This VIQTOR DAVIS Podcast is about data and innovation. At this stage you can only try to envision how the world will look like by 2030 as a result of developments such as internet regulation, digital citizenship and advances in areas like artificial intelligence and hyper-connectivity. Every episode deals with a data related topic, driving digital transformation. We call this Data Craftsmanship.
Meet Bart Wassink and Herman Stehouwer, both have a track record in executing digitisation projects in the field of Customer Experience. They explain what digital customer service means today and how new technology contributes to a tailored customer experience.
Customer expectations towards digital customer service have changed in recent years. Increasingly, they expect customer service to be available at all times (24/7) and for all types of inquiries and transactions. They expect to be able to use the channel of their choice and get an increasingly tailored, personalized and trustworthy experience.
Customer and engagement data can be used to provide personalized interactions and to enable smooth transitions between channels, providing a tailored experience to each customer.
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We clearly see a growing need for guidelines and best practices to apply while executing end-to-end ML projects, so that delivery on the promise of Machine Learning is finally enabled.
VIQTOR DAVIS brings speed and agility in delivering Machine Learning pipelines which automate processes across the ML lifecycle to build, train, deploy and monitor ML models. In order to do so, we consistently follow our ML Ops principles. Meet Robin van der Heijden who explains the advantages of this concept.
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Responsible AI is about transparency and trust in Artificial Intelligence. In this first ever VIQTOR DAVIS Podcast we meet 'Data Scientist Marijn Kroes' who guides us through the world of Machine Learning and Black Box Decision Making.
Artificial intelligence is revealing the hidden value of data by automating decision-making. But poorly designed AI solutions can spiral out of control. There is, therefore, a growing need for artificial intelligence that can be understood and explained, operates according to regulations, norms and values, and is comprehensible and acceptable for customers and the public. Learn about how to build transparency and trust in existing or new AI solutions.
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