Case study · App tier

Strategy Scenario Engine
5,000 Monte Carlo runs in 200ms

A strategy stress-testing tool that runs genuine probability distributions client-side — cash runway, burn variance, growth assumptions, and survival probability with tabbed results and export flows.

TierApp — simulation engine
Simulations5,000 per run
StackVanilla JS · Web Workers
Live demoOpen tool →

The problem

Leadership teams plan with single-point forecasts that hide tail risk. Spreadsheet Monte Carlo is fragile and slow to share. The tool needed to run thousands of simulations instantly in-browser, surface survival probability and break points, and present results in an institutional tabbed UI — same rigor as enterprise RMF deployments, different domain.

What we built

  • Monte Carlo engine — 5,000 iteration runs with configurable cash, burn, growth, and variance inputs
  • Survival probability — percentile bands and horizon analysis showing where strategy breaks
  • Tabbed results UI — summary, distribution charts, sensitivity views, and narrative output
  • Sample data presets — one-click load for exploration without manual data entry
  • Optimized execution — ~200ms for full simulation batch on typical hardware
  • Export actions — copy and download flows for board prep and async sharing

Results

Demonstrates that App tier builds don't require React or a backend to handle serious computation — vanilla JS with careful algorithm design delivers sub-second Monte Carlo at scale. Prospects evaluating custom dashboards, forecasting tools, or risk calculators can run this demo and inspect source to verify engineering depth.

Similar build?

Need a simulation or forecasting tool?

Custom calculators, Monte Carlo engines, and analytics dashboards — scoped in a written SOW.