Advanced analytics

Let your machines work for you.

Wouldn't it be nice when machines can perform tasks without explicit instructions. That is exactly what machine learning or artificial intelligence are all about: learn your machine to help you. Yet developing algorithms and fine-tuning statistical models is a complex and time-consuming task. Luckily we are there to help you!

What is machine learning and artificial intelligence?

With GenAI emerging, everything is labelled as Artificial Intelligence. Even though Machine Learning and Artificial Intelligence are related fields, they are not the same. Machine Learning is a subset of AI that specifically focuses on the development of algorithms and statistical models that enable computers to learn from and make decisions based on data. ML systems improve their performance over time without being explicitly programmed to perform a task.

Machine Learning and Artificial Intelligence focus on providing predictions based on past behavior. The recent rise of GenAI has transformed how we interact with these models. Generative AI no longer restricts itself, but is set free to generate new content, unlocking new possibilities.

Why embark on the AI journey today?

In today's dynamic landscape, ML and AI are not just a luxury but a necessity. Global organizations have risen the bar of expectations: customers expect a personalized experience through recommenders, personalized content and much more. On the other hand, operational excellence is becoming one of the main objectives for executives. Consider the impact of predictive analytics automating supply chain management, or personalized customer experiences driven by machine learning algorithms. These are just a glimpse of the countless possibilities.

How we turn your ML use-case into success.

Through our data strategy offering, we help our customers to identify valuable use-cases, even those including machine learning tasks. With our data architecture offering, we assist you in selecting the right toolbox to support your use-cases. That is rather the start of your use-case, you can now start creating value. Our experienced machine learning engineers can assist you throughout the entire process of data collection, algorithm selection, model training and evaluation, and MLOps.

We recommend the most suitable ML algorithms and techniques based on the use-case requirements and data characteristics. We develop, train, and evaluate ML models using best practices to ensure they meet the defined success criteria. Fine-tuning models can take a huge amount of time, and has an uncertain outcome. Together we time-box the development time, to optimize your effort-to-value.

We will implement performance monitoring to continuously monitor the behavior of your algorithms. We will develop strategies for model retraining to either adapt to the arrival of new data, or purely to improve the model. We do not only focus on the mathematical performance of models: in the end you build use-cases to obtain value, hence we will measure the business impact of your machine learning use-cases.