Synthetic User Research Lab
An AI-first lab that simulates responses, preferences, objections and psychological profiles to test campaigns, validate products and analyze messaging before investing. Includes a transmedia narrative line (cyberpunk manhua) and a psychological video game as intellectual property.
Synthetic User Research Lab
An AI-first lab that simulates responses, preferences, objections and psychological profiles to test campaigns, validate products and analyze messaging before investing. Includes a transmedia narrative line (cyberpunk manhua) and a psychological video game as intellectual property.
What needed to be solved
Validating a campaign, a price or a product with a traditional focus group takes weeks, is expensive, and carries the social-desirability bias of real participants.
How we tackled it
We built a simulation engine with synthetic agents that represent audience archetypes with real demographic data, able to react to stimuli (copy, pricing, designs) quickly and at a fraction of the cost of a traditional study.
System components
Panel of synthetic agents with demographic and psychological profiles
Simulated reaction to stimuli (copy, price, design)
Objection analysis and price sensitivity
Transmedia narrative line and psychological video game as the lab's intellectual property
Test it on a synthetic society before asking the real market.
Synthetic User is a new lab almost nobody knows: it is not a survey tool. It turns verified data, social signals and specialized AI agents into private synthetic studies to anticipate perceptions, objections, risks and opportunities before launching campaigns, products, messages, policies or commercial strategies. Synthetic users do not replace human research: they anticipate it, make it cheaper and focus it, always with a human in the loop. It is a line of jsadsAI | José Santamaría.
No closed public prices: each project is quoted by sector, scenarios and depth across three tiers (Signal, Simulation and Intelligence). The lab console runs on credits and the first quick study is free. The scale is jsadsAI's: a fraction of the time and cost of a traditional study (the site estimates up to 70 % less time, as an illustrative figure).
Visit Synthetic User Research Lab ↗A lab, not a survey tool
Synthetic users are AI-created profiles built from statistical, demographic, socioeconomic, cultural and behavioral data. Synthetic audiences are built from public data and need no personal data from the client; digital twins use authorized, anonymized and structured real data for higher fidelity to a specific population.
The flow has four auditable phases: defining the problem and population, designing the synthetic population, simulating scenarios and deciding with human validation. There are 20 sectors with their own methodology (business, government, health, politics, marketing, brands, media, education, finance, culture…) and 20 packaged commercial services, each in three tiers.
The online console runs statistically structured quota samples (age, socioeconomic level, region) for Colombia, Mexico, Panama, Costa Rica, Puerto Rico, the Dominican Republic and the US market; the AI Focus Group can run with real AI and the rest are illustrative simulations.
- Companies that want to validate products, pricing and journeys before investing.
- Marketing teams and brands that test campaigns, messages and reputation.
- Government and health teams exploring public perception and communication, with reinforced responsible use.
- Researchers who want to focus the human phase of a study.
Services and lab
As published on syntheticuser.jsadsai.com: 20 commercial services, 20 sectors and an online console.
Synthetic Audience Lab
Synthetic audiences by segment, built from statistical and public data.
See service ↗Digital Twin Research
Digital twins from your own authorized, anonymized and structured data.
See service ↗Synthetic Society Map
Animated map of synthetic agents: adoption, trust, risk and polarization per scenario.
See the demo ↗Lab console
Quota samples (quick 50 profiles, standard 385, high 1,067) on credits; the first quick one is free.
Open console ↗From the problem to the decision, in four phases
Definition
The problem, target population and assumptions to validate are scoped.
Synthetic population
Synthetic audiences or digital twins are designed and segmented.
Simulation
Scenarios run and perception, adoption and risk are observed.
Decision
Patterns, recommendations and an executive report with human validation.
Three levels of depth
As published on syntheticuser.jsadsai.com/planes: no closed public prices; each project is quoted by sector, scenarios and depth. The tiers apply to all 20 services and the quote tool recommends the level.
Signal · quick validation
Quoted
1 scenario, up to 3 synthetic segments, executive report, main objections, perception map and initial recommendations.
Quote Signal ↗Simulation · strategic decision
Quoted · popular
Up to 3 scenarios, 5 to 8 segments, comparison by audience, risk matrix, recommendations by channel and an executive session.
Quote Simulation ↗Intelligence · enterprises and government
Quoted
Full lab: multiple scenarios, recurring synthetic panel, dashboard, comparative models, narrative analysis and advanced documentation.
Quote Intelligence ↗The lab console runs on credits (quick study 1 credit, the first free; standard 5; high 12). Credit pricing is shown in the console.
Ethics and responsible use
- Probabilistic simulations, not absolute predictions. Reliability depends on the data, the calibration and the representativeness of the synthetic population.
- Every study includes human review. Human validation is part of the method, not an extra.
- No personal data without authorization. Synthetic audiences use public data; digital twins use authorized, anonymized data.
- No covert manipulation. No opaque propaganda or microtargeting; in politics, health and the public sector the results are exploratory instruments.
- It does not sell absolute prediction of the future or guarantee political, medical or social outcomes.
- It does not replace critical human validation.
- The demos (except the AI Focus Group) are illustrative simulations with preloaded data.
- A synthetic quota sample is not a survey: the margin of error measures the sampling, not the real world.
All of Synthetic User Research Lab, link by link
Every section lives on the project's official site. From here you go straight to it.
What people ask about Synthetic User Research Lab
Synthetic User is the predictive human research lab of jsadsAI | José Santamaría: with synthetic users, digital twins and AI agents it simulates how a market or a society would respond to a product, a campaign, a message or a policy before investing in the real decision, always with human validation. It is live at syntheticuser.jsadsai.com.
There are no closed public prices: each project is quoted by sector, scenarios and depth across three tiers (Signal, Simulation and Intelligence). The lab console runs on credits and the first quick study is free.
No. They anticipate and focus them. They cut cost and time in early phases, but human validation remains part of the method.
They are probabilistic simulations, not certainties. Reliability depends on data quality, model calibration and the representativeness of the synthetic population.
Yes. With authorized, anonymized and structured real data, higher-fidelity digital twins are built through Digital Twin Research.
Yes, with reinforced care and under responsible-use principles: in health and the public sector the results are exploratory decision-support instruments, not definitive policy guides.
Actively in development; the flagship project of jsadsAI's AI-powered market research lab.
Services this project demonstrates
These are not related topics: they are the systems actually built in this project, available as services.
Category: Behavioral Intelligence · synthetic users and AI focus groups. To learn the full scope and how to apply a similar approach to your business, write to us — no strings attached.
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