Their goals: Launch a working iOS and Android app within four months Build a scalable food database with comprehensive ingredient information Use a privacy-first architecture that stores no personal data on servers Support subscriptions without collecting emails, phone numbers or logins How It Works: A user creates a profile with their specific intolerances, allergens and dietary preferences. The user scans or searches for a food product, and the app cross-references its ingredients with the profile and flags problem items. The user can follow a meal plan, track symptoms and adjust the profile as needs change. Account features run on a locally generated ID stored only on the device, so no personal data ever reaches a server. Key Features: Food Classification: Scan or search products to instantly see whether they contain ingredients the user is intolerant to Custom Intolerance Profiles: Detailed, editable profiles covering intolerances, allergens and dietary preferences Scalable Food Database: Calories and ingredient data in a structure that is easy to access and change Privacy-First Accounts: Locally generated device ID instead of emails, phone numbers or logins Demo Version: Users can try the app before buying Native iOS and Android: Built natively for speed and reliability Outcome: The app launched on schedule within the 4-month timeline, runs fast and reliably on both iOS and Android, and met the client's goals. With ongoing support it gained popularity and now serves a large global audience. Tech Stack: Native iOS and Android, custom scalable food database, locally generated device IDs.