Your market - and the AIs it increasingly trusts - judges your launch first. Test it on twins, verify with real humans, commit with evidence. Every outcome sharpens the next read.
Request early accessSix launch questions teams bring in week one. Each runs the loop - Twins, Humans, Evidence, Market - and ships as a workflow template you can stitch your own steps into.
"We have 12 hooks and budget for 3 - which deserve production?"
See how it runs ›"Does $39/mo with a 14-day trial beat $29/mo without?"
See how it runs ›"Clinical-grade, derm-approved, or family-safe - which wins premium buyers?"
See how it runs ›"Will the CFO kill this at the security review?"
See how it runs ›"Interview 30 churned customers by Friday."
See how it runs ›"Ask our Discord which of these three names actually lands."
See how it runs ›“We have 12 hooks and budget for 3 - which deserve production?”
Twins react to every hook on identical footing, segment by segment - not on averages that hide the differences.
“Does $39/mo with a 14-day trial beat $29/mo without?”
Price sensitivity is a segment property, not a market property. Watch anchoring, trial value, and switching costs move each cluster differently.
“Clinical-grade, derm-approved, or family-safe - which wins premium buyers?”
Every positioning route triggers a different objection. See which one each route trips - brand trust, feature confusion, weak differentiation - while changing course is still cheap.
“Will the CFO kill this at the security review?”
“Show me payback inside two quarters or this waits for next year's budget.”
“Fine on architecture - but SOC 2 needs to be on the first slide, not the appendix.”
“This kills three tools. I'll champion it if the CFO math holds.”
Deals die on the stakeholder you didn't rehearse. Build a committee panel from roles - or from real prospect data you've opted in - and pressure-test the pitch before it's live.
“Interview 30 churned customers by Friday.”
Send a link - your brand twin runs each interview in your voice, always disclosed as AI. Video, voice, text, or async form, with adaptive follow-ups that chase the objections the synthetic panel predicted.
“I didn't leave over price. I left because onboarding never showed me the one feature I bought it for.”
“The trial ended before I'd set anything up. Two more weeks and I'd probably have stayed.”
“Ask our Discord which of these three names actually lands.”
Your community is the cheapest honest signal you own. Brand twins post the question, moderate the replies, and roll them into a channel-by-channel read.
"Listing A or B for the family upgrader on Amazon?" Test retailer copy and claims against the segments that buy there.
Subject lines, hooks, and social posts - panel first, humans second, save the ones worth shipping.
"Haven't we tried 50% off before?" Logged outcomes are retrieved when a similar brief returns - a past loss overrides an optimistic call.
Every use case is a workflow: Test it on twins Hear it from humans Evaluate the evidence Measure it in market
A premium TV launch tested on a Gen Z + family panel: 12 synthetic consumers, 4 segments, 36 reactions - one clear call, ready to verify with real humans before the buy.
Mild positive across the panel - but watch the price-sensitive segment, which trends neutral with high spread.
Solid intent ceiling - needs a complementary "trade-up" hook to convert the status-driven cluster.
"$1,099 feels like an aspirational stretch" - surfaced in 3 of 4 clusters; consider a financing line or anchor product.
Confidence 0.58. Ship variant B and re-test variant A with the financing line for a follow-up read.
“$1,099 feels like an aspirational stretch - a financing line would change my math.”
Them AI helps teams choose better messages, pricing, and positioning by Asking Them before budgets are committed. Reactions are predictions, not certainties - so real humans verify the call, and your real results calibrate the panel. That's the proof a generic AI chat can't give you.
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