QuickSpend

QuickSpend is a native iOS app for logging expenses quickly: open the app, say or type a short sentence like "50k coffee yesterday", and the app extracts the amount, description, category, and date. It is offline-first, does not require an account, stores data locally, and supports import/export for backups.

Download: App Store. Landing page: quickspend.taiphanvan.dev.

Background#

Most finance apps make users walk through too many fields before saving a tiny daily transaction. QuickSpend flips that flow: capture first, fix later. The core use case is logging with text or voice in a few seconds while the app infers the rest.

Tech stack#

SwiftUI + Swift — native iOS UI with dark mode and responsive layouts.
Local-first storage — transactions, categories, settings, and backups stay on device.
Speech / AI parsing flow — natural-language input becomes amount, category, and date.
Charts + Calendar UI — interactive spending views by category, range, and month.
Recurring engine — recurring income/expense rules with pause and resume.
Import / Export JSON — portable backups for migration and restore.
StoreKit — monthly/yearly Premium subscription.

Challenges#

The hard part is reducing capture friction without making the parser feel risky. The app needs to save fast, but still keep correction cheap when the guess is wrong.

Lessons#

For personal finance, capture speed matters more than perfect detail at input time. If the flow is slow, the dataset never becomes useful enough for insights.

Download: App Store. Landing page: quickspend.taiphanvan.dev.

Background#

Tech stack#

SwiftUI + Swift — native iOS UI with dark mode and responsive layouts.
Local-first storage — transactions, categories, settings, and backups stay on device.
Speech / AI parsing flow — natural-language input becomes amount, category, and date.
Charts + Calendar UI — interactive spending views by category, range, and month.
Recurring engine — recurring income/expense rules with pause and resume.
Import / Export JSON — portable backups for migration and restore.
StoreKit — monthly/yearly Premium subscription.

Challenges#

The hard part is reducing capture friction without making the parser feel risky. The app needs to save fast, but still keep correction cheap when the guess is wrong.

Lessons#

For personal finance, capture speed matters more than perfect detail at input time. If the flow is slow, the dataset never becomes useful enough for insights.