Never send a human to do a machine's job.

Artificial intelligence (AI) and data analytics are undisputedly decisive levers in digitalisation and offer far-reaching possibilities for automation and information extraction. The use of the aforementioned technologies allows for scalability and determinism of processes and enables analyses with dimensionality and data volumes that are unattainable by human means. 

CORE has had the privilege of implementing various elements and services of Artificial Intelligence and Data Analytics for clients in different markets. From pattern recognition in genetic data to support diagnosis, statistical analysis of vehicle data to predict warranty claims, to the prediction of customer needs to support automated customer interaction. 

Often, companies and organisations are not initially clear about the extent to which their data can be used as valuable information or to automate processes. In addition, clients are at different stages of using AI or analytics. After a proof of concept, it is often determined that the first step is to create the necessary data infrastructure in order to harness the further potential of AI and analytics.  

The CORE Analytics Framework addresses the three levels of methods and models (that represent the analyses), technology and infrastructure (that represents the technical basis of performant data accessibility) and organisation (which focuses on the readiness of data usage in the organisation).