Generative AI with STACKIT

How Data Is Transformed into Effective Solutions
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July 31, 2026, Reading time: 6 minutes

💡 At a Glance: What Is Generative AI?

Generative AI accelerates processes, automates customer service, and analyzes large datasets. With STACKIT’s robust cloud platform, businesses and government agencies can use LLMs, code generators, and image generators in full compliance with the GDPR within the European legal framework. Through finely tuned models, scalable infrastructure, and standardized interfaces, you can combine maximum performance with absolute data sovereignty.

Generative AI with STACKIT: How Data Becomes Solutions

As we all know, time is money. Today, businesses and government agencies must process more information than ever before. Service processes need to run faster, and decisions must be made more quickly. At the same time, demands for security and data protection are rising—as are the expectations of citizens and customers. Whether it’s precise answers and short processing times, seamless customer service, real-time analytics, or the rapid evaluation of massive amounts of data: without generative artificial intelligence, these capabilities are hardly conceivable anymore.

Generative AI like ChatGPT automates on a large scale, lightens the daily workload, and creates space for new ideas—all while strictly adhering to national and European data protection standards, of course. STACKIT ensures that data remains under control and that digital transformation doesn’t falter due to complex requirements. Whether it’s code, text, images, document generation, or smart chatbots—the possibilities for using generative AI are as diverse as your challenges.

Find out here how STACKIT’s robust cloud platform adapts to your needs and what companies should keep in mind when using generative AI in the future.

Key Terms Related to Generative AI

Generative AI with STACKIT: Your Benefits at a Glance

STACKIT brings together the strengths of generative AI on a single platform that combines practicality, data protection, and flexibility. The following benefits show how this technology can be a true game-changer for your business as well.

Control Over Training Data & Data Protection

Your own data can be used in compliance with the GDPR to train generative AI models without leaving the European legal jurisdiction. This ensures that companies and government agencies retain control over sensitive information at all times. This is a key advantage for all digital products created using AI.

Custom Models & Quality Assurance

Generative AI models specifically support industry-specific applications and use cases—whether for technical texts, code snippets, or automated analyses. Custom training pipelines, regular quality checks, and traceable model versions generate content that consistently meets your own standards.

Scalable infrastructure for complex tasks

Whether it’s a proof of concept or continuous production operation, STACKIT provides flexibly scalable computing resources—even for computationally intensive large language models, image or code generators, and complex machine learning workloads. This allows you to reliably run everything from small pilot projects to large training and production environments within your own tenant.

Seamless Integration of Generative Tools

From LLMs to image and code generators: With STACKIT support, you can easily integrate and combine various generative tools. The platform supports both proprietary models and open-source solutions and integrates seamlessly into existing processes and system landscapes.

Transparency, Security, and Auditability

With STACKIT, all processes can be seamlessly documented—from the training data used to the generated content and model updates. This simplifies audits, meets compliance requirements, and ensures that critical applications are always operated in a traceable and secure manner.

Generative AI with STACKIT: How the Technology Works in Detail

Generative AI models reach their full potential when they are deployed strategically, securely integrated, and continuously optimized. To achieve this, STACKIT utilizes robust cloud environments that support both standard solutions and customized workflows—ideal for customers in government, digital health, or retail.

From Generative AI Models to Custom Solutions

The first step is selecting the right generative AI model. STACKIT offers a variety of options—from large language models (LLMs) for text and code to image generators and industry-specific variants. Pre-trained models, such as GPT-based variants, are activated immediately. You can easily integrate your own models or open-source models. Integration is handled via standard APIs. Many generative AI models are based on deep learning technologies that are specifically designed to accurately recognize complex patterns.

Your own data is processed in the STACKIT cloud in compliance with the GDPR. For specific tasks, a model can be tailored to internal data or optimized through fine-tuning. Methods such as supervised learning or reinforcement learning are also used for generative models. This results in applications that are precisely tailored to the target audience and significantly improve the quality of the results.

Automated Workflows in Practice

The finished applications run on a scalable infrastructure and automatically deliver high-quality results—from the intelligent processing of large amounts of data to the creation of new content. Generative AI tools analyze complex data sets, generate reports, and can independently create and initiate processes. Interfaces ensure that the AI integrates seamlessly into existing systems and workflows or can be used as a standalone application.

Raise Quality Standards, Ensure Security

STACKIT supports ongoing quality control with monitoring and audit functions. Results are checked for accuracy, language style, and compliance requirements to flexibly improve rule systems. At the same time, the verified infrastructure ensures protection: access rights, encryption, backups, and updates are integral components. In this way, the quality of the generated content remains consistently high—even with complex models such as VAEs.

