A Tech context Layer for qualitative research
Beyond Productivity
Most of the AI conversation in qual research is about productivity: transcribing, coding, and summarizing faster. At GHz, we asked a different question. Our work lives in the field, in people’s homes and neighborhoods. So what technology could make fieldwork deeper, letting us understand not only what a participant says, but the physical reality of the territory they say it from?
Qualitative research is great at capturing what people feel. But it has no native way to register what the environment around is physically doing: the heat, the water, the air quality, the slow pressures that shape behavior without anyone naming them. We call that missing context the Latent Layer.
Bridging the Gap
That gap led us to BRISE, a Brazilian environmental intelligence startup that operates microlocal sensor networks, integrates satellite imagery and public data, and turns it into continuous intelligence about a specific place. We saw a fit with our fieldwork and co-developed a model designed specifically for research: a way to overlay a territory’s environmental reality onto the studies we run, without changing anything for the participant.
Environmental Reality in Action
The Latent Layer is most useful where everyday behavior is directly sensitive to the environment: how people move, eat, go out, consume, and spend. Smoke or rain reshapes a commute. A flood turns a social platform into crisis infrastructure. A heat wave empties restaurant patios and fills delivery apps. The behavior we were already studying turns out to be partly shaped by conditions that were always present and still not measured.
Another valuable output is the friction between the layers: the moments where what a person reports and what their territory recorded pull in different directions. Those contradictions are not noise; they point to hypotheses worth testing.
Work with Us
This Latent Layer is now part of our core qualitative offering. We are partnering with teams facing complex, real-world challenges to explore how environmental context reshapes consumer behavior.
We have prepared a short case study showcasing applications across social media, streaming, mobility, financial services, pharma, and food. Reach out to request it.
