Zegami was born out of a collaboration led by Oxford scientist Steve Taylor and tech polymath Roger Noble to analyse and understand large datasets from experiments generating thousands of images of cancer cells and data from the human genome. The application of Zegami starts with any output from any imaging methods e.g microscopes, ultrasound, X-Rays allowing scientists or clinicians to look for trends and outliers in large data sets. Building on this Zegami works with teams creating machine learning models where it is key to understand and look for problems or biases in the training data.