Wahllabor.ai
Chat interface for talking to 12 synthetic voter personas — one-on-one interviews and multi-agent focus groups. Winner of the BVM Innovation Prize 2025.
The Problem
Political researchers need to understand how different voter segments think and react. Traditional polling is slow and expensive. Focus groups are hard to organize and biased by group dynamics. There's no quick way to pressure-test campaign messaging against realistic voter archetypes.
The Approach
The client had the AI backend — 12 functionally representative synthetic voter personas. My job: two interaction modes. First, one-on-one chats where a researcher talks directly to a single persona. Second, multi-persona focus groups where several synthetic voters discuss a topic together — showing group dynamics that make focus groups valuable in the first place.
Personas react to each other's arguments, agree, disagree, shift positions. The researcher can observe, interject, redirect the discussion, or let it run.
The Result
Shipped and used during the German federal election cycle. Live at wahllabor.ai with paying users. Won the BVM Innovation Prize 2025 — recognized for combining AI with qualitative research traditions. Up to 100 synthetic in-depth interviews per hour.
My Role
Frontend and chat interface — both the 1-on-1 conversation mode and the multi-persona focus group experience. The client owned the AI/persona backend — I owned the user-facing experience.