How did you hear about the Start-up Games?
We’re part of the current participants in the SpinLab Accelerators at Smart Infrastructure Hub Leipzig and a member of the Digital Hub Logistics in Hamburg. Both alerted us to the Startup Games.
What did winning the Start-Up Games mean for you?
After winning the Start-Up Games, we got a lot of new inquiries about our solutions. In our experience, we have relatively long sales cycles because our products require explanation, and a lot of planning is needed to put them into use. But we’re on the verge of concluding the first deals that go back to the Start-Up Games.”
What’s your biggest challenge right now?
Without doubt, one of the greatest challenges is finding personnel. Right now we’re looking for a full-time software engineer who knows his or her way around data science issues. We can already see that we’ll also need hardware people in the near future. Another challenge is maintaining focus. There are so many opportunities that unfortunately we often have to tell people no. It’s important to always keep sight of our vision and current goals so that we don’t lose track.
Have you adapted your business model because of the corona pandemic?
We’ve asked ourselves how our solutions can help in the current crisis. On the one hand, various studies have shown that there’s a connection between air pollution and Covid-19 mortality, and on the other, our measurements of CO2 and VOCs within buildings offer air-quality parameters that allow conclusions about air circulation. We’ve concentrated more on these aspects during the corona crisis. Several companies are already using our sensors and simple visualization tools to show their employees the quality of the air in the large-scale offices and encourage them to ventilate such spaces sufficiently.
What’s going on in your sector right now?
We’re increasingly seeing that users of air-quality sensors are no longer satisfied with just collecting data. One of the questions here more and more frequently is: “I know now where the problems are, but what do I do with the data?” Relatively early on, we focused on not just collecting data but deriving measures and solution scenarios from it. We call this “Environmental Intelligence.” I think that in future cities and companies will no longer draw up air-quality plans based on static models but that they will be determined dynamically and implemented automatically, based on existing data. They include automatic alterations in traffic flows, traffic signal patterns, dynamic public transport ticket pricing and direction of city sanitation. We already have a catalogue of 3500 air-quality measures and positive location factors we employ here. We also reuse data collected, in anonymous form, from one customer to the next, and we intend to improve in the area of intelligent data use. For example, together with a Finnish start-up we’re developing a routing app for pedestrians who want to avoid air pollution on their way from A to B. Our ultimate goal always remains improving the environmental quality of life.