Four audiences. One rehearsal stage.
The same synthetic society, tuned to the way brands, campaigns, agencies and researchers actually work — and to the questions each one can't afford to get wrong.
Stop burning creative on focus groups.
Test every variant against a synthetic audience that mirrors your real one — in hours, not weeks. From a two-person team shipping on instinct to an enterprise brand with a launch-scale spend.
The pain today
- Creative review cycles take 4–8 weeks per asset; most variants never get tested at all
- Backlash risk is "felt", not measured
- Focus groups are 6–10 people in a room — a launch deserves more
- Insight platforms tell you what happened, not what will happen
- AI agents are starting to shop for your customers — and nobody knows how your site reads to a bot with a budget
15 workflows on every asset
Resonance, hook quality, backlash sensitivity, claim substantiation, CTA strength, brand-voice consistency and more — scored in minutes on text, image, video or a live page.
Bring your own scorecard
Ask the questions your brand team actually asks, get structured scored answers, and save the framework as a reusable template for the whole team.
Synthetic audience to your spec
Upload your census workbook or first-party panel summary; get a stratified population with price sensitivity, brand loyalty and media diet layered on.
Surveys in hours, not a month
Purchase-intent polls with cross-tabs, significance testing, notable-segment detection and per-respondent reasoning — grounded in the campaign if you want.
Watch a persona use the store
Budget-conscious, brand-loyal or impatient personas shop your live site; every click gets a technical and a psychological explanation. Usability testing without recruiting.
Daily model reputation monitors
"Is [brand] good to buy from?" asked to GPT, Gemini, Grok and DeepSeek every morning — with an alert the day an answer changes.
War-game your message against a state-shaped electorate.
Before the press release goes out, before the town hall, before the donor email — see how the actual electorate would react, county by county, with the reasoning behind every response.
The pain today
- Polling is slow and gives you a number, not a model of why
- A bad tweet becomes a 72-hour news cycle — there's no rehearsal stage
- Contrast lines are written on instinct; backlash gets found out the hard way
- Donor appeals are A/B-tested live on actual donors
- Debate prep happens against staffers, not the opposing worldview
Constituency-shaped audiences
Upload a county-level workbook; get a synthetic electorate stratified by race, age, urbanicity, education, religion and political affiliation. Save it as "the MI-08 audience" and reuse it forever.
Message rehearsal
Any statement, ad or stump line scored on resonance, backlash, objections, claim substantiation, contrast effectiveness, fundraising appeal and issue salience.
Debate prep with a judge
Seat a rural undecided, a base voter and a hostile partisan against your position — sourced from the opponent's latest ad or today's breaking news. The AI judge extracts the lessons for countering the winning narrative.
Synthetic polling with real analysis
Head-to-head questions with per-persona reasoning, wave comparison, and significance-tested cross-tabs by any demographic.
County-by-county score maps
Queue an assessment per battleground county overnight; wake up to the swing-county picture plotted red-to-green on a map.
Watch how the models describe the race
Voters ask ChatGPT who to vote for. Daily monitors chart what every frontier model says about the candidate — and flag the silent model update that recasts the race before the press finds it.
Stress-test public communications across the whole population.
Including the cohorts who tune you out. Public-health bulletins, safety advisories, crisis communications and service portals — rehearsed against a synthetic population matched to your real one, on approved model providers only.
The pain today
- PSAs are drafted by committee and tested with one focus group, if any
- A message that lands with cohort A triggers distrust in cohort B — found out too late
- Crisis communications have no rehearsal stage
- Misinformation moves faster than the approval chain
Population-accurate cohorts
Census or departmental profiles become synthetic populations matched on urbanicity, education, religion, age, occupation, household composition and disability status.
Pre-publication triage
Claim substantiation, polarisation forecasts, backlash-sensitive phrasing, and forecasted replies — on every draft before it ships.
Codify your comms doctrine
Plain-language compliance, accessibility of the call to action, trust-cohort sensitivity — saved as a template and applied consistently across every team and campaign.
Crisis-arc simulation
Model a 72-hour arc — advisory → confusion → counter-narrative → reassurance — with environment shocks at controlled magnitude.
Citizen & AI-assistant journeys
Point the UX Simulator at a service portal with a task like "find out if you qualify and start the application" — every abandonment annotated with the human reason.
Sovereignty & audit built in
Restrict workloads to approved model regions. Row-level-secured tenant isolation, verified on every schema change. Every governance action audit-logged.
A controllable, replicable lab for synthetic societies.
Sentiment contagion, network dynamics, multi-agent deliberation, human–computer interaction — studied on populations you can seed, fork, replay and export, with the instrumentation most social-network research needs and rarely has.
The pain today
- Running contagion experiments on real platforms is no longer ethical, legal or clean
- Agent-based modelling tools produce edges and counters, not realistic content
- Most "AI behaviour" papers can't be re-run — models, prompts and populations are moving targets
- IRBs and funders want timestamped, auditable, replicable interventions
Statistically-grounded populations
21 structured facets via documented largest-remainder stratification, plus ~70 catalogued dimensions assigned by a deterministic seeded sampler.
Big Five with layered interventions
Persona → country → cluster → global modifier hierarchy, all timestamped and stored, so an experiment replays exactly.
Decision traces on everything
Every post, comment, swipe, vote and survey response records the model's reasoning. The dataset contains the why, not just the what.
Statistics built in
Two-proportion z-tests on cross-tabs, notable-segment scanning, Pearson correlation of personality dials vs sentiment, network density and cluster detection.
Fork-and-compare lineage
Clone a scenario, change one parameter, and produce a clean comparison run — with crashed runs visible, never silently "completed".
Raw export for the replication package
Posts and personas stream out as RFC 4180 CSV — sentiment, tones, demographics, Big Five columns — straight into R, pandas or Stata.
Tell us who you need to reach.
We'll build them.
Bring a real message and a real audience profile to the demo — we'll run it live.
Book a demo