GeoAI & Machine Learning
Predictive models, computer vision on satellite and drone imagery, and spatial forecasting. We build geospatial AI systems that go beyond research papers. Our models run in production, serve real users, and integrate with your existing workflows.
What We Deliver
Models that forecast events based on where and when they are likely to occur. Used for risk prediction, demand forecasting, and resource planning.
Object detection and classification on satellite, aerial, and drone imagery. From identifying vegetation on railway tracks to tracking construction progress from above.
End-to-end systems that combine model inference with visualization and alerting. Not just a model file, but a deployed system your team can act on.
Rapid proof-of-concept development for novel geospatial AI applications. We partner with universities and research institutions to push the boundary between research and production.
How We Work
Every AI project begins with a feasibility assessment. We evaluate your data, define success criteria, and estimate what accuracy is achievable before committing to a full build. If the data cannot support the goal, we say so early.
We iterate on model architecture in tight feedback loops with your domain experts. The people who understand the problem validate the predictions. This catches issues that metrics alone miss, like a model that is technically accurate but operationally useless.
Deployment is not an afterthought. Every model ships with monitoring, retraining triggers, and clear documentation. We build the infrastructure around the model so it stays accurate as your data changes over time.
Tools & Technologies
Python, PyTorch, TensorFlow, scikit-learn, GeoPandas, Rasterio, GDAL, Mapbox, CesiumJS, cloud GPU (AWS, GCP, Azure)
Selected Projects
EIT UM & Graz Linien
A pioneering road safety initiative featuring real-time accident reporting, GPS-based location marking, and advanced data analysis to identify high-risk areas and prevent future accidents for public transit drivers.
RAG
A spatio-temporal prediction model for mining-related property damage claims, integrating spatial data with complex mining and claims datasets to forecast future incidents and visualize risk areas.
ThyssenKrupp Industrial Solutions AG
An automatic progress tracking solution for large construction sites using drone imagery, combining 3D geospatial datasets and artificial intelligence for smart, autonomous feature recognition and automated reporting.
BMBF
Together with the Karlsruhe Institute of Technology, Technical University of Munich, and public organizations, we participate in a research project that aims to develop a monitoring, data management...
BMBF
Together with the University of Potsdam, Technical University of Munich and KISTERS, we participate in a research program that aims at the development and integration of innovative digital tools for...
Your Project
Tell us about your project requirements. We'll match you with the right specialists and outline a tailored approach, no commitment required.