Pre-spend triage
Built to answer before the auction, not to autopsy after it. Minutes, not weeks.
Creating stopped being
the hard part.
GenAI made creative infinite - infinite ads, infinite copy, infinite variants, conjured in seconds. But attention, budget, and judgment stayed exactly as scarce as before.
So teams ship more than ever, and still learn what the market thinks only after the money's gone. We kept watching brilliant people place million-dollar bets on a gut feeling - and find out they were wrong from the spend report.
It didn't have to be that way.
Every launch is really one question: how will people react? And for the first time, you can ask them - before you spend a dollar.
That's why we built Them AI.
A panel of twins, built from your own market, reads your launch in about a minute. When the call matters, your brand twins carry it to real people - always disclosed as AI. The two reconcile into one honest piece of evidence: ship, iterate, or hold.
Then it does the thing research never could. It remembers. You log what actually happened in market, and the panel grades itself - getting sharper for your brand with every launch. The longer you use it, the less you guess.
And the timing isn't an accident. Soon the people you sell to will send their own AI agents to research, compare, and decide. The muscle you build today to rehearse humans is the one you'll use to rehearse their agents tomorrow.
Them is the people you're selling to.
Consult Them before you spend.
Them is the people you're selling to - and the four layers that put them in the room before you decide. First as twins, then as humans, finally as the market itself.
Two twins: consumer twins grounded in your market signals, and brand twins that ask in your voice. The fast gear: a read in minutes.
Your community, Reddit, interviews of any kind - run by your brand twins, always disclosed as AI. The honest gear: verification in hours.
The reconciled decision - twins and humans agreeing or disagreeing, resolved into ship / iterate / hold with confidence intervals. Not opinions, evidence.
Launch outcomes and external metrics - ad performance, sales, CRM. The final judge, feeding calibration so every future read is sharper.
Them AI is not a survey tool with AI bolted on. Your panel is made of autonomous consumer agents that react the way your market would - and your brand gets twins too: agents that ask in your voice, run the polls, threads, and interviews, and are always disclosed as AI. A reasoning layer runs the judgment on top.
Each persona is an agent that reasons in character: immediate gut reaction, considered evaluation, and social response, not a templated score.
Agents that speak in your voice: they fan questions to your community, moderate the threads, conduct the interviews, and report back - always disclosed as AI.
An orchestrating layer turns thousands of agent and human reactions into structure: what buyers believe, what they resist, and a decision with confidence intervals.
Buyers are starting to let AI assistants research, compare, and decide for them. The twins you build to rehearse humans today are the same muscle you will use to rehearse their agents tomorrow.
Anyone can prompt a model for opinions. Our edge is the calibration loop: outcomes and external metrics - ads, sales, CRM - grade every prediction, and the panel gets demonstrably sharper for your brand with every launch. That history cannot be copied.
Built to answer before the auction, not to autopsy after it. Minutes, not weeks.
A ship, iterate, or hold call with confidence intervals, not a wall of raw reactions.
Every logged outcome tunes the panel to your brand and category, so trust is earned, not claimed.
Accuracy improves with each launch. The longer you use it, the harder it is for anyone to match.
Four steps, composable into workflows: start from a template like ad pre-flight or pricing test, or stitch your own.
Generate a panel grounded in your market signals and get a first read: sentiment, intent, objections, and a ship / iterate / hold call.
Your brand twins fan the same question to your community, Reddit, and interviews of any kind - in your voice, always disclosed as AI. Real reactions in hours, scored against what the consumer twins predicted.
Twins and humans resolve into one reconciled call with confidence intervals - evidence your team can inspect and defend.
Launch, then let outcomes and external metrics - ads, sales, CRM - grade the prediction. Calibration compounds; every future read gets sharper.
The more people and markets that run through one workspace, the more valuable it gets. Copy, panels, and decisions become shared institutional memory instead of knowledge stuck in one person's head.
The whole team tests the same copy, ads, and panels against the same audience and the same standards, so reads stay consistent across people and campaigns.
What worked for one region, segment, or location becomes the starting point for the next, so a winning angle in one market inspires the next instead of starting from a blank page.
The decision log is reusable. Revisit a past call, see what the panel got right against real outcomes, and test the next variant against what the team already learned.
Co-founder
Builder and former CTO with experience across commerce, AI, CDP consulting, and omnichannel marketing systems. He has helped startups and growth teams turn complex data and product ideas into practical software.
Co-founder
Brings experience from Meta and Adobe, with focus areas across AI evaluation, monetization, commerce systems, attribution, compliant messaging, and conversion strategy.
Read answers about synthetic consumer panels, launch simulations, calibration, and how teams use Them AI before spending on media or production.
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