Private AI Architecture: AI Models on Your Own Infrastructure
Your company data never leaves your environment. AI runs on your infrastructure, controllable, auditable, and GDPR-compliant.
Every time an employee enters business data into ChatGPT or Copilot, that content leaves your company. GDPR and internal compliance policies often forbid this. Private AI solves the problem at the source: AI models run on your infrastructure, and your data stays under your control.
The most common challenges
Employees use AI tools with company data without authorization
The search for productivity gains is real, and employees use tools regardless of policy. Without your own AI infrastructure, the result is uncontrolled data leakage to third parties.
Public cloud AI creates regulatory risks
For financial institutions, healthcare providers, and other regulated industries, sending personal data to OpenAI or Azure Cognitive Services is a major compliance risk.
Public models lack your specific context
If you need specialized domain knowledge, industry terminology, internal processes, proprietary data, generic public models won't cut it.
The CCsolutions approach
CCsolutions builds Private AI architectures based on Kubernetes: open-source models (Llama 3, Mistral) run on GPU-enabled nodes in your infrastructure. The API layer is OpenAI-compatible, existing integrations work without code changes.
Optionally, models can be linked to internal knowledge bases via RAG (Retrieval-Augmented Generation). The result is an AI that knows your industry, your products, and your context, without exporting data.
All processing remains within your infrastructure. No third party ever sees your queries, documents, or responses.
Technologies
Frequently asked questions
Which models run as Private AI?
Llama 3, Mistral, Mixtral, and other open-source models. The choice is based on the use case and available hardware.
Do we need our own GPUs?
Not necessarily. For many use cases, CPU-based deployments with quantized models are sufficient. For high throughput, we recommend dedicated GPU nodes or on-premises clusters.
How does this differ from Azure OpenAI Service?
Azure OpenAI processes data on Microsoft's infrastructure. Private AI processes everything on your own, no third party involved, no data processing agreements needed.
Ready to get started?
We analyse your situation for free and show what is possible in your specific case.
Request AI Assessment