Real-World Examples: Use Cases for Generative Artificial Intelligence

Whether it’s automation, analysis, or content creation—these examples show how generative AI works in practice with STACKIT.

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Efficient and Data-Secure Responses to Citizen Inquiries in Public Administration

Long wait times for responses are a thing of the past when generative AI automatically captures, sorts, and answers citizen inquiries. An intelligent chatbot can understand complex phrasing such as “Where do I apply for a new passport?” and provide a precise, legally compliant answer that directs the user directly to the appropriate online application form. All data remains in certified data centers in Germany or Austria—fully GDPR-compliant. In addition, the generative AI checks submitted forms for completeness and automatically requests any missing information. This significantly reduces the workload on specialized departments.

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Optimized Patient Communication and Analysis in Digital Health

Using just a small amount of structured medical history data, AI generates a complete patient summary within seconds. Generative AI processes medical content and formulates it in understandable language. It checks medical findings for consistency and identifies patterns in large datasets that indicate risk factors. This provides physicians with targeted guidance for diagnosis and treatment. All processes are auditable and compliant with regulations, with sensitive data stored locally in the STACKIT Cloud.

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Create and Analyze Content for E-Commerce Applications in Real Time

What used to take hours now happens in minutes: Generative AI creates product descriptions for large product ranges, translates them into multiple languages, and optimizes them. Customer reviews are analyzed in real time and translated into trends such as “Many buyers praise the new battery feature.” Critical issues are also immediately identified and flagged. Product management and marketing can respond promptly, while new variants go live in the ERP system in no time.

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Tips for Successfully Getting Started with Generative AI Models Using STACKIT

With the right strategy, appropriate technology, and clear processes, you’ll lay the foundation for successful generative AI projects with STACKIT.

Choose the Right Generative Model for Your Use Case

Not every AI model is suitable for every goal. Large language models are well-suited for text and code generation, image models for creative content, while specialized variants are ideal for industry-specific analysis. STACKIT supports you in making your selection with consulting, test environments, and customized models. This is how we help you find exactly the right model to meet your needs.

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Commit to consistent data sovereignty

Data protection isn’t an option—it’s a requirement. With STACKIT, all data remains in certified data centers in Germany or Austria and is processed in compliance with the GDPR. This ensures you have full control and protects sensitive information—a crucial factor, especially in the fields of public administration, healthcare, and e-commerce.

Data Sovereignty with STACKIT
Plan resources realistically

Performance requirements can vary significantly depending on the model. While smaller applications can get by with moderate computing power, complex LLMs or image generators often require GPU-accelerated environments. STACKIT offers granular resource management that allows you to precisely adjust capacity, reduce costs, and boost performance.

Promote knowledge sharing within your team

Generative AI is transforming workflows in a lasting way. Train your teams, actively involve users in the development of new processes, and foster collaborative learning through the exchange of best practices. The more expertise available within the company, the more efficiently and securely the technology can be deployed—including to optimize marketing strategies based on data.

Insist on seamless integration

Standardized APIs and interfaces make it easier to integrate AI into existing workflows, document management systems, or ERP systems. Plan the integration so that AI is part of a seamless process chain.

Test Before Going Live

Every new model should be thoroughly tested before going live. Use test environments to evaluate outputs, identify potential sources of error, and make adjustments. This will help you avoid costly corrections during live operation.

Keep your systems up to date

AI models and cloud services are constantly evolving. Schedule regular updates to benefit from performance improvements, new features, and optimized security mechanisms. Our support team ensures that updates are deployed smoothly and without interruption.

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Generative AI with STACKIT – Use It Confidently, Reap Lasting Benefits

Generative artificial intelligence has long been part of everyday business. When used correctly, it can accelerate processes, increase productivity, optimize customer service, and generate a clear competitive advantage—in the public sector as well as in retail and the digital health sector.

Our cloud infrastructure delivers full performance and ensures that your AI applications remain transparent, secure, and flexible. When you implement generative AI with STACKIT as your partner, you’re making a choice for data sovereignty, control, and a long-term competitive advantage.

Frequently Asked Questions About Generative AI with STACKIT

What generative AI models does STACKIT offer?

STACKIT offers pre-trained models for text and code generation (LLMs), image generation, and industry-specific applications. Additionally, you can train and customize your own models.

Can I integrate my own generative AI models?

Yes, through standardized interfaces and flexible cloud solutions, you can seamlessly integrate and scale your own or external models.

What are some examples of generative AI applications?

Possible applications range from automated text generation in customer service to document verification in administration and code generation in development teams. These examples demonstrate how flexibly generative AI can be used in practice with STACKIT—from searching for relevant information to automated analysis and the creation of new content.