The amount or complexity of the available data often establishes the need for analytical and machine learning (ML) models in companies. By using them, we provide a deep insight into previously unknown parts of the data, we can make predictions, predictions, optimizations and reveal more complex relationships.

What can I use it for?

There are many possibilities and benefits waiting for you with the data. Clients usually ask for predictions and optimization, but it can also provide answers to problems that we might not have even thought of. For example:

• Anomaly detection between data,
• Price offers and dynamic pricing,
• Logistics system automation,
• Predictive maintenance,
• Optimizing production efficiency,
• Minimizing scrapping and quality control,
• Stock optimization,
• Development of energy management,
• Prediction of production defects.

When is it worth it?

In the case of large amounts of data or to solve complex problems, several medium-sized companies have already realized that the best way in today's modern world is AI. Continuous development needs and predictive analyzes offer its users a competitive advantage and cost reduction options, not to mention those processes that are overloaded or too complicated and would need a sophisticated solution.