Computer Vision · Utility

Coin Counter

Problem, solution, stack, timeline, and outcomes — from a real product in our portfolio.

The problem

Counting large volumes of coins by hand is slow and error-prone — a daily grind for cashiers, small businesses, and collectors. Hardware coin counters solve it, but they are expensive, stationary, and overkill for most users. The idea: turn the phone people already carry into the counting machine.

The solution

We built a mobile app that uses the device camera and on-device image recognition to identify, classify, and count coins in real time. Point the camera at a pile of coins and the app detects each denomination, keeps a running total, and lets the user save or share counts. The recognition pipeline was tuned for overlapping coins, varied lighting, and worn faces — the messy conditions real users actually shoot in.

Stack

iOS and Android mobile clients
On-device camera capture and image recognition
Denomination classification and running totals
Offline-capable processing (no network required for counts)

Timeline

Scoped in a discovery call, delivered in fixed milestones with sprint demos, then a documented handover for store-ready builds.

Outcomes

Users can count coin piles with the phone they already carry — no dedicated hardware counter.
Recognition works under overlapping coins, varied lighting, and worn faces.
Counts stay available offline because processing runs on-device.