LLMOps Competence Center Finland

Deploy, scale, and operate Large Language Models on European cloud infrastructure. We combine deep Kubernetes expertise with platform engineering to run your LLM workloads on APPUiO, OpenShift, enterprise private cloud, or sovereign cloud infrastructure — reliably, securely, and with full data residency.

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Kubernetes-Native LLM Hosting

Deploy and scale LLM workloads on Kubernetes and OpenShift, on public and private cloud. We provide production-grade platforms tuned for AI inference and training, with automated scaling, namespace isolation, and resource quotas to keep your models running efficiently alongside other workloads.

Model Serving Infrastructure

Run production-ready model serving with autoscaling, load balancing, and GPU scheduling. Whether you serve open-source models like Llama or Mistral, or integrate with commercial APIs, we engineer the infrastructure layer so your data science team can focus on model quality rather than operational overhead.

Vector Database Integration

Build retrieval-augmented generation pipelines with managed vector stores running alongside Application Catalog databases. PostgreSQL with pgvector, dedicated search indices, and automated backups — all operated on European infrastructure with SLA guarantees for your managed services.

Sovereign Cloud Ready

Run LLM workloads on sovereign cloud partners that guarantee full data sovereignty and regulatory compliance. We operate across European sovereign cloud providers, ensuring your models and training data never leave trusted jurisdictions — critical for financial services, healthcare, and government use cases.

European Data Residency

LLM inference, training data, and vector embeddings stay in European data centres. We operate on Exoscale, cloudscale.ch, and other European cloud providers, ensuring full GDPR compliance and data residency for organisations that cannot afford to send sensitive data to hyperscaler regions outside Europe.

Observability and Cost Control

Monitor latency, throughput, token usage, and infrastructure costs across your entire LLM fleet. We integrate Prometheus, Grafana, and custom dashboards into your platform so you always know what your models cost to run, where bottlenecks are, and when to scale up or down.

Frequently Asked Questions

What platforms do you support for LLM workloads?
We deploy and operate LLM workloads on APPUiO (a managed Kubernetes platform), Red Hat OpenShift, enterprise private cloud infrastructure, and sovereign cloud partners. All platforms run on European data centres and are backed by a 99.9% uptime SLA. We help you choose the right platform based on your compliance, performance, and budget requirements.
Which cloud providers are available for LLM hosting?
We operate on multiple European cloud providers including Exoscale and cloudscale.ch, as well as European sovereign cloud partners. For organisations that need GPU-accelerated workloads, we work with providers offering GPU instances in European data centres on public and private cloud. All infrastructure is managed under a single SLA with 24/7 support from our operations team.
How do you handle GPU scheduling and scaling?
We configure Kubernetes GPU scheduling with NVIDIA device plugins, resource quotas, and pod priority classes so your inference workloads get the GPU time they need. Horizontal pod autoscaling adjusts replica counts based on request queue depth or latency targets. For batch training jobs, we set up preemptible scheduling to optimise cost without blocking interactive inference.
What is the pricing model for managed LLM infrastructure?
Pricing depends on your platform choice and resource requirements. A typical starting point for a managed Kubernetes namespace with GPU access begins at CHF 2,500 per month, including 24/7 operations, monitoring, and backup. Storage for vector databases and model artefacts is billed separately starting at CHF 0.09 per GB per month. Contact us for a tailored quote based on your workload.
Can you manage vector databases for RAG pipelines?
Yes. We operate PostgreSQL with the pgvector extension as a fully managed service through the Application Catalog. You get automated daily backups with up to 720 GB of backup storage, point-in-time recovery, high-availability replicas, and the same 99.9% SLA as all our managed database services. We also support dedicated search indices for hybrid retrieval workflows.
How do you ensure data sovereignty for LLM workloads?
All infrastructure runs in European data centres operated by European sovereign cloud providers. Training data, model weights, vector embeddings, and inference logs never leave the chosen jurisdiction. We guarantee that all operational access is from European-based engineers, and we provide audit trails for compliance reporting.
Do you support open-source and commercial LLM models?
We support both. For open-source models such as Llama, Mistral, and Falcon, we provide Kubernetes-native serving infrastructure with vLLM or Triton Inference Server. For commercial APIs like Anthropic Claude or OpenAI, we help integrate them into your application architecture while ensuring European data residency for prompts and responses through API gateway configurations hosted in European data centres.
What monitoring and observability do you provide for LLM workloads?
We integrate Prometheus and Grafana into every managed platform, with custom dashboards for