Full Data Sovereignty
All models, data, and logs remain in your data center – no cloud export, no data leaks.
Your AI, Your Rules – Behind the Firewall
CCNet implements your enterprise GPT on-premise – with full data sovereignty, zero-trust security, and seamless integration into your existing systems.
Your Enterprise GPT Behind the Firewall
With over 15 years of experience in cybersecurity and infrastructure projects, we have hardened the most complex corporate networks and seamlessly integrated system solutions. With CCNet On-Premise AI, you retain full data sovereignty, benefit from proven interfaces, and meet all EU AI Act requirements without compromise. Local language models run directly on your own infrastructure, behind the firewall, without data transfer to external clouds.
Five Steps to Your Own Enterprise GPT
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Requirements Analysis
Where do you want to position yourself with AI solutions in the medium and long term, and what do you need to achieve this?
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Infrastructure Analysis
Current state analysis of existing and required IT, OT, and IoT infrastructure.
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Define AI Architecture
Determine technology stack, interfaces, and software/hardware ecosystem.
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Pilot and Roadmap
Set up proof-of-concept, test, and create implementation plan.
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Lifecycle Management
Ensure commissioning, model management, and sustainable scaling.
Benefits for Your Company
Highest Security and Compliance
Zero-trust architecture, EU AI Act ready, and GDPR compliant – audit documentation provided.
Seamless System Integration
Out-of-the-box connectors for SAP, CRM, DMS, and more ensure smooth end-to-end workflows.
Maximum Performance and Availability
Low latency, dedicated resources, and continuous monitoring enable real-time responses and reliability.
Scaling Without Vendor Lock-in
Your on-premise architecture grows with your business – from PoC to enterprise cluster, completely vendor-independent.
15+ Years of Infrastructure Expertise
CCNet brings proven know-how from critical infrastructure and medium-sized enterprises to your AI project.
Frequently Asked Questions about On-Premise AI
Do I need to provide infrastructure?
No, the software and hardware ecosystem is selected together with you and installed on-site. We support you throughout the entire setup process.
How does a RAG system work?
RAG (Retrieval-Augmented Generation) combines a language model with your own knowledge base. This allows the model to access your internal documents, databases, and processes to deliver precise, context-aware responses.
How quickly can the system go live?
Depending on the package and complexity of your requirements, the system can go live in less than one to three months.
How does the system scale?
The on-premise architecture is designed for scaling from the start. You can upgrade anytime from a simple core setup without vendor lock-in or data migration.
Request On-Premise AI
Talk to our experts and learn how we implement your enterprise GPT.