Large Language Models in Business Practice

Introduction

Large Language Models (LLMs) such as GPT have fundamentally changed expectations for modern word processing and communication. They enable impressively natural dialogues, the creation of complex content, the summarisation of extensive texts or even the generation of program code. However, while the innovative leap is undisputed, companies are rightly concerned about data security, loss of control and regulatory risks – especially with regard to the European General Data Protection Regulation (GDPR).

With AIR CHAT, a solution is now available that combines the best of both worlds: the convenience and versatility of modern LLMs, as well as the protection and sovereignty of a fully on-premise architecture. AIR CHAT is a language model service for a company's own infrastructure – powerful, scalable and GDPR-compliant. The following article examines the state of the art, the special requirements in the corporate context and how AIR CHAT meets these with technological depth and practical orientation.

The paradigm shift through LLMs

Large language models based on neural networks have made significant progress in recent years. Based on billions of parameters and huge text corpora, they not only understand syntax, but also the semantic and contextual subtleties of human language. This opens up a wide range of applications that go far beyond traditional text processing.

The paradigm shift brought about by LLMs is particularly evident in the way companies process and use language. For example, modern language models enable the automated creation of high-quality texts that are virtually indistinguishable from human content in terms of style, structure and coherence. Whether it's sales emails, technical product descriptions, social media postings or internal reports, targeted prompting can be used to generate texts that are both linguistically precise and relevant in terms of content. For example, a marketing team can use a few key words to generate full-fledged campaign texts that are precisely tailored to the target group in terms of tone, significantly reducing time to market.

The strengths of LLMs also come to the fore in the area of translation. They not only deliver literal translations, but also stylistically high-quality and contextually appropriate translations that take into account idiomatic peculiarities, technical terms and cultural subtleties. This enables international sales teams to create consistent documentation across countries or offer multilingual customer support without having to rely on several specialised translation teams. One example of how it can be used: in an international company, a product data sheet can be automatically translated into six languages in a few seconds – with impressive quality and without any loss of technical accuracy.

Another key field of application is the combination of extensive documents. LLMs analyse long texts, extract the most important information and present it in a structured way – a decisive efficiency gain in data- and document-heavy work areas. A compliance officer, for example, can have long regulatory texts prepared in an understandable short form in order to quickly identify any need for action. Project managers also benefit from LLMs, as they need to get an overview of existing documentation at the beginning of a new project – without spending hours reading it.

LLMs also have potential in software development: they generate code, explain complex functions, document source code and help with debugging. For example, a developer can automatically generate a Python script from a function description or replace existing, poorly documented sections of code with a comprehensible explanation. DevOps teams also use the technology to automate scripts or CI/CD processes – particularly helpful in dynamic environments with a high pressure to change.

Finally, LLMs also enable the development of intelligent dialogue systems that function as modern chatbots or internal assistance systems. They understand complex questions, keep the context of the conversation in mind and can even ask follow-up questions to provide more precise answers. In customer service, this makes it possible to answer queries faster, more consistently and more cost-effectively – even outside business hours. At the same time, internal users also benefit: an HR chatbot can quickly provide employees with answers about holiday regulations, processes or training opportunities – around the clock and without waiting.

Overall, LLMs open up a wide range of possibilities for making processes more efficient, making information more accessible and making the interaction between humans and machines much more natural. However, companies that want to tap into this potential need solutions that combine the convenience of such models with the highest data protection, integration and transparency requirements.

The data protection gap in public LLMs

The majority of LLM offerings available today are operated as cloud services, often outside the European legal area. In these cases, data used for query processing leaves the company's own infrastructure and is often – consciously or unconsciously – used to improve the model. This not only poses a compliance risk, but also directly conflicts with internal company data protection guidelines and the GDPR.

A key problem with the use of publicly available LLMs is the lack of transparency regarding how and where company data is processed and stored. Many cloud services operate in complex, geographically distributed infrastructures whose exact data flows are almost impossible to trace. For companies, this poses a significant risk, as neither the processing locations nor the security measures can be clearly controlled at all times – a situation that is unacceptable in sensitive industries or when handling personal data.

Another critical risk is the possible unintentional disclosure of data to third parties. When users send sensitive content – such as personal data, confidential business strategies or internal processes – to a public language model for analysis or generation, there is a risk that this data may fall into the wrong hands during model training or debugging. In many cases, it is not possible for the user to recognise whether and how this information is permanently stored, evaluated or reused.

