Asking Smarter Questions

There are no stupid questions. But there are smart questions.

Question Mark

Many important questions can be answered by just asking someone. But the biggest questions often require asking many people. Sometimes multiple times over a period of time. And asking good questions can be hard.

We have all seen surveys which were too long, or too confusing, or too repetitive, or where we couldn’t quite give the answer we wanted to. Or we have struggled to create questionnaires ourselves and in the end we still wished we had asked a specific question we left out.

We want to make asking good questions easier.

Asking good questions would be easier if the questions themselves could help.

If they could be smart.

If they could only show up when they are needed. If they could change and rearrange themselves based on the situation. If they could remember your previous responses and ask you follow-up questions which make sense. Months later, if necessary. If, while creating a survey, they could recommend themselves to you based on your intent and point out or even correct mistakes.

We are in unique position to accomplish this goal.

Our roots are in AI research, so we are used to asking questions and dealing with data. We also have the expertise to infuse intelligence into the questions themselves. And for years, we have worked closely together with partners who have been asking some of the biggest questions for decades.

We have built the foundation.

The foundation for truly smart questions, surveys, and studies must be a flexible digital model which serves as the core of a powerful survey engine where every aspect can be dynamically updated, where complex logical relationships can be defined, and where every imaginable possibility can be created.

This is what we have already built. Coneno’s AI Survey Engine (CASE) serves as the basis upon which we will build the systems which will enable the truly smart questions of the future. But even on its own, it is already powering some of the most important questions which can be asked today.

CASE has been expanded into an open and flexible platform which includes a configurable web-client with a component-based UI layout and a server-backend which protects participants’ privacy while keeping their data secure. This platform is today powering the next generation of instances.

Live Platforms

Infectieradar (NL)

The National Institute for Public Health and the Environment (RIVM) in the Netherlands uses CASE to monitor symptoms of infectious influenza-like illnesses, including coronavirus infections. Data from works as an addition to the figures from test streets, hospital admissions and other RIVM studies.


Some people suffer long-term health issues after being sick with COVID-19. To understand these effects, the National Institute for Public Health and the Environment (RIVM) in the Netherlands conducts studies with their LongCOVID platform based on CASE.

Infectieradar (BEL) is a Citizen Science Platform for Infectious Disease Surveillance operated by the University of Hasselt and University of Antwerpen that aims to collect valuable information on the circulation of infectious diseases in Belgium.

And more to come.

We are currently working together with partners in multiple countries to deploy additional platforms.

Asking the questions of the future.

We are continuing to work on bringing CASE to more questions, while increasingly focusing on further research to make questions smarter in even more ways which were never possible before.

This work is not only driven by the belief in the power of surveys when it comes to answering questions, be they related to the largest topics such as the COVID crisis, or to smaller topics such as understanding the needs of customers. But we also firmly believe that the world will be a better place if more people are empowered to ask good questions. Because asking good questions and receiving good answers enables all of us to make more informed decisions and to benefit from better decisions made by others.

Press Releases

Live-Experiment mit App zur Kanzler-Debatte - Bitte unterstützen Sie uns

Die Universität Koblenz-Landau, das Deutsche Forschungszentrum für Künstliche Intelligenz (DFKI), das DFKI-Spin-off coneno und die Technische Universität Kaiserslautern untersuchen in einem Live-Experiment die Wahrnehmung und die Wirkung der TV-Debatten 2021 („Triell“) zwischen den Kanzlerkandidaten Armin Laschet (CDU), Olaf Scholz (SPD) und Annalena Baerbock (Bündnis 90/Die Grünen).

Live-Experiment mit App zur ersten Kanzler-Debatte: Baerbock und Scholz profitieren deutlich stärker als Laschet

Die Universität Koblenz-Landau, das Deutsche Forschungszentrum für Künstliche Intelligenz (DFKI) und die Technische Universität Kaiserslautern haben im Rahmen eines Live-Experiments Wahrnehmung und Wirkung der ersten TV-Debatte 2021 („Triell“) zwischen den Kanzlerkandidaten Armin Laschet (CDU), Olaf Scholz (SPD) und Annalena Baerbock (Bündnis 90/Die Grünen) untersucht. Die Hauptergebnisse des Live-Experiments mit rund 110 Teilnehmerinnen und Teilnehmern: Olaf Scholz und Annalena Baerbock profitieren deutlich mehr als Armin Laschet von der Debatte. Zudem hat die Debatte einen erheblichen Einfluss auf Kanzlerpräferenz und Wahlabsicht.

Asking Your Questions.

Whether you want to fund our research and want to ask us questions or whether you want to ask your own questions in a smarter way, we want to hear from you! 631 627991-0