About Carlo
A visual Monte Carlo simulation builder for modeling uncertainty and making better decisions under risk.
What is Carlo?
Carlo is a visual tool for building Monte Carlo simulations without writing code. Connect blocks on a canvas, define probability distributions, and run thousands of scenarios to understand how uncertainty affects your outcomes.
Monte Carlo simulation is a computational technique that uses random sampling to model the probability of different outcomes. Instead of a single estimate, you get a distribution of possible results with associated probabilities.
In Carlo, you build models by connecting blocks that represent variables, calculations, and outputs. Each variable can have its own probability distribution, and the simulation runs thousands of iterations to reveal the range of possible outcomes.
Use Cases
Carlo is designed for anyone who needs to make decisions under uncertainty:
Financial Planning
Model retirement savings, investment portfolios, and FIRE (Financial Independence, Retire Early) timelines with uncertain returns, inflation, and spending.Try FIRE Calculator →
Project Risk Assessment
Estimate project timelines and budgets when task durations and costs are uncertain. Quantify the probability of meeting deadlines or staying within budget.Try Project Risk →
Business Decisions
Evaluate new product launches, pricing strategies, or capacity planning when market conditions, demand, and costs are uncertain. Model correlated factors like weather and sales.Try Weather-Sales →
Education & Research
Teach probability concepts, explore statistical distributions, and prototype models for academic research. Share simulations with students or collaborators.
Who It's For
Analysts & Planners
Financial analysts, project managers, and strategists who need to quantify risk and communicate uncertainty to stakeholders with data-driven confidence intervals.
Students & Educators
Learn and teach probability, statistics, and risk analysis with an intuitive visual interface that makes abstract concepts tangible.
Entrepreneurs
Validate business models, forecast revenue scenarios, and stress-test assumptions before committing resources to new ventures.
Personal Finance
Model retirement timelines, savings goals, and investment strategies with realistic uncertainty instead of oversimplified single-point projections.
Why Monte Carlo?
Traditional forecasting gives you a single number—a point estimate. But real-world outcomes are uncertain. Monte Carlo simulation reveals the full range of possibilities.
Traditional Approach
"The project will cost $100,000."
Monte Carlo Approach
"There's a 90% probability the project costs between $85,000 and $125,000, with a median of $102,000."
Key Benefits
Quantify confidence intervals, identify risk factors with sensitivity analysis, make decisions based on probabilities rather than guesses, and communicate uncertainty clearly to stakeholders.