How to Forecast Demand From Your SQL Account or AutoCount Data

If your sales sit inside SQL Account or AutoCount, you already have everything you need to forecast demand. Neura57 connects to that data, trains a model on your own sales history, and predicts demand per SKU per branch over a 30 to 90 day horizon. No data migration, no rebuilding your stack, and the first forecasts usually appear within days of connecting.

This guide explains how that works and how to get started.

Why your accounting data is enough

Every invoice, credit note, and stock movement in SQL Account or AutoCount is a data point. Over months and years, that history captures your real demand patterns: which SKUs move, when they peak, how branches differ, and how promotions shift the curve. Most businesses never use it because the data sits in tables built for accounting, not for prediction.

Neura57 reads that history through a certified connector, organises it with a semantic layer, and feeds it to a forecasting engine. You do not export spreadsheets or hire a data analyst.

The four steps to a forecast

1. Connect the data source

Neura57 connects directly to SQL Account and AutoCount using read-only access. Your live system keeps running exactly as it does today. There is no migration and no downtime.

2. Model your sales history

The platform aggregates transactions into clean daily and weekly demand series for each SKU and each branch. It cleans out one-off events, handles returns, and aligns the data so the model learns real demand rather than accounting noise.

3. Train the forecasting engine

Neura57 trains an XGBoost model on your history. It learns seasonality, day-of-week effects, branch differences, and trend, then projects demand forward. Because the model is trained on your own numbers, the forecast reflects your business, not an industry average.

4. Act on the forecast

You receive demand forecasts per SKU per branch, dead stock warnings, and reorder suggestions that account for supplier lead time. Alerts arrive by email and WhatsApp, so the right person acts before a stockout or an overstock costs money.

What you can forecast

Question	What Neura57 predicts
How much will this SKU sell next month?	30 to 90 day demand per SKU per branch
Which products are about to become dead stock?	Slow movers flagged early, before they pile up
When should I reorder, and how much?	Reorder timing and quantity, with lead time built in
Which branches are trending up or down?	Branch-by-branch demand trends and anomalies

Accuracy depends on history, not magic

A forecast is only as good as the history behind it. As a rough guide, 12 months of clean sales data gives a solid seasonal forecast, and 24 months is better. New SKUs with little history are forecast using similar products until they build their own track record. Neura57 is honest about confidence, so you know when to trust a number and when to treat it as a directional estimate.

Getting started

If you run SQL Account or AutoCount, you can be forecasting within days. Neura57 connects to your data, trains on your history, and delivers forecasts and alerts without disrupting your current workflow.

Request a demo and we will show you a forecast built on your own sales data.