Generative Artificial Intelligence (GenAI)
Successfully deploying technology
with data expertise and software excellence

From concept to reality: GenAI

Generative artificial intelligence (GenAI for short) has the potential to fundamentally change the way we live and work. In companies, it can contribute to significantly more efficient workflows, a high degree of individualization, and rapid market launches in almost every department.

Difference between AI and GenAI

Traditional artificial intelligence (AI) analyzes existing data to identify patterns and draw conclusions. The difference between GenAI and traditional AI is that GenAI not only analyzes data, but can also generate completely new content, such as text, images, or code. This opens up entirely new applications for GenAI in business.

Companies that manage to harness the potential of GenAI will gain long-term competitive advantages. The successful use of GenAI depends on proven data competence and a high level of expertise in software and application development. We are the right partner for this.

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That is our promise

Data expertise meets software excellence

Rapid developments in the GenAI environment require more than just excellent technical skills. With many years of experience in software development and data analysis, our multidisciplinary teams support creative problem solving to create unique benefits for your company through GenAI. Particularly important: actively monitoring the latest AI developments and continuously adapting skills that are critical to success.

End-to-end partner for GenAI projects

We are the right partner for the entire process, from brainstorming to maintenance. We keep an eye on the specific challenges of GenAI in all phases: This starts with data quality, covers ethical and data protection issues, among other things, and extends to the selection of suitable control and monitoring mechanisms for AI-generated content. Always with the right balance between costs and benefits under the given legal framework.

Independent advice for the best solution

The selection of tools, technologies, frameworks, and cloud AI service providers always follows the problem solution, not the other way around. We navigate independently through a make-or-buy decision, always with the best solution in mind. With our many years of experience, we evaluate all relevant factors, such as time-to-market, competitive differentiation, and scalability options for solutions. Whether you need an off-the-shelf product or a deeply integrated custom solution, we will find the right solution for you.

Using GenAI correctly:
These are the first steps

The first steps are usually the hardest. The following points will help you make the right decisions for using GenAI.

  • 1. Select risk-tolerant areas

    Are you using this technology for the first time? Choose an area that has a certain risk tolerance.

    The application should not be critical to the operation of the business, but should offer teams a gain in comfort or efficiency.

  • 2. Incorporate control mechanisms

    Full automation is counterproductive in the first step: explicitly integrate functionalities for human control. For example, by having AI generate the first draft of a support mailing, but having employees send it out.

    AI capabilities are developing at a rapid pace. Controlling generated content is an important success factor, as current models are still immature in certain application scenarios.

  • 3. Start with text- or code-intensive topics

    The breadth of topics covered by GenAI can quickly become overwhelming. Therefore, try to focus initially on text- or code-intensive tasks, such as generating dossiers, sentiment analyses, or automatic vulnerability analyses in the build pipeline.

    Be sure to balance the relationship between cost, benefit, complexity, and risk.

  • 4. Consider: What is the business value?

    Not everything that is feasible is also sensible to implement: always ask yourself what value can be created for the company.

    If you manage to generate insights quickly, you can realign processes and company capabilities and learn to use and expand the capabilities of GenAI.

Unique range of expertise

Specific expertise in various specialist areas is required to successfully implement GenAI. With the experience of our experts, we combine all the necessary skills to ensure that your project achieves real business value.

Data management

  • Data collection and preprocessing: The ability to collect and preprocess relevant data for training and inference.
  • Feature engineering: The ability to extract raw data and convert it into meaningful features that can be used by machine learning models.

Implementation and maintenance

  • Model deployment: The ability to deploy trained models in a production environment to make them accessible for real-time predictions or decision-making.
  • Model monitoring and maintenance: The ability to continuously monitor and maintain the performance of deployed models to ensure they remain accurate and up to date.

AI accountability

  • Explainability and interpretability: The ability to provide explanations or insights into the decision-making process of AI models to ensure transparency and trustworthiness.
  • Ethical considerations: Understanding and incorporating ethical principles and considerations into the development and deployment of AI systems.

Machine learning

  • Machine learning algorithms: Knowledge and implementation of various machine learning algorithms such as regression, classification, clustering, and deep learning.
  • Model training: The ability to train machine learning models using labeled data or unsupervised learning techniques.
  • Model evaluation and validation: The ability to evaluate the performance of trained models and validate their accuracy and reliability.

Specific AI functions

  • Natural language processing (NLP): The knowledge and application of techniques for understanding and processing human language, including tasks such as text classification, sentiment analysis, and language translation.
  • Computer vision: The ability to analyze and interpret visual data, including tasks such as object recognition, image recognition, and image segmentation.
  • Reinforcement learning: The ability to learn and make decisions by interacting with an environment, using techniques such as reward-based learning and policy optimization.

Your contact

Do you have a specific concern or questions about the use of GenAI in your company? Feel free to book an appointment.

Jens Werschmöller, Lead Generative AI Team

FAQ

What is Generative Artificial Intelligence (GenAI)?

GenAI refers to AI models that can generate new content such as text, summaries, images, or code. Companies use GenAI to accelerate knowledge work, automate processes, and develop new digital products and services.

What added value does the use of GenAI offer companies?

GenAI can help reduce costs, optimize operational processes, and accelerate product development by automating repetitive tasks and developing new AI-supported digital solutions.

How does iteratec support companies in the field of generative AI?

iteratec helps companies identify potential for generative AI and supports them in developing and implementing suitable solutions. The focus is on both technical and technological issues.

How can you get started with GenAI?

A structured introduction can be achieved through formats such as workshops, boot camps, or sprints, in which relevant applications are developed together with experts and initial concrete approaches are developed.