Data science involves the use of scientific methods, processes, algorithms and systems to generate insights and create direct value from your data. Our data science practice has two major streams: advanced analytics and cognitive intelligence.
Within advanced analytics we use statistics and machine learning algorithms to reveal patterns in data which you can use for predictive maintenance, demand forecasting and modelling the behaviour of your customers.
Cognitive intelligence is used by our teams to develop centres of excellence using document mining and non-linear bots to increase efficiency within your organisation, automate manual processes and improve customer satisfaction.
Automatic (pre) processing of large number of documents/contracts leading to more efficient case handling, lower risk of errors and the ability to use large bodies of unstructured data.
Applying cognitive computing to enable automated decision support, such as conversational agents (chatbots). Agent technology improves customer service efficiency and effectiveness, provides guided navigation in complex rules and automates manual processes such as claims handling.
Scraping, classifying and mining news sources to provide the most important and relevant information from the external world in real-time. This provides in-depth knowledge on the competitors and market and supports early-warning alerts for breakthrough trends and external risks.
Using statistical and machine learning algorithms to reveal patterns in data. Applications range from predictive maintenance to (demand) forecasting, modelling customer behaviour, automatic email classification and routing, predicting claim or credit application validity and using computer vision to detect defects in high volume and velocity factory production output.