Use case
A research lead at a brand or consultancy who must quickly test pricing, concepts or user feedback hands interview guides and target groups to the platform; AI runs hundreds of consumer and expert interviews in parallel with preliminary analysis, and human researchers interpret the meaning and context to deliver decision-ready findings.
Outsourcing surveys and focus groups to traditional research firms, or running in-house survey tools plus manual phone interviews; long cycles and high per-study cost keep research frequency low, with many decisions made on experience or scattered feedback.
Per the founder's public statement, a single traditional study costs around €100,000 and takes three months, so companies cannot run one every time they need an answer; by the time findings arrive the market has moved, and the real cost is making important decisions without hearing from customers.
xOcto's call
Demand is evidenced
Trend: high-labour, project-priced market research is splitting into AI-run interviews plus human interpretation, compressing delivery from quarters to days. Entry: start with the small-sample validation work that brands and consultancies cut first, charging per study or per interview rather than per seat; the moat is the respondent panel and interpretation quality, not the model.
Reason to use it
Why users would choose it
Compared with outsourced studies that wait for scheduling and run interviews one by one before manual coding, it lets AI run hundreds of interviews at once and aggregate immediately, removing the wait-for-scheduling, wait-for-interviews and wait-for-coding steps so a research lead can get answers inside the decision window; keeping human interpretation eases doubt about reliability. This is inference from product capability and the old workflow, not yet supported by customer
Where the easy answer breaks down
The tension worth following
An English validation note will follow from the public evidence.
If this is your job
Worth trying. Compared with outsourced studies that wait for scheduling and run interviews one by one before manual coding, it lets AI run hundreds of interviews at once and aggregate immediately, removing the wait-for-scheduling, wait-for-interviews and wait-for-coding steps so a research lead can get answers inside the decision window; keeping human interpretation eases doubt about reliability. This is inference from product capability and the old workflow, not yet supported by customer
Entry and what to borrow
Trend: high-labour, project-priced market research is splitting into AI-run interviews plus human interpretation, compressing delivery from quarters to days. Entry: start with the small-sample validation work that brands and consultancies cut first, charging per study or per interview rather than per seat; the moat is the respondent panel and interpretation quality, not the model.