Demand forecasting
Forecast demand and stock needs from sales history, seasons and events.
The problem
Buying and stock decisions rely on spreadsheets and gut feel, leading to stock-outs on some items and cash tied up in others.
How AI helps
Forecasting models learn from your sales history, promotions, seasons and public holidays in each market, and suggest order quantities that planners can adjust.
What you'll need
- Two or more years of sales and stock history
- Product and location data
- A planner to compare forecasts with reality
How success is measured
- Forecast accuracy
- Stock-outs
- Inventory days on hand
Guardrails
- Planners keep the final say
- Forecasts show their confidence range
- Models are retrained as patterns change
Other use cases
- Document processingRead invoices, delivery orders and forms, and turn them into clean data in your systems.Read the use case
- Customer service assistantDraft accurate replies to customer emails and chats from your own policies and order data.Read the use case
- Knowledge searchLet staff ask questions in plain language across policies, manuals and past work.Read the use case
- Proposal and tender draftingProduce first drafts of proposals, tenders and questionnaires from your best past work.Read the use case
- Reporting and meeting automationTurn meetings and raw data into summaries, action lists and weekly reports.Read the use case
Not sure which seats you need?
The fit check takes about two minutes and suggests a starting bench, with reasons.