Vantage

Foresight · Precision · Insight

A multi-industry forecasting sandbox that demonstrates how a single prediction engine adapts to five different commercial use cases — with real models, honest data labelling, and plain-English explanations.

How the Engine Works

Model Selection

Runs Holt-Winters, exponential smoothing, regression, Croston (intermittent demand), seasonal-naive and moving-average baselines. The champion is the model with the lowest back-tested error — not the fanciest name.

Rolling-Origin Backtesting

Every model is tested by hiding real history and forecasting forward, repeatedly. Performance is measured with MAE, RMSE, MAPE, sMAPE, WAPE and bias — not on training data, on held-out actuals.

Live Recalibration

Enter a new actual and the forecast updates immediately. The engine classifies the reading (normal / anomalous / structural), re-estimates the level, and explains in plain English what changed and why.

Scenario Comparison

Base, optimistic and conservative cases compared side by side — with stockout risk, revenue and margin computed per scenario. Custom scenarios for contracts, campaigns and constraints.

Data Confidence

Every data source is labelled: real historical, simulated, user-entered, contracted, pipeline or public. The system never silently mixes real and synthetic data and always tells you what would improve the forecast.

Industry-Aware

Each industry gets its own metrics, assumptions, language, constraints and model families. The maths is the product — the skin flexes to match the client. A brewery is not a SaaS startup with hops.

Choose Your Industry

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Brewery

Demand, stock, production, delivery. Seasonal forecasting with weather and event drivers.

Live demo →

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DTC Retail

SKU demand, campaigns, inventory, fulfilment. Marketing-driven with return-rate modelling.

Live demo →

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SaaS Startup

MRR, churn, expansion, pipeline. Cohort-based with cash runway and capacity planning.