// Retail · e-commerce
Inventory Forecasting
Sales history from every channel feeds a forecast per SKU. The system tells you what to reorder, when and how much, and drafts the purchase order.
- Problem
- Stockouts on best sellers and overstock everywhere else.
- Platforms
- Web
- Stack
- Python · Django · MySQL · Claude
- Size
- Medium: several connected parts
// Live demo
Try it yourself
A working sample of the app, set up for a made-up company. Click around the way your team would.
// What we would build
Features
Every channel in one history
Shopify, Amazon, wholesale and retail sales combined per SKU.
Forecast per SKU
Seasonality, trends and promotions taken into account, with the forecast shown next to actuals.
Reorder points
Calculated from lead time and target stock cover, updated as sales change.
Draft purchase orders
Grouped by supplier, respecting minimums and case packs, ready to approve.
Overstock report
Slow movers and aging stock, so cash is not sitting on shelves.
Ask in plain English
An AI assistant answers questions like “what will run out before Black Friday?”
// Connects to
Works with what you already use
Using something else? Most systems with an API, a database or a scheduled export can be connected.
// FAQ
Common questions
How much history do we need?
A year of sales gives a useful forecast; two years captures seasonality properly. Newer SKUs borrow patterns from similar products.
Will it place orders automatically?
It drafts them. A person approves each purchase order before it is sent.
CAD + Product Development
CADs, specs and factory quotes live in email threads and folders.
Try the demo →Shipment Tracking + Issues
Shipping problems surface when the customer calls to complain.
Try the demo →Customer Proposal Builder
Reps build product offers in spreadsheets from stale stock lists.
Try the demo →// Next step
Need a inventory forecasting?
Tell us how the work gets done today. We will tell you plainly what we would build, how long it would take and what it would cost.