Processand Expertise in Advanced analytics

Simple analytics no longer cover today's reporting needs.

We help our customers activate ideas and solutions in order to take advantage of a new world full of opportunity. Sometimes classical analytics approaches are not sufficient at delivering the necessary information. This is where Advanced Analytics is required.

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Streamline your business operations with machine learning solutions.

AI Business Models

With hands-on experience in machine learning, our AI engineers help companies solve complex business problems by facilitating data-based decision making and building new data-driven business models.

Machine Learning Algorithms

We use techniques, including computational intelligence, pattern recognition and predictive analytics to create future-ready machine learning applications.

Optimize and automate your business processes.

Every journey begins with the first step. Let our team of highly experienced Process Mining veterans guide you through the rough parts of the road ahead and help you realize maximum ROI with minimal risk.

01. Prepare and process data

During this lengthy but critical step, we analyse your data, visualize it for better understanding, potentially select a subset of the most useful data and then pre-process and transform it to create a legitimate dataset.

After that, we split the dataset into three sets of data: training, (cross-) validation and testing sets. This is necessary...

1.) To train a model and define its parameters.
2.) To tweak the model's settings and parameters to achieve the best results.
3.) To evaluate a real model's performance to solve a task after training.

02. Develop models

We will train several models to decide which one produces the most accurate results.

We experiment with many different types of models, feature selection, regularization and hyper-parameters tuning until we get a well trained model – neither under- nor overfit. For each experiment, we evaluate model accuracy using the appropriate metric.

03. Deploy models

The process of putting a model into production depends on your business infrastructure, the volume of data, the accuracy of all previous stages and whether you're using machine learning as a service product.

04. Review and update

The project continues even after the model is completed.

We will help you track the metrics and apply testing to define your model’s performance over time and improve it when needed.

Leverage our advanced analytics development services.

Deep Learning

With artificial neural network algorithms, inspired by the human brain, we try to learn from large amounts of data.

Predictive Analytics

With statistical algorithms and machine learning techniques, we try to identify the likelihood of future outcomes based on historical data.


With our optimization algorithms we compare iteratively the various solutions until an optimum or a satisfactory solution is found.

Machine Learning

Machine learning algorithms help us do identify root causes of specific inefficiencies. With natural language processing we bring together unstructured data with structured ERP data.

Jakub Dvorak,
Senior Data Scientist

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