Test before you invest.
Run the decision as a simulation. Then spend the money on the version that won.
Raise prices. Open the second location. Move the budget from Meta to Google. Run it against a model of your customers and see the outcome before you commit the money.
We're building this now. Tell us the decision you're weighing and we'll run it as one of the first simulations.
Hypothesis
500 runs · done“What happens to revenue if we raise the price 40% and add onboarding?”
8,400 simulated customers · 12 weeks · 500 runs. Churn rises 6% at $69, and the onboarding offer more than covers it. Illustrative: your model runs on your numbers.
The only way to know is to spend the money first
Big companies de-risk these decisions with modeling teams. Everyone else runs the experiment live, with the real budget and real customers, then calls the result experience.
You pay to learn
A price change, a new offer, a new channel. You find out whether it worked after the money is gone.
One test at a time
One live test per quarter. Four answers a year, while the market moves every week.
Customers see the misses
Losing tests run on real customers, and they remember the bad version longer than you do.
Where a spreadsheet stops
A spreadsheet does the arithmetic you already assumed. A simulation gives you customers who decide for themselves, each with a budget, a habit, and a limit to what they'll pay. Thousands of those decisions add up into an outcome nobody hand-wrote. What comes back is a range with odds on it, plus the reason the winner won.
From question to answer in an afternoon
- 1
Describe the business
Your product, prices, margins, customers, and channels. Connect a sales export, an ad account, a spreadsheet, or just write it out.
- 2
Write the hypothesis
State it in plain language: “What happens to revenue if we raise the price 40% and add onboarding?” No model to build, no formulas to wire.
- 3
Let the population react
A population of simulated customers, matched to yours in behavior, budget, and taste, meets the change and reacts. Every variant, thousands of runs each.
- 4
Get a decision you can defend
Ranked outcomes with the reasoning attached: what wins, by how much, how confident the answer is, and what would have to be true for it to be wrong.
Every call you've been making on instinct
If being wrong costs money, simulate it first.
Pricing & packaging
Raise the price, add a tier, bundle the add-on. See what each does to revenue, churn, and the mix of who buys.
A new product or offer
Before you build it or stock it: who buys it, what it cannibalizes, and what it actually adds to the top line.
Where the ad budget goes
Split the same budget across channels a hundred ways before you commit it to one of them.
A new market or location
A second location, a new city, a new segment. Model the demand before you sign the lease.
Discounts & promotions
Find out how much volume the discount buys and how much margin it burns, before it goes live.
Where the next hire goes
Two more salespeople, or the same money into ads? Simulate both and compare the payback.
Three ways to learn the same thing
Only one of them lets you be wrong for free.
| Approach | What it costs | How long | How many hypotheses | What's at risk |
|---|---|---|---|---|
| Test it live | Your real budget | 4–12 weeks | One hypothesis | Real customers see the losing version |
| Hire a consultant | $15k–$100k | 3–8 weeks | A handful, by hand | A deck you still have to act on |
| Simulate it first | Less than one failed campaign | The same afternoon | Every variant you can think of | Nothing but the time to read it |
The Fortune 500 has had this for years
Market simulation isn't new. It has been sold as a six-figure engagement with a consulting team attached, which left the businesses that could least afford a bad decision making them blind. We're building the same capability for the operator who signs the checks personally: self-serve, same-day, priced like software.
Questions & Answers
What you're probably wondering
Something we didn't answer? Join the waitlist and tell us what you'd want to simulate first.
Security & governance
Bank-grade security for non-public data
SOC 2 Type I & II
Independently audited for continuous security, system availability, and confidentiality. Full audit reports available upon request under NDA.
Zero Model Training & Compliance
Your financial data is strictly isolated and never used to train public AI models. Fully compliant with GDPR and CCPA, with standard DPAs available.
Encryption & Access Control
AES-256 encryption at rest and TLS 1.3 in transit. Enterprise access is governed via SAML SSO, MFA, and strict Role-Based Access Control (RBAC).
Stop paying to find out.
We're building Simulations with a first group of small and mid-sized businesses. Bring the decision you're weighing. We'll run it and show you what came back.