AI? Big Data?
Enough with buzzwords!

Get more out of your IoT data today

Our Data Science experts solve your challenges in the exploitation of IoT data. Benefit from our many years of experience and proven solution components.

Use IoT to enable data-driven decision making

The content of our standardized workshop packages is designed to facilitate data-based decision-making. We first analyze the existing data basis and determine potential business challenges. Simultaneously, we support you in ensuring sufficient data quality.

Initial prototypes help us to build an infrastructure specifically tailored to you and be able to establish a new value creation of the data. Of course, the new infrastructure can be integrated into your preferred cloud service.


Our approach

Data quality

Ensuring sufficient data quality is a prerequisite for any data science use case, whether simple or complex. This forms the basis for all further considerations.

Using our insights from dozens of cross-domain IoT projects, we can ensure a rapid analysis of your existing data. At the same time, we always maintain an eye on any potential errors that may occur, any corrections that may be necessary as a result, and any new, feasible use cases.

Added value

As soon as correlations are detected and initial data-based decisions can be made, the process of value creation begins. You can benefit from automatic reporting, predictive maintenance or the optimization of your processes.

360° Support

We will consult with you to analyze your individual requirements in order to find and implement the right service infrastructure for you. In doing so, we always keep sustainability and scalability in mind. By using simulation studies, we validate our considerations.

Questions about long-term operation and adoption of the systems? Our experts are happy to help you with that as well.

Our areas of responsibility

Consulting on IoT data utilization

Consulting on IoT data utilization

Let us work with you to get more out of your IoT projects and data. Regardless of whether you have already developed ideas and use cases or whether you still have no idea whether data analytics can add value to your business. Our non-committal consultation will pick you up exactly where you are right now.
Exploratory data analysis

Exploratory data analysis

Using data analysis, we identify the potential that can already be utilized today. The focus lies on key aspects of data quality, such as the completeness, correctness, timeliness and usefulness of the data. On this basis, we work out correlations in a structured manner and present them through intuitive visualizations.


We use prototypes to quickly determine whether and when a result can be achieved with the selected solution approaches and methods. To do this, we use both existing and simulated data. Specifically, it can be used to identify a point in time at which an evaluation or prediction can be expected to be sufficiently accurate.
Advanced Analytics

Advanced Analytics

Through your data, you can provide more than just statements about past events. Predicting key parameters can facilitate your decision-making processes. In addition to predictive maintenance, there are many other possible applications, for example in the area of production quality, warehouse and maintenance, or in the context of supply chains.
Create business value

Create business value

Together, we analyze how your IoT data can have the greatest impact. In addition to the immediate added value for your customers, this also includes opportunities for indirect value creation within your business. We focus on the most purposeful methodology that enables the use case. AI and machine learning are just some of the possible tools.


Depending on your needs, we can either build a new, independent "Data Driven Platform" or integrate it into existing architectures. We always decide according to the focused use case as well as the current and future requirements of your solution.

Successfully implemented

Service Meister

Data-driven and predictive maintenance analysis for connected tools from Würth.
Hypothesis testing examines anomalies in the data for statistical significance.
Our parameterizable algorithm detects anomalies on any data set.
Classification of tickets using Natural Language Processing.
Automation and Monitoring of Data Science Applications with Apache Airflow Pipelines.

Knorr Bremse

Azure based platform for maintenance data analysis of trains.
Using Databricks to run Data Science applications.
Terraform modules for rapid deployment and parameterizable pipelines.
Data Lakehouse for linking data lake and data warehouse structures.
Apache Spark for efficient and parallel processing of big data.


Get in touch

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