Private AI Inference: Secure, High-Throughput Model Serving
Private AI Inference is an enterprise-grade replacement for public AI APIs, designed to cap your variable costs and guarantee data sovereignty. We deploy a fully managed, high-performance inference engine directly onto your preferred compute (AWS, GCP, Azure, Verda, or Hetzner). You get a fixed monthly cost starting at €1,500 — with no per-token fees, no shared infrastructure, and absolute certainty that your proprietary data never leaves your network.
Why choose the Private AI Inference?
The OpenAI Tax
- Paying per-token fees
- Data leaves your network
- Surprise monthly bills
- Shared GPU latency
Private Cloud (Us)
- Fixed Monthly Cost
- Data stays in your VPC
- Dedicated BYOC or Hybrid GPUs
- No Per-Token Fees
What Does the AI Inference Platform Include?
We deploy natively on your preferred cloud (AWS, GCP, Azure) or establish a secure hybrid bridge to highly cost-effective EU bare-metal GPUs (Hetzner, Verda). You get guaranteed performance with zero shared resources.
We provide a fully managed, highly optimized inference stack designed for maximum throughput. It serves models like Llama 3 and Mistral at scale, without the operational headaches of managing the underlying infrastructure.
Your proprietary data never leaves your network. We enforce strict VPC isolation and end-to-end encryption, ensuring your AI workloads meet the highest enterprise compliance and GDPR standards.
What Are the Boundaries of the Service?
To keep this service affordable and sustainable, we adhere to strict boundaries. We run the platform; you run the code.
Our Responsibility (Infrastructure)
- GPU Infrastructure: We ensure the hardware is running.
- K8s & vLLM: We manage the inference engine.
- Security: We patch the OS and drivers.
- Scenario: ‘API is down’ -> We fix it.
Your Responsibility (Application)
- Model Selection: You choose the weights.
- Prompts: You write the system prompts.
- Application: You build the frontend/logic.
- Scenario: ‘Model is hallucinating’ -> You fix it.
How Much Does AI Inference Cost?
Plus $3,000 Setup Fee
- Up to 2 GPU Nodes managed.
- No Per-Token Fees — flat-rate pricing.
- OpenAI-compatible API.
- 24/7 Automated Monitoring.
- Strict Data Privacy & Control.
Have questions about our AI Inference service?
Can I run my app in AWS but use Hetzner/Verda for GPUs?
Yes. This is a very common hybrid architecture. We establish a secure, encrypted tunnel (e.g., Tailscale or Site-to-Site VPN) between your AWS VPC and the dedicated GPU servers. Your application stays in AWS, but routes inference requests securely to your private GPUs without traversing the public internet.
Which models can I run?
Any model supported by vLLM (Llama 3, Mistral, Gemma, etc.).
Can I scale up?
Yes. We can add nodes to your cluster in minutes.
What is the latency compared to OpenAI?
Often lower. Since you have dedicated GPUs, you don’t wait in a public queue. First-token-time is consistent.
Do you support LoRA adapters?
Yes. You can load multiple LoRA adapters on top of a base model at runtime.
What happens if the hardware fails?
We keep spare nodes on standby. If a GPU dies, we migrate your workload to a fresh node automatically.
Is it OpenAI compatible?
Yes. Just change your `base_url` and `api_key`.
Do you see my data?
No. Your data is processed on your dedicated hardware. We only monitor infrastructure metrics.
Can I run multiple models on one node?
Yes, if they fit in VRAM. We can partition the GPU or swap models in/out.
How secure is the connection?
We provide a private IP and mTLS certificates. Traffic is encrypted from your app to the inference server.
Can I bring my own container?
Yes. While we recommend our optimized vLLM stack, you can deploy any Docker container.
Reclaim your proprietary data. Deploy Private AI.
Stop sending your proprietary IP to external APIs and managed SaaS. We deploy high-throughput inference and stateful agents directly onto your own Bare-Metal or VPC infrastructure. Execute AI workloads with zero API taxes, zero hyperscaler lock-in, and absolute control over your data.
What other AI infrastructure products do we offer?
discovery Zoom. We’ll review your AI workloads, data flows, and current cloud setup, then give you a clear Go / No-Go recommendation. If private inference, agent runtimes, or managed data services make sense for your architecture, we’ll show you the next step. If not, we’ll tell you directly.
Interested? Contact us.
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