Trusted by Market Leaders in Education, Travel, Finance and E-commerce since 2007
We put excellence, value and quality above all - and it shows
A Technology Partnership That Goes Beyond Code
“Arbisoft has been my most trusted technology partner for now over 15 years. Arbisoft has very unique methods of recruiting and training, and the results demonstrate that. They have great teams, great positive attitudes and great communication.”
Created award winning app that helps predict vehicle parking through sensors
Arbisoft developed an award-winning parking prediction app for Predict.io, a Berlin-based startup focused on offline data management. The app accurately detects the driver's parking behavior using real-time sensor data, optimizing SDKs without being resource-intensive. As a result, Predict.io achieved its goal of launching quickly and saw an immediate boost in revenue, resulting in numerous prestigious industry awards.
IndustryTechnology
HeadquartersBerlin
PlatformAndroid
“The app has generated significant revenue and received industry awards, which is attributed to Arbisoft’s work. Team members are proactive, collaborative, and responsive.”Silvan RathCEO, Predict.io
Predict.io & Arbisoft
Founded by Berliners Silvan Rath and Jörg Sädtler, the Berlin-based startup Predict.io has been on a mission to “make sense of sensors” since 2012. predict.io is an intelligent offline data management platform helping retail brands drive revenue by anticipating and generating customer demand. Their SDK helps app developers use smartphone sensors to provide contextual updates and make devices location-aware.
predict.io - How we fit together
Predict.io reached out to us with the basic idea of developing an app that would accurately detect the when and where the vehicle was parked using smartphone sensors. They hired a team of Arbisoft engineers to develop a B2C app with machine algorithms that work with real-time sensor data to predict the driver’s parking behaviour. Arbisoft’s team was closely integrated with their team, building native apps and SDKs that were “location aware” without being resource-intensive. Our developers provided smart algorithms that optimized the SDK while adding critical functionality such as intent labelling and Points-of-Interest selection. We also developed algorithms that could avoid getting locked in by geofences or produce false positives.
