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Data Growth & AI - The way to AI implementation

How the use of AI succeeds with data & strategy

AI has become an integral part of everyday corporate life, offering more business benefits along the entire value chain. The basic prerequisite is the interaction of various elements, including a sound data infrastructure, a customized AI strategy and the right use cases. Our experts show what is needed to get off to a successful start with AI. 

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Data

Our data experts know the technical requirements for data, IT infrastructure and systems. These should definitely be checked and strengthened before using AI.
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Strategy

No AI without strategy: Our strategy team looks at the given challenges and identifies the AI use cases with the greatest added value for the department or company.
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Use Cases

There are many AI use cases, but which one has the greatest added value for your own company? One example of an optimized customer experience is our AI chatbot called Dicobot. Take a look at its development history here.
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How data unleashes the potential of AI

The "De-Hyping the Hype" report puts an end to unrealistic AI hype scenarios and highlights the critical importance of data in utilizing AI effectively. It emphasizes that only with high-quality data as input can the output of an AI solution achieve high quality. Within the report, you can discover the steps necessary to master the successful utilization of data and explore the questions and pitfalls that require consideration. 

De-Hyping the Hype-Report
Data & Technology Readiness
Is the data quality sufficient for successfully training AI?
Team Readiness

Do employees have the expertise to implement a transparent data culture?

Inventory

Can you answer "yes" to all the points in our AI readiness checklist?

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Successfully implementing AI strategies

In our "Playtime is over" report, we guide you through the process of implementing AI in your company or department with a focus on concrete application. Utilizing the four core elements of objectives, use cases, enablers, and implementation, our AI experts illustrate the components of a well-considered strategy essential before embarking on specific AI projects. We firmly believe that the “playtime” is past; now is the time to extract the maximum individual value from AI to enhance business success. Our approach steers away from trial and error, emphasizing a direct path towards effective implementation. 

Playtime is over-Report
Define goals
The goals of the AI strategy should be in line with the company's overall strategy. 
Identify use cases

AI applications with the greatest added value must be identified, evaluated, and prioritized. 

Find enablers

Not everything has to be done internally, cooperation with partners is important. 

Start implementation

The initial use cases and strategies are continuously optimized in an iterative implementation process. 

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AI use case Dicobot - our chat assistant

Would you like to know more about how AI chatbots are developed? Join our developer team and Dicobot during its creation and learn the development story from its perspective. Dicobot is now live and ready for testing! 

test now
Alpha
A specialized development team set to create a new type of AI chatbot called Dicobot.
Beta

The AI chatbot model of our Dicobot is being further refined. To do this, our AI chatbot is launched in a secure test environment.

Go-Live

The time has come: Dicobot is now available to all visitors to our diconium website. This means that our AI chatbot will provide you with all the information you want to know about diconium and our services to round off your visit to our website. Have fun testing it out!

Curious?

To find out more, please contact us!

Axel Wetten
senior business development manager