01Start from your research
Segmentations, usage and attitude studies, trackers and interviews. Each row is a real respondent.

The AI Consumer OS
Fairgen connects your research, customer data and market intelligence, then tests what comes next with audiences modeled on your real consumers.
Built on work with consumer leaders
The workspace
Fairgen reads every study, tracker and customer record you connect. It answers in seconds and opens the source behind each claim.
Connected knowledge




Your audiences stay yours and ready to answer, so every message, product and price is tested before you commit.
Segmentations, usage and attitude studies, trackers and interviews. Each row is a real respondent.

34 · Mexico City
Selective splurgers
27-year-old student in Guadalajara. Buys drugstore makeup, follows video tutorials.
One twin per respondent, with their full profile. Together they form your audience: 1,200 beauty buyers.
Ad, concept, price and claims tests, built by you or the assistant.
Film A leads on intent with 25–34s. Film B wins with sensitive skin.
“It works in a week, and they show real skin.”
“Light texture, sinks in, not greasy.”
“It’s for skin like mine, oily in the T-zone.”Quantitative and open answers, side by side.
Consumer brands and research partners that work with Fairgen


The decision brief
The preferred direction, why it matters and what to test next, with every source and audience response one click away.
Built every Monday from your research and your twins
Reviewed by your team before it is shared
Delivered as PowerPoint, Excel or a Teams message
Recommendation
Lead with convenience for home blenders. Open with a trial price for occasional buyers.
Why this direction
Home blenders chose convenience 64 to 36; occasional buyers leaned to price 58 to 42.
What to test next
Test two trial price points with occasional buyers, then the winning pair in market.
Smoothies · 3 sources · 1,200 digital twins
Here is your requested deck. I customized your template and included the backup data.
Exports (2)

Smoothie_Brief.pptx

Twins_by_Segment.xlsx
Customer stories
Nadia ObukhovaGlobal Consumer Insights Manager, L’Oréal
Antoinette SandySenior Data Scientist, T-Mobile
Katrin De GrenierDirector Global Customer and Market Insights, Accor

Frank Brezout
Global CMI Director, L’Oréal

Andy Davidson
Chief Data Officer, Big Village

Christophe Jourdain
General Manager, Ifop

Joel Anderson
EVP, Advanced Analytics, Dig Insights

Emilie Boutes
Chief Innovation Officer, The BVA Family
Built by


Founder and CEO
PhD in generative AI (Oxford, UCL, Imperial). Trained foundation models at Meta AI.
Enterprise-grade
Your research and customer data stay in your own instance and never train anyone else’s models.
SOC 2 Type II
Close
Audited, not asserted. Controls are verified over time, not at a single point. The report is available under NDA.
Your own instance
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US and EU hosting
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GDPR, CCPA and DPA
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ESOMAR corporate member
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Every answer keeps its sources
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Questions
What is the AI Consumer OS?
One system that connects your consumer knowledge, models your audiences and runs the recurring work around both. Retrieval gives cited answers from your research. Simulation tests decisions with digital twins grounded in real consumer data. Workflows combine the two and deliver the output to your team.
What research can we use to build digital twins?
How is a modeled audience different from asking a chatbot?
Does it replace field research?
Which sources can we connect?
Who owns our data?
How do we start?

Bring one category and one decision. Orchestrate your knowledge. Build your twin audiences. Get insights instantly.
Enterprise deployments · SOC 2 Type II