Shelfie
Smart inventory intelligence for households and small businesses. Computer vision meets inventory algorithms to track what you have, what you need, and when to buy.
See it, track it, predict it
Vision Layer
Camera-based shelf scanning identifies products, reads labels, and estimates quantities from a single photo.
Inventory Engine
Tracks consumption patterns, calculates depletion rates, and maintains real-time stock levels across locations.
Prediction System
ML-based reorder recommendations. Knows when you'll run out before you do and suggests the optimal buy time.
What it's built with
Hard problems in inventory
Shelf recognition at scale
Training vision models to recognize thousands of product SKUs from phone camera photos in variable lighting conditions — not a lab environment.
Consumption prediction
Building accurate depletion models from sparse data. Households don't scan items out — the system has to infer usage from periodic shelf snapshots.
Mobile-first architecture
Heavy CV processing happens server-side, but the UX must feel instant. Optimistic updates and background sync keep the app responsive.
Multi-tenant inventory
Same system serves households tracking groceries and businesses managing stockrooms. Shared core, different rules and interfaces.