AI in the service of depth
Tools in the service of depth.
We hold on to both sides: synthetic “respondents” replace no conversation here — and everywhere else, AI has long been working for depth, in production, on our own infrastructure. That is not a compromise but a division of labour: machines transcribe. People answer.
Question the study
A study does not have to remain a PDF. On request you receive your results as an agent that stands exclusively on the transcripts of your study — every answer backed by the verbatim quote. A report becomes a place where you can keep asking. Even months later.
In use
What is already working here today
- Co-creation with image models
- In the middle of the conversation, respondents make visible the inner images they lack the words for — together with generative models. The image becomes part of the research encounter, not its replacement.
- Transcription in many languages
- Every conversation becomes searchable text, in dozens of languages — on our own servers. No interview leaves our infrastructure for it.
- Agent-assisted analysis
- Agents work in the loop over the study material — for our researchers and, on request, directly for our clients. Every statement stays tied to the original quote: verifiable down to the word.
All self-hosted. Interviews, transcripts and analyses never leave our servers.
The line
Why the machine never sits on the couch
Models are static. People aren't.
A language model is a photograph of yesterday's internet. People experience new things, change their minds, contradict themselves — precisely this movement is the market signal. A synthetic “respondent” can only reshuffle what has already been said in public. The depth interview looks for what has not been said yet.
Big Tech proves it itself.
The big AI labs go to great lengths to filter machine-generated text out of their training data and invest in watermarking to keep it out. If model output could replace human output, nobody would pay to exclude it. They treat human data as what it is: irreplaceable.
The Turing fallacy.
Studies claiming that language models pass the “Turing test of market research” prove indistinguishability in conversation — nothing more. That a simulation convinces says nothing about whether it reflects real market trends. A perfect actor is not a witness.