Decision simulation · demonstration project · live model output · ← back to simplicate.ai
Test your next business move before you make it.
What happens if you raise prices, cut a shift, or switch suppliers? A business is a connected system: cut staff and costs drop, but service pressure rises and this month's walk-aways become next month's missing regulars. Vector is a Simplicate-built demonstration, a fictional restaurant in a competitive market. It shows what a decision model does, not what your business will do. Pick a move and read what happened and why.
Raise every menu price 5%
How the simulation works
The chart compares the scenario's profit month by month against the baseline's average month, drawn flat. Same inputs, same results, every time: the engine is deterministic and replays byte-for-byte. Figures are twelve-month season means over 8 random seeds from the calibration pack, config . The engine writes a causal breakdown for every metric, every month; the explanation above is the plain-English version. Decision simulation is a complementary capability to the automation work, not a substitute for it.
Where this fits
A complementary capability, not the core offer.
Simplicate's work is automation architecture: audit, build, prove, deploy. Decision simulation uses the same modeling discipline to answer a different question.
Is a digital twin the same as a business simulator?
Same discipline, two time horizons. The twin asks whether an automation behaves correctly before it goes live. A decision simulator asks whether a pricing, staffing, or supplier change pays off before you commit. Both model your business as a connected system and run it against scenarios first.
Is Vector a model of my business?
No. Vector is a fictional restaurant in a competitive market, calibrated to plausible figures so the mechanics are visible. A model for your business would be scoped to the decisions you face, calibrated to the data you have, and delivered with its assumptions written down. If the data to calibrate it does not exist, that is the first finding, not a reason to guess.
What decisions is this good for?
Ones where a change in one part of the operation moves another: pricing against volume and retention, staffing against service pressure, a supplier switch against quality and margin, a second location against the first. It is not for forecasting a single number; it is for seeing the ripple before you commit.