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For us, artificial intelligence (AI) is not a break with the past, but a significant upgrade for the future. It optimizes work processes, increases efficiency and enables new approaches to solving old problems. AI supports human capabilities with immeasurable data processing capacity and precise analyses, opening up innovative paths and transforming industries in the long term. With AI, we are taking a step further towards progress, not away from tried and tested methods. This will make us better, faster and more resilient.

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Consulting

Is AI just the next hype again? Will our corporate landscape really change radically in the next 5-10 years? These and many other questions are on the minds of entrepreneurs. So what to do? We support you in these turbulent times with our many years of experience in consulting, digitalization and AI. We know what is currently possible and how you need to position yourself to keep up with the incredible speed of development. We have defined six steps to systematically analyze the potential of artificial intelligence (AI) in a company. Let’s get started.

Initial needs analysis and target definition

The first step is to understand the company's AI needs and goals. This is done through discussions and workshops with key people to identify business processes that can be improved through AI.

Inventory and data analysis

In the second step, the company's technology and data infrastructure is analyzed. Existing IT systems, data sources and data quality are reviewed. It is determined which data is available and how it can be used for AI applications.

Identification of AI use cases

The third step is to identify AI use cases that offer the greatest added value. Brainstorming and analysis of business cases help with the selection. The use cases are prioritized according to feasibility and impact in order to select promising projects.

Feasibility study and pilot projects

Step four validates AI use cases through feasibility studies and pilot projects. Prototypes or PoCs are developed and tested. The results provide important insights for further implementation.

Cost-benefit analysis and business model

In the fifth step, AI projects are evaluated economically. Implementation costs, potential benefits and savings are estimated. A business plan and an ROI analysis assess the economic viability of the AI initiatives.

Implementation strategy and roadmap

The final step is the creation of a detailed AI implementation strategy with a schedule, resource planning, risk management and training measures. A continuous monitoring and optimization process ensures the long-term successful use of AI solutions.

Training courses

Discover the fascinating world of artificial intelligence with our first-class courses. Learn from leading experts in the industry and gain valuable knowledge in machine learning, neural networks and data analysis. Our practice-oriented modules offer you the opportunity to directly apply what you have learned and continuously expand your skills. Whether you are a beginner or an advanced learner, you will find the right course with us to advance your career in the AI industry. Start your journey into the future of technology today! Register now and secure your place!

Introduction to artificial intelligence for business professionals

The first step is to understand the company's AI needs and goals. This is done through discussions and workshops with key people to identify business processes that can be improved through AI.

Data analysis and machine learning for corporate strategies

In the second step, the company's technology and data infrastructure is analyzed. Existing IT systems, data sources and data quality are reviewed. It is determined which data is available and how it can be used for AI applications.

Automation of business processes with AI

The third step is to identify AI use cases that offer the greatest added value. Brainstorming and analysis of business cases help with the selection. The use cases are prioritized according to feasibility and impact in order to select promising projects.

Customer data analysis and personalization with AI

Step four validates AI use cases through feasibility studies and pilot projects. Prototypes or PoCs are developed and tested. The results provide important insights for further implementation.

AI-based decision-making in management

In the fifth step, AI projects are evaluated economically. Implementation costs, potential benefits and savings are estimated. A business plan and an ROI analysis assess the economic viability of the AI initiatives.

Ethics and regulation of artificial intelligence in business

The final step is the creation of a detailed AI implementation strategy with a schedule, resource planning, risk management and training measures. A continuous monitoring and optimization process ensures the long-term successful use of AI solutions.

Data Science & Big Data

Welcome to the exciting world of data science and big data!
Do you want to better understand your data and turn it into valuable insights?
Our experts will help you navigate through the vast amounts of data and make informed decisions.
With state-of-the-art analysis tools, proven process models (e.g. CRISP-DM) and a touch of magic, we turn your data into gold.
Let’s get your data talking together and ensure the success of your projects.
Data analysis has never been so exciting and easy at the same time!

What is data science

The first step is to understand the company's AI needs and goals. This is done through discussions and workshops with key people to identify business processes that can be improved through AI.

Big data: what's behind it

In the second step, the company's technology and data infrastructure is analyzed. Existing IT systems, data sources and data quality are reviewed. It is determined which data is available and how it can be used for AI applications.

Important methods and tools of data science

The third step is to identify AI use cases that offer the greatest added value. Brainstorming and analysis of business cases help with the selection. The use cases are prioritized according to feasibility and impact in order to select promising projects.

Areas of application for big data and data science

In the fifth step, AI projects are evaluated economically. Implementation costs, potential benefits and savings are estimated. A business plan and an ROI analysis assess the economic viability of the AI initiatives.

Custom Solutions

Is AI just the next hype again? Will our corporate landscape really change radically in the next 5-10 years? These and many other questions are on the minds of entrepreneurs. So what to do? We support you in these turbulent times with our many years of experience in consulting, digitalization and AI. We know what is currently possible and how you need to position yourself to keep up with the incredible speed of development. We have defined six steps to systematically analyze the potential of artificial intelligence (AI) in a company. Let’s get started.

Requirements analysis

Business objectives, challenges and expectations are recorded in an intensive dialog with the customer. Targeted questions are used to identify the specific problems that the solution should address and clear, measurable goals are defined.

Concept and design

A detailed solution concept is created that includes architecture, functions and technologies. Wireframes or mockups illustrate the user interface. The concept is coordinated with the customer to ensure that it meets their requirements.

Development and implementation

The design is converted into a functioning solution. Agile methods and suitable tools are used. Regular tests ensure that errors are detected and rectified at an early stage.

Testing and quality assurance

The solution is seamlessly integrated into the existing IT infrastructure. Tests in the real environment ensure compatibility and performance. Training courses prepare users for use.

Introduction and rollout

Thorough tests check whether the solution meets all requirements and runs without errors. Performance tests ensure scalability and stability. Identified problems are rectified before deployment.

Maintenance and support

Continuous maintenance and support ensure optimum operation. Performance is monitored and errors are rectified. The solution is continuously improved based on feedback and new requirements.

Cloud, IoT, hardware co

We do a lot, but certainly not everything. Nevertheless, we also have a lot of experience in things that are not directly related to deep learning or AI. If you feel like it, just drop by our workshop for a coffee, there is always a lot to discover. The following is an excerpt.

Cloud Solutions

We are cloud natives. Our cloud solutions offer scalable, secure and efficient data processing for any business. Whether you need to store huge amounts of data or perform complex computing operations, our cloud services ensure performance and reliability.

IoT and sensors

Connect your devices intelligently with our IoT and sensor solutions. We integrate advanced sensor technology into your business to capture and analyze data in real time, resulting in more efficient and cost-effective operations.

VR/AR

Experience the future with our VR/AR solutions that create immersive experiences. Ideal for training, education and entertainment, our applications offer a new dimension of interaction and visualization.

Hardware prototyping

Our hardware prototyping service enables fast and precise development of physical products. From the initial idea to the finished prototype, we support you in realizing innovative solutions efficiently.

Smart Objects

Smart objects are revolutionizing everyday life and industry. Our intelligent objects are connected and autonomous, offer personalized functions and improve safety and convenience in many areas of life.

3D Prints

3D printing technologies enable us to produce prototypes and end products quickly and cost-effectively. Our 3D printing solutions offer exceptional design freedom and material diversity for every industry.