ON-PREMISE AI · HARDWARE, MODEL AND AGENT FROM ONE VENDOR
The zenpAI appliance brings hardware, a local model and agent orchestration together into one system that runs inside your own infrastructure. External dependencies, manual workarounds and scattered pilot projects come back in-house. Data sovereignty means something concrete here: you decide who has access, how processing happens, what gets logged and who operates it.
Public APIs are a rental agreement. Foreign jurisdiction, monthly notice period, and the infrastructure belongs to someone else.
Training data, process logic and internal company knowledge do not belong in someone else's operating environment. Data residency alone does not cover that. You need control over access, processing, models, logs and results.
Anyone can assemble the stack. The work is getting it into running production.
Buying GPUs is easy. It gets harder when they have to sit inside a regulated production environment that still respects GDPR, BSI baseline protection and your maintenance window. Most AI software is built for the cloud, not for your rack.
Consulting stops at the roadmap. We stay until the system is running.
Many AI projects end with a strategy, a prototype or a recommendation. We start there. What you get is a system running in your infrastructure, one your IT can take over, backed by maintenance, monitoring and operating documentation someone can actually read.
Every request is processed entirely on-premise. No data leaves your organization, no external interfaces, no cloud dependencies. That satisfies strict GDPR and BSI requirements and leaves control over sensitive information with you.
Most vendors deliver one layer: hardware, model or application. The value shows up once those layers work together, once the AI carries business processes and connects systems. We deliver hardware, local model and agent layer as one system that runs inside your infrastructure.
The agent layer is the conductor of the system. It decides whether a model, a tool or a specialized agent handles the next step, from a single RAG agent to several working in concert. Context is kept, systems stay connected, tasks run through reliably.
The same layer sets the guardrails for operations. Access, tool calls and relevant system actions are logged locally, error paths are defined, processes stay traceable. That is what makes the automation something an auditor can follow.
We pick the models to fit your data, processes and hardware requirements, tune them and run them locally. Embedding, reranking and specialized domain models run alongside the LLMs. Models and data stay in your hands. When a better model appears, the stack can be updated.
We deliver a GPU server sized for your use case, your user count and your operating requirements. It gets integrated into your existing IT infrastructure, with monitoring and support. The system runs under your control and belongs to you.
Sounds like your setup? Book an intro call
Many deliver components. The question is who brings them together.
| SOVEREIGN CLOUD | SYSTEMS HOUSE / INTEGRATOR | AI SOFTWARE STARTUP | ZENPAI | |
|---|---|---|---|---|
| Hardware · your rack | ||||
| Local model | ||||
| Agent layer / application | ||||
| System integration across all layers | ||||
| Operation after go-live Monitoring & Support |
The difference is who brings the layers together and stays responsible once the system is running.
You rent the cloud, and every request costs extra. The appliance you buy once. More usage costs nothing after that, and past the break-even the gap widens every year.
The biggest hidden on-premise cost is ongoing operations, not the hardware. We go through that openly in the intro call. By default we hand everything over to your IT, and we support you optionally on request. When the appliance pays off depends on how intensively you use it, with a typical break-even of 1.5 to 3 years. We build the exact calculation from your real volumes, methodology based in part on Lenovo Press LP2368.
We look at your infrastructure together and tell you honestly whether zenpAI fits. A technical assessment, not a sales pitch. You decide the next step.