AI Infrastructure
Why an increasing number of mid-market companies are opting for local AI infrastructure — and how you can have your own AI productive in 4 weeks. Without US cloud dependency, without data protection risks, without exploding API costs.
The Challenge
Most AI solutions on the market run on US cloud infrastructure. That is convenient — but for German companies with sensitive data, it is a risk many underestimate. When you want to automate processes, a central question arises: where is your data processed?
US providers like Microsoft, Google, and OpenAI are subject to the CLOUD Act. This means: US authorities can demand access to your data at any time — even if the servers are located in the EU. Following the Schrems II ruling by the CJEU, the legal basis for EU-US data transfers is fragile. Any supervisory authority can audit and impose fines.
Those who rely on OpenAI or Azure AI tie themselves to a single provider. Price increases, changes to terms of service, or model deprecations — you have no control. In February 2024, OpenAI adjusted GPT-4 Turbo pricing three times within six months. Your budget planning? Obsolete.
API costs at OpenAI and Anthropic scale linearly with volume. What is affordable at 1,000 requests per day becomes a serious cost factor at 50,000. Companies report monthly API costs between EUR 5,000 and 30,000 — rising with every additional automated process.
When the OpenAI API goes down, your automated process stops. In 2024 alone, OpenAI had over 20 documented outages. Add to that: every request travels over the internet — with variable latency. For time-critical applications in production or customer service, this is unacceptable.
Certain industries are subject to strict regulatory requirements that effectively preclude cloud processing of sensitive data. In healthcare, patient data protection laws prohibit the transfer of patient data to third-party providers without explicit consent. Financial services firms must meet BaFin requirements (MaRisk, BAIT) for IT outsourcing — with comprehensive documentation and audit rights that US cloud providers cannot guarantee. Public authorities are bound to German infrastructure by the BSI basic protection compendium and EVB-IT contract standards. Companies in these sectors that want to use AI productively need infrastructure that meets these compliance requirements from the ground up.
Our Approach
We use a hybrid architecture that gives you maximum control without sacrificing performance. Sensitive data stays on German servers — non-critical tasks can optionally be processed in the cloud. This is how we combine data protection with cost efficiency, as part of our process automation solutions.
On-premise or private cloud in ISO 27001 and BSI C5 certified data centres. Locations in Frankfurt, Munich, and Hamburg. Your data never leaves German sovereign territory. Physical security, redundant power supply, 24/7 monitoring included.
The world's best open-source models, hosted on your infrastructure — no vendor lock-in, full transparency over model behaviour, and the ability to fine-tune on your company data. For text processing, we use Llama 3.1 (8B to 405B parameters): in benchmarks like MMLU, the 70B model achieves 82%, on par with GPT-4 for structured tasks such as classification and extraction. For speech-to-text, we use OpenAI Whisper (locally hosted) — with a word error rate below 5% for German-language recordings, comparable to commercial cloud services but fully on-premise. For image analysis and visual inspection, CLIP is deployed: the model understands relationships between text and image, enabling semantic image search, quality control, and automatic categorisation without cloud connectivity. These are complemented by Mistral Large, Mixtral, and Qwen — we select the optimal model for your use case.
Not every task needs the largest model. Our routing layer automatically selects the optimal model for each request: a 7B model for simple classifications, a 70B model for complex analyses. This saves up to 80% in compute costs — without quality loss.
Sensitive data (contracts, personnel files, financial data) is processed exclusively locally. For non-critical tasks such as general text generation, the cloud can optionally be used. You define the rules — our system enforces them automatically.
All solutions are implemented GDPR-compliantly and can be seamlessly integrated into your existing IT landscape via system integration.
Comparison
The right infrastructure depends on your requirements. Here are the four common options in a direct comparison.
Use Cases
Not every use case requires local infrastructure. But with sensitive data, high volume, or real-time requirements, on-premise AI makes the decisive difference. Here are the five most common scenarios we implement as part of our process automation.
Automatically analyse, classify, and extract from contracts, invoices, proposals, and correspondence — without a single byte leaving Germany. Particularly relevant for law firms, insurance companies, and the public sector. Processing speed: up to 500 documents per hour on a single GPU server.
Make internal company knowledge searchable and usable — trained on your own data, manuals, process documentation, and emails. Employees receive precise answers in seconds, instead of spending hours searching SharePoint. RAG-based (Retrieval Augmented Generation), with source citations.
Sales forecasts, churn prediction, maintenance intervals — calculated on your own servers. Your historical business data stays internal. Particularly relevant for companies with confidential revenue or customer data that must not flow into external systems.
Image recognition and visual inspection directly on the production line — processed locally, in real time. No internet latency, no external dependencies. Defective parts are detected in milliseconds. Ideal for manufacturing companies that need to protect production secrets.
A local AI chatbot, trained on your company knowledge base — manuals, FAQs, product documentation, ticket history. The bot automatically answers 60–80% of all Tier 1 support inquiries without transferring customer data to external services. Inquiries about order status, product specifications, or contract terms are answered in real time, around the clock. More complex issues are forwarded to your team with full context. The result: on average 45% shorter response times, significant relief for your support team, and the assurance that confidential customer data — contract information, payment data, personal concerns — never leaves your infrastructure.
Frequently Asked Questions