We tag and annotate objects and patterns in image files to create high-quality training data for machine learning.

Machine learning is already being used in many areas: identification of road users for autonomous driving, detection of diseases in health care, aerial image and earth observation data analysis, recognition of handwritten documents in business processes, and in cultural heritage archives. Humans are indispensable in the development of artificial intelligence. They must perform the necessary preliminary work by manually marking shapes, patterns, movements and objects in image data so that the software can then learn from this information. Manual preparatory work is very time-consuming and therefore expensive.

We can do this work for you at a reasonable price. Thanks to our impact sourcing partner Digital Divide Data, who runs operations in South-East-Asia and Africa based on a social mission, we are able to index your data quickly and reliably, with consistently high quality and at a fraction of European labour costs. We can flexibly adapt our capacities to your data volume, which will give you a lower entry barrier for feasibility studies and a faster time-to-market. Read the interview with founder Daniel Lanz.