AI demand forecasting for mid-market operators
Per-SKU forecasts you can defend, built on the sales and inventory data your team already exports. See the drivers behind every number and the uncertainty range around it.
Good data, weak forecasts
Most mid-market planning teams still forecast in spreadsheets. Accuracy sits wherever it landed years ago, and nobody can say why a number is what it is. When the forecast misses, the cost shows up later as a stockout or a write-off, and by then it is too late to act.
The usual fixes do not fit. A full planning platform is a multi-quarter, multi-million-dollar project. A custom in-house model means hiring data scientists and maintaining it forever. Both are the wrong fit for a mid-sized operator that just needs better numbers.
The data is already there, in sales history, inventory reports, and the exports your planning team produces every week. The gap is turning it into forecasts you can trust and act on.
Forecasting built for planners, not black boxes
Ensemble per-SKU models
We run a set of forecasting models per SKU and select the best fit for each series, instead of forcing one model across a catalog where products do not all behave alike.
Explainable drivers
Every forecast comes with the seasonality, promotions, and external factors behind it, so your planners can sanity-check the logic instead of taking the number on faith.
Uncertainty ranges, not point guesses
Each forecast carries a confidence range your team can plan against, which is what actually drives good inventory decisions.
External signals built in
Tariffs, weather, and macro trends feed the forecast as inputs, so the numbers reflect the world your business operates in.
Runs on your existing data
We start from the spreadsheets and exports you already produce. No data warehouse project, no rip-and-replace.
What better forecasts are worth
Start free, expand when it pays off
Diagnostic
Free, 1-2 weeksWe quantify the working capital exposed to forecast error in your categories, on your data. No IT project, no procurement.
Pilot
Paid pilotProduction-grade forecasts on a focused subset of SKUs, with light integration, so you can measure the lift before committing.
Production
Scoped to your deploymentFull rollout across categories and locations, with continuous forecasting, exception alerts, and quarterly accuracy reviews.
Built for mid-market planning teams
AI demand forecasting fits mid-market manufacturers, distributors, and high-SKU retailers where forecast accuracy drives both service levels and working capital. If your team still plans in spreadsheets and needs forecasts it can trust and defend, this is built for you.
Questions planners ask
Do you replace our planning system?
No. We sit alongside whatever your team plans in today, whether that is SAP, Oracle, NetSuite, Kinaxis, Anaplan, RELEX, spreadsheets, or something else, and we use that output as an input. Most customers keep their current stack and add MetaLearner as the forecasting and decision layer.
How is this different from a custom in-house model?
You get the forecasting layer without the build, the hiring, or the maintenance backlog. For teams that already have data scientists, we handle model selection and upkeep so they can focus on higher-value work.
How long until we see a number?
The free diagnostic produces a defensible working-capital exposure figure by category in 1-2 weeks, using the data your team already exports.
What data do you need to start?
Sales history, inventory records, and whatever forecast files you keep today. Spreadsheets and exports are fine. There is no data warehouse requirement at the diagnostic stage.
How accurate is it?
Across deployments we see a 15-20% accuracy lift over spreadsheet and ERP baselines, which typically frees 10-25% of the working capital tied up in the SKUs we touch. Your results depend on your starting point, which the diagnostic measures first.
What does it cost?
The diagnostic is free. The pilot is a small, fixed-scope paid engagement, and production pricing is scoped to your deployment.
Go deeper on the method
See the number on your own data
Schedule the free Forecast-to-Inventory Diagnostic. In 1-2 weeks you get a defensible working-capital exposure figure by category, with no IT or procurement involved.
