Leveraging the full potential of geodata

Our mission

Integrating geodata into analyses and processes is a major challenge. They are difficult to obtain, are available in a wide variety of formats, and require a lot of storage space. This makes them the epitome of Big Data.

The Geo Engine is a cloud-based analysis platform that overcomes the limitations of existing solutions on the market. It connects data sources in such a way that data scientists can process them interactively over time intervals and analyze them visually. The results can be integrated into machine learning frameworks and business processes via our interfaces or presented to decision makers as an interactive app.

The Geo Engine allows to focus on data analysis

Our features


We offer a large repository of public data and incorporate your private research data and enterprise data lakes.


Geo Engine can be used via open interfaces from all common GIS tools and, for example, Python. AI frameworks such as Tensorflow are also connected.


Our engine handles correct data processing across space and time dimensions and scales to arbitrarily large datasets thanks to stream-based processing.


Geodata can be analyzed particularly well visually. Our web-based user interface offers linked views for visual analytics and an interactive workflow definition.

Open Source

The core version of our product includes the most important features as free and open source software (FOSS). The code and further information are available on GitHub.

In addition, we offer a commercial license for an extended Pro version and support for the Geo Engine. This includes a fully managed cloud service or on-premises deployment and integration.

The features of the Pro version target the needs of enterprise customers, such as increased effectiveness, vertical scalability, third-party integration, improved security or higher speed of Geo Engine. With this, we simplify large-scale management and offer several modules that extend Geo Engine’s functionality.

Your benefit

The effective provision of geodata collections and products plays a central role in scientific projects, public agencies and commercial enterprises. The same requirements are always in the foreground.

Existing data sources must be organized and connected.
Basic operations for selecting and preparing relevant data extracts must be provided.
An intuitive and interactive graphical representation of the data and operations should be easily provided to a wide range of users.

The Geo-Engine platform dramatically simplifies geospatial data portal creation. Our data connectors already tie in most data sources and can be easily extended to include new protocols. Based on our UI component library, portals can be realized with little front-end development effort. For processing the data e.g. for spatial filtering, temporal aggregation or blending of multiple sources the full functionality of the engine can be accessed.

Processing geodata in analyses is prohibitively complex. The selection and procurement of the right data is already costly. The preparation and processing of the data then costs 80% of the total effort, as studies have shown. This means that only 20% of the time can be spent on the actual analysis work.

With Geo Engine, we aim to reverse this ratio so that data scientists can focus on the actual analyses. For this purpose, we offer an existing repository with analysis-ready data. We hold particularly popular data sets directly, and we connect many other data providers in such a way that the data can be provided automatically on request. Own data can also be brought into the system with little effort by means of a semi-automatic import process. In the analysis work, our engine relieves users of the task of standardizing data sets and correctly processing time series with different resolutions or regularities. Through our web-based UI, analyses can be quickly created via exploratory workflows and the results interactively provided. Using our open interfaces, other tools such as GIS software or Python scripts can also be integrated into the analysis process. Overall, we can thus greatly increase the efficiency of data science work in the geospatial environment, as analyses can be created and reused more quickly.

AI methods of machine learning such as Deep Learning enable radically new applications – also for geodata. Satellite images can be classified and segmented so that clouds can be detected, for example, or defective solar panels on drone images. Beyond such detection, predictions based on current and historical data are extremely valuable. The basic prerequisite for all AI applications is high-quality training data.

Here, Geo Engine helps to create training data by connecting and preparing the raw data. For the actual training process, we offer a connection to frameworks such as Tensorflow and corresponding compute capacities in our cloud. The application of the resulting model is also supported by Geo Engine by providing it as an operator that can be applied in the system. Thus, the Geo Engine offers easy access to AI methods and the possibility to significantly improve analyses and predictions.

Our services


We support you in the realization of your geodata projects.

Application development

We develop special applications based on Geo Engine according to your requirements.

SaaS in the cloud

We offer you a cloud instance of Geo Engine tailored to your needs.

Our Team

We are an interdisciplinary team combining expertise from computer science, geography and business administration.

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Numbers & facts

earth observation satellites
PB data/year
bil. € market size
mio. locatable devices