In addition, the absence of control and audit mechanisms represents a structural deficit. When using external LLMs, companies have no way of systematically tracking which content has been processed, how, which users have accessed it, or whether data has been deleted in accordance with regulations. This lack of transparency poses a compliance risk with potentially serious consequences, especially for organisations in the finance or healthcare sectors that are subject to audits.

Last but not least, classic cloud LLM offerings are often incompatible with company-specific confidentiality and security requirements. In many industries, there are internal requirements that certain data must never leave the company's own infrastructure – for example in the public sector, in the area of critical infrastructures (KRITIS) or within the framework of client relationships. In such cases, the ‘Software-as-a-Service’ (SaaS) model is not allowed per se, regardless of the performance of the underlying language model.

Therefore, companies need a solution that unlocks the functionality of modern LLMs while maintaining complete control over infrastructure, data flow and user rights. This is exactly where AIR CHAT comes in.

AIR CHAT: LLM functionality securely in your own infrastructure

AIR CHAT was developed specifically for use in sensitive, privacy-critical corporate environments. It is a fully locally integrable LLM solution that works without connecting to external cloud services. The underlying models are operated on-premise, so that all data remains within the company's own infrastructure.

AIR CHAT offers the convenience of well-known AI platforms, but with the following key advantages:

• Data protection-compliant language processing in accordance with the GDPR, without third-country transfers.
• No data transfer or model training with company data – full sovereignty over content.
• High flexibility and customisability of the solution to company-specific use cases. Role- and access-based rights concept that ensures content is only available to authorised persons. Integration into existing IT environments (e.g. via REST APIs or as a microservice in containerised systems).

This makes AIR CHAT the ideal LLM platform for companies that prioritise innovation and data protection equally.

Scope of services: versatile fields of application in everyday business

AIR CHAT covers a wide range of typical tasks in a business context and can be flexibly configured for different departments and application areas. Its core functionalities include:

1. Text generation

AIR CHAT supports the automated creation of texts of all kinds – from e-mails and reports to editorial or technical articles. Based on a prompt, the system generates coherent, grammatically correct and stylistically appropriate content. Companies can use predefined templates or custom prompts to ensure specific writing styles, terminology or formats.

2. Document Summaries

The ability to efficiently summarise long texts is of great benefit, especially in knowledge-intensive environments such as law, compliance or research. AIR Chat analyses complex content and generates concise summaries that present the most important information in a structured way – ideal for decision-making processes, meeting preparations or knowledge databases.

3. High-quality translations

AIR CHAT enables translation between numerous languages based on context-sensitive models. Unlike traditional translation programmes, the model not only takes into account word meanings, but also idiomatic peculiarities and technical terminology. This enables companies to ensure consistent, high-quality multilingual communication – both internally and externally.

4. Code generation and explanation

Developers benefit from AIR CHAT through the automatic generation of code snippets, the explanation of complex functions or the commenting on existing lines of code. If desired, the solution can be enriched with industry-specific examples or internal company code standards, thus acting as an interactive assistant in software development.

5. Customer support and chatbots

AIR CHAT is also suitable as a basis for intelligent dialogue systems in customer service. Whether via a website, app or internal support portal – the LLM can answer questions automatically, trigger standard processes or act as an assistance system for service employees. Local data storage ensures that even sensitive content such as contract details or personal requests are processed securely.

Technological architecture: modular, secure and high-performance

AIR CHAT is based on a modular architecture principle that decouples various components, thus enabling flexible scaling and easy maintenance. The core consists of a high-performance LLM backend that has been further developed on an open-source basis and is specially optimised for on-premise use.

Outlook: The future of secure AI in companies

With AIR CHAT, it has been proven that state-of-the-art AI technology and strict data protection requirements do not have to be a contradiction in terms. The trend is clearly moving towards ‘AI Sovereignty’ – i.e. the ability of organisations to operate and further develop AI technologies under their own control and to integrate them into business processes without becoming dependent on cloud providers.

Conclusion: AI convenience without data protection compromises

With AIR CHAT, companies get the full range of functions of modern language AI – from text generation and translation to automated interaction – without having to give up their own data. The solution offers a convincing answer to the challenge of combining innovative technologies with regulatory requirements.

AIR CHAT represents a new generation of trustworthy AI systems that are not only efficient and powerful, but also secure and controllable. For companies that value data protection, adaptability and digital sovereignty, AIR CHAT is a future-proof tool for the transformation of speech-based processes.