Back to all workCase study, retail POS

Ambel POS

Billing, stock and reordering for independent shops and small chains. It bills fast with GST built in, tracks stock across shops, and tells owners what to reorder.

TypeOur own SaaS product
Our roleProduct, build, AI, launch
StatusLive, Android app on Play Store
Ambel POS homepage

The problem

A small shop owner bills on one tool, keeps stock in a notebook and reorders from memory. Running out of a best seller costs sales, and over-ordering ties up cash. Ambel puts billing, stock and reordering in one place, and is built so an owner with no tech background can set it up alone.

What it does

1

Bill

Fast checkout with GST, across several registers.

2

Sell any unit

By kg, litre, box or pack, loose or pre-packed.

3

Track stock

One view of stock across every shop.

4

Forecast

Predicts demand from each item's sales history.

5

Reorder

Tells the owner what to reorder, and how much.

The hard part:forecasts that earn their place

A new shop has no sales history, and a bad forecast is worse than none. So Ambel starts with a simple rule and only switches to machine learning when it has proven it does better.

Rule first

A clear heuristic gives sensible reorder levels from day one.

Models that compete

AutoETS, AutoARIMA and Seasonal Naive are backtested, and the winner is picked by held-out error.

Kept separate

Forecasting runs as its own Python service with read-only, least-privilege database access.

AI also helps with setup: when an owner uploads a product spreadsheet, a model suggests how its columns map to Ambel's fields, and the owner confirms before anything is imported.

2editions: India (GST) and international
2languages: English and Telugu
3forecasting models compared
1app for billing, stock and reordering

Built with

Next.jsTailwind + shadcn/uiKotlin MultiplatformCompose MultiplatformNode.js + ExpressTypeScriptPrismaSupabase PostgresClaude APIPythonStatsForecastpandasWebSocketsPlaywright

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