Most product failures aren't engineering failures. The thing usually works exactly as designed — it just turns out nobody wanted it enough to pay for it, and that discovery arrives six months and a real budget too late to be cheap.

The standard fixes don't actually fix this. "Talk to customers" produces generous conversation and unreliable signal — people are polite in interviews and honest with their wallets. "Build an MVP and see" still requires building something first, which is the exact expense you were trying to avoid finding out about. And the recent wave of AI "validation" tools mostly generate plausible-sounding opinions from a prompt, dressed up as market research.

We built KPIndicator to run the test that actually answers the question: put a specific offer in front of real people, spend real budget getting it seen, and measure what they actually do. Not what they say they'd do. Not what a model predicts they'd do. What they click, sign up for, and pay a deposit toward.

We work like an in-house growth team you can rent for three weeks instead of an agency selling you a retainer — because that's the model that gets you a straight answer fastest, and then gets out of the way once you have it.