breakdown.

Role
Lead iOS Engineer
Period
2025
Platforms
iOS
Plot My Calories AI app icon with black lettering on pink
Contribution

Built the iOS product from zero to one, including image input, AI processing, concurrency, and the result experience.

0 → 1

product delivery

Responsive

non-blocking AI workflow

Product context

Plot My Calories reduces the effort of nutrition tracking: take a photo and receive a structured view of calories and nutritional impact. The product needed to make a complex AI operation feel like one direct interaction.

Engineering approach

Image preparation, networking, and model work are coordinated with Swift Concurrency so processing never blocks the interface. The result experience converts the response into a consistent visual structure that is easier to scan than unformatted model output.

What the work demonstrates

This project shows zero-to-one delivery, vision-based AI integration, concurrent iOS engineering, and the product thinking required to turn a model capability into a focused consumer experience.

Engineering challenges

  1. Move image and AI processing through the product without blocking interaction.
  2. Turn uncertain model output into a legible, useful nutrition result.
  3. Keep the camera-to-result flow fast and understandable.

Key decisions

  1. Used Swift Concurrency to keep networking and AI processing away from UI work.
  2. Designed the experience around a single photo-to-insight path instead of manual food entry.
  3. Presented nutritional output as a clear hierarchy rather than raw model text.

Next case study

LNER