Your own AI. On your servers. Under your control.
Private AI infrastructure enables companies to run AI models on their own servers, under their full control. Most companies use AI through public services such as ChatGPT, Google Gemini, or Microsoft Copilot. This works fine for simple tasks. But as soon as you start processing business-critical data, customer information, or confidential documents, you run into fundamental problems.
Your data is processed on servers outside Europe. You have no control over what happens to that data. Some providers use your input to train models, including your trade secrets. And costs can quickly add up with heavy use, without you ever owning the infrastructure.
With Private AI, you can run AI models on your own servers or in a secure cloud environment. All data remains within your organization. You decide which models to use, how they are trained, and who has access. This isn’t a luxury—for more and more companies, it’s a necessity.
The AI market is broadly divided into two camps: proprietary models from major tech companies and open-source models that are freely available. Both have their place, but there are significant differences between them.
Powerful and user-friendly. You pay per API call and get immediate access to the latest technology. The downside: your data leaves your organization, you’re at the mercy of the provider’s pricing, and you have no insight into exactly how the model works.
Models such as Llama 4, Qwen 3, and DeepSeek-R1 perform comparably to their proprietary counterparts on many tasks, but you can run them on your own hardware. There are no per-token API fees, you have full control over your data, and you can fine-tune the models using your company’s expertise.
In practice, most organizations opt for a hybrid model. Sensitive tasks run on private infrastructure, while non-sensitive tasks are handled via cloud APIs. Mediacooks you design this architecture.
Not an overengineered enterprise solution, but a pragmatic setup that works, is secure, and allows your team to get started right away.
We assess your current processes, data flows, and IT environment. Where does AI automation offer the greatest value? Which data is sensitive? Which systems need to be integrated? Based on this analysis, we determine whether on-premises, hybrid, or cloud-based AI is the best fit.
We design the technical architecture: hardware or cloud, model selection, integrations with your CRM, website, or internal systems, and the RAG pipeline that allows the AI to use your business knowledge as a source without permanently storing data in the model.
We build the environment, install and configure the models, connect your knowledge sources via RAG, and train the system to match your tone of voice, processes, and business rules. Your team will have access to an intuitive interface, similar to ChatGPT, but completely private.
Models improve, hardware evolves, and your organization grows. We monitor performance, update models when better versions become available, and scale to meet your needs. We can provide this as a managed service or train your team to manage it themselves.
We use proven, enterprise-grade open-source technology. No experimental tools, but components that are used every day by thousands of organizations worldwide.
The heart of your Private AI environment. Ollama makes it possible to run open-source LLMs locally with minimal configuration. For higher volumes and production workloads, we use vLLM, optimized for speed and efficiency.
Depending on your scale, we’ll recommend the right hardware. For small-scale implementations, an Apple Silicon Mac (M-series) or a server with an NVIDIA GPU is sufficient. For larger organizations, we set up dedicated GPU servers at a Dutch data center.
Instead of feeding all your business data into a model, we use Retrieval Augmented Generation. The model consults your documents and knowledge base the moment a question is asked. Data stays where it belongs, and answers can always be traced back to their source.
Your team works with a familiar browser-based chat interface, similar to ChatGPT, but running on your own infrastructure. No data leaves your organization.
We integrate your Private AI with your existing systems: CRM (HubSpot, Salesforce), email, website, and internal databases. Using APIs and workflow tools like n8n or Make, we automate processes end-to-end.
| Private AI (on-premises) | Public AI (API/SaaS) | Hybrid | |
|---|---|---|---|
| Data ownership | 100% with you | At the provider | You choose for each task |
| GDPR compliance | Entirely under our own control | Depending on the provider | To be configured per use case |
| Costs for high volumes | Hardware | Variable; can add up quickly | Balanced |
| Fine-tuning using your own data | Unlimited | Limited or not possible | By model |
| Vendor lock-in | None | High | Limited |
| Available offline | Yes | No | Partially |
| Suitable for sensitive data | Yes | Risky | Yes, provided it is properly set up |
Then Private AI is the logical next step. Combine it with our Agent as a Service or AI knowledge base for maximum results. Mediacooks you from strategy to implementation: pragmatically, securely, and tailored to your needs.
We are neither a data center nor a pure IT provider. Mediacooks a digital marketing and sales automation agency that leverages private AI infrastructure where it delivers the greatest value: in your customer processes, marketing, and sales. Check out our CRM integration and AI Agency services as well.
Private AI means running AI models on your own servers or in a secure environment, rather than through public cloud services. All data remains within your organization. You own the infrastructure, the models, and the output, without any third parties having access to your data or using it for training.
For many business applications: yes. Open-source models such as Llama 4, Qwen 3, and DeepSeek-R1 perform comparably to proprietary models on tasks such as text generation, summarization, translation, and Q&A. The gap is rapidly narrowing.
That depends on the scale. For a small team, a powerful workstation with an NVIDIA GPU or an Apple Silicon Mac is sufficient. For larger organizations, we set up a dedicated server at a Dutch data center. We always provide recommendations based on your specific situation and budget.
A basic implementation starts at a one-time fee of €5,000, plus any hardware costs. Managed services start at €750 per month. We’ll provide a transparent estimate during a free introductory meeting.
Because all data processing takes place within your own environment, you have full control over GDPR compliance. There is no transfer of data to third countries. The EU AI Act sets requirements for transparency and human oversight: with Private AI, you can meet all these requirements because you have full control over the architecture.
Absolutely. Most organizations opt for a hybrid approach: sensitive tasks run on private infrastructure, while non-sensitive tasks are handled via cloud APIs. We’ll help you design your architecture so that data automatically follows the correct path.
A basic setup is operational within 2–3 weeks. A full implementation, including RAG, CRM integration, and agent functionality, takes 4–6 weeks. After that, we continuously optimize the system.
No. The end-user experience is similar to ChatGPT: a chat interface in your browser. The technical complexity is handled behind the scenes, and we manage that for you.
Schedule an introductory meeting and discover how Private AI can make your business safer, smarter, and more independent. No obligations, just immediate insights.
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