Making every perspective count.

Technological progress is changing not only how research is conducted, but also which questions can be studied in the first place. In mathematics and the natural sciences, researchers can now analyse vast amounts of data, develop models and conduct experiments that would have been almost unimaginable only a few years ago. In applied social and health research, this transformation is only just beginning.

Zeitgeist Labs was founded to lead this transformation.

We develop scientific methods and technologies that allow us to study people, their behaviour and social dynamics at greater depth and scale. We create new approaches to data collection and analysis, include far more people in research, and combine qualitative interviews with survey, behavioural, contextual and case-specific data.

This lets us take on research questions that used to be out of reach. Talking to hundreds or thousands of people in person was rarely feasible. Different types of data were hard to bring together. And analysis often took so long that the findings arrived too late to be of use.

We want to push the boundaries of what we can understand about people, their behaviour and our society.

New methods change more than what research can do. They change whose experiences and knowledge become visible.

Understanding society means taking everyone’s lived experiences seriously. We are interested in different experiences, beliefs and perspectives, even when they contradict one another or challenge existing assumptions. Our aim is to study this diversity with an open mind and scientific rigour.

The work of the organisations we partner with affects hundreds, thousands and sometimes millions of people. Yet research and decision-making often reflect the perspectives of only a small fraction of those affected. Not because other perspectives matter less, but because including them has traditionally been too costly, time-consuming or difficult.

We want to change that. Our technologies make it possible to have open conversations with far more people, across languages, with fewer barriers to participation, and at any time. Conventional research easily misses people who are hard to reach, who speak other languages, or whose views do not fit a fixed set of answers. Open conversations bring their experiences, needs and knowledge into view.

Our goal is not to collect as much data as possible. We want to understand the patterns that emerge across individual experiences and what they mean for decisions. What matters is that we put these new possibilities to sound scientific use.

When a decision affects thousands of people, why shouldn’t all of them be heard?

1. AI expands what researchers can do. It does not replace them.

Research questions, study design, methodological decisions and interpretation remain in the hands of our researchers.

We use AI where it can meaningfully extend the possibilities of research: to conduct large numbers of open-ended conversations, analyse substantial volumes of qualitative data and bring different types of data together. It allows us to work at a scale that would be difficult to achieve with conventional approaches alone.

Responsibility for the science stays with our researchers. For us, progress does not mean removing researchers from the process. It means expanding what they are able to think through, analyse and investigate.

2. Depth and breadth belong together.

Qualitative research can reveal how people experience their world, what matters to them and why they act the way they do. Traditionally, this depth has been limited to small samples. Standardised surveys can reach far more people, but they are less able to capture individual experiences and the insights that emerge through open conversation.

New technologies are changing that trade-off.

We can hold open, adaptive conversations with many people and analyse far more qualitative data than was practical before. When the research question requires it, we combine these conversations with standardised surveys and behavioural, network or contextual data. Breadth no longer has to come at the expense of depth.

3. We remain researchers ourselves.

Zeitgeist Labs does not develop research technology from the sidelines. We use our methods ourselves, test them in our own research projects, and develop them further together with universities and research institutes.

This grounding in research shapes both our technology and our work with clients. For us, it is not enough that a method works. We want to understand what it measures, where its limits lie and under what conditions its results can be trusted.

We want Zeitgeist Labs itself to be an institute where technological development and rigorous research go hand in hand.

Mahdi and Edgar met many years ago at a research academy of the German Academic Scholarship Foundation. Conversations about society, the natural sciences and the future of research led to a question that has stayed with them ever since:

What if social and health research saw the same technological innovation as the natural sciences?

They initially approached this question from different disciplines. Today, Mahdi is a computational social scientist at the Max Planck Institute of Geoanthropology, where he studies how social dynamics across individuals, groups and institutions can be observed and modelled. Edgar is a researcher at Charité; his work combines medicine, AI, computer science and global health.

Zeitgeist Labs brings these perspectives together.

We do not want to simply digitise existing research or use AI to speed up individual steps. We want research to be able to do more: to address more questions, include more people and reveal connections it could not see before.

And we want to help bring this knowledge to the people whose decisions shape many lives.