Data science

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.

Why work with VIQTOR DAVIS?

• We are frontrunners in natural language processing, artificial intelligence and cognitive computing
• Our data scientists are some of the most talented in the industry – over 50% have PhDs in quantitative sciences
• We offer you end-to-end delivery of all aspects of your project from design to implementation
• VIQTOR DAVIS is a Microsoft Gold Partner, AI Inner Circle, IBM Global Elite Partner and IBM Best Cognitive Solution

Focus

• Cognitive solutions
• Predictive analytics
• Innovative technologies

Key value propositions

Document mining

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.

Agent technology

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.

Market monitoring

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.

Predictive analytics

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.