Portfolio

Real projects. Real outcomes.

Every project here solved a real problem for a real business — most of them Australian. No design mockups, no concept work: these are things we built, shipped and still support.

NIRAPOD Mobile App

NIRAPOD

Crowdsourced incident reports that turn into real-time risk zones and location-based safety alerts.

Result

Delivered as a production application on Firebase (Blaze) with all four MVP phases plus post-MVP work complete: 30+ screens, 7 Firestore collections with rule-level security, 11 Cloud Functions and a Flutter Web admin console. The app ships on Android and iOS (v1.2.2), with Email, Google and Apple sign-in, account deletion with full server-side data cleanup, and a decay job that keeps risk data current instead of letting stale incidents accumulate. Geohash prefix queries and topic-based fan-out keep "nearby" lookups and alert delivery to a fixed cost per user rather than scanning the whole dataset.

Real-time incident reporting with category, photo, GPS location and an anonymous option
Automatic risk-zone (red zone) generation from clustered reports, weighted by incident severity
Location-based push alerts delivered via geohash FCM topics to users in the affected area
Flutter Dart Riverpod
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HealthIQ AI AI Solution Ongoing

HealthIQ AI

Scan your food, know your health — an AI nutrition coach in your pocket.

Result

Shipped as a production cross-platform app on a live Firebase backend — 20+ Cloud Functions deployed, server-enforced entitlements and usage caps, a hosted internal admin console with live business metrics, and a Claude-powered analysis pipeline optimised from ~20 s to ~13 s per scan. The product is feature-complete through V2.4 with a subscription tier (US$5.99/mo, $49.99/yr) wired end-to-end through RevenueCat and validated against real billing events in sandbox. It is currently in store-release: Android in internal testing and iOS working through App Review, with early accounts on the platform and monetisation not yet switched on for real revenue.

AI food scanning — photo, barcode, or nutrition label, analysed in seconds
Personalised 0–10 health score computed against the user's goal, medical conditions, and allergies
Safety-critical allergen detection that caps the score and warns before logging
Flutter Dart Riverpod (hooks_riverpod)
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