Forecast QA for In-House Growth Teams

An async decision-assurance service plus lightweight software for in-house growth and performance marketing teams that regularly propose channel forecasts, experiment bets, and budget-shift recommendations. Teams submit planned claims in structured form — for example, 'new creative theme will improve CTR 10-15% within 2 weeks' or 'landing-page simplification will reduce CAC this month' — and AE stress-tests them before budget is committed. The output is a decision memo, not a client narrative: which claims are grounded, which rely on hidden assumptions, which exhibit AE's six failure patterns, what evidence window is actually valid, and whether each claim should be promoted, demoted, or killed. Over time, AE grades forecast quality against real outcomes, building a reality-based record of which reasoning patterns and operators are trustworthy. The buyer is a VP Growth, Head of Performance, or marketing lead who needs fewer bad bets, cleaner postmortems, and a defensible planning process across paid media, creative, and landing-page experimentation.

AE has a credible wedge as the pre-commitment QA layer for growth forecasts: it improves the quality of decisions entering the plan, where existing AI forecasting tools largely do not operate.

Engine verdict: GATHER_MORE_SIGNAL (WORTH_SKIMMING). Real whitespace, but no proof yet that growth leaders will adopt and enforce a pre-spend QA ritual.