The clever use of data is one of the most important drivers of innovation for companies. It enables the optimisation of existing processes and opens up new business models. We help you to exploit this enormous potential with the help of data science and artificial intelligence (AI).
We guide you safely through the world of big data, machine learning and (generative) AI. We identify potential and develop a tailored strategy for you
Based on your commercial goals and your individual jumping-off point, we develop roadmaps for projects relating to data analysis and AI
We create reliable forecasts and projections for your business based on large databases and we develop algorithms for efficient optimisation
Sometimes a picture is worth a thousand words. Wwe show you what's in your data with simple and clear visualisations of the results
We use computer-aided image, object and character recognition to implement new applications, from simplified ordering processes to parking guidance systems
Analysing sensor data offers opportunities to detect problems relating to material wear at an early stage and improve maintenance processes
In the age of the Internet of Things (IoT), Industry. 4.0 and Big Data, a strategic alignment in terms of Data Science AI is a must for companies in almost all sectors.
Businesses that still make decisions based on gut instinct risk being at an immense competitive disadvantage. Based on pattern recognition and predictive analyses, companies can make more informed data-driven decisions and optimize processes. In addition, the use of data provides an essential basis for new business models and innovative services and products.
With our solutions and expertise, we help you to develop your roadmap and to capture, process and understand objects, data and images. We use common methods such as the Cross-Industry Standard Process for Data Mining (CRISP-DM). We support you from the initial concept through prototyping to productive application.
Get more out of your data with us.
We help you with all the processes involved in data-supported value creation.
Informed, data-driven decisions
Automate repetitive tasks with AI
Faster reactions through forecasts
Improvement of processes through data analysis
Individual recommendations and offers
More innovative product development
In the first step, we determine the potential of data analytics AI for your business. Which use cases come into question? What goals should be achieved? What is the expected added value? These goals, once defined, can be refined going forwar
We then consolidate the available data. This includes analysing sensor data, for example. We check the quality of existing data and evaluate whether new data sources may need to be developed for the desired use cases
In the next step, we create a statistical model to solve the given problem. Here we rely on methods such as feature engineering, machine learning (supervised, semi-supervised, unsupervised), artificial neural networks (ANN) and deep learning (DL)
The implemented model is then reviewed in detail. The analysis and evaluation focus on performance, but also on the achievement of the defined goals
The final step involves integrating the model into a productive environment and deploying it in the intended process
In the field of data science and artificial intelligence, we rely on common tools, technologies and industry standards such as the Cross-Industry Standard Process for Data Mining (CRISP-DM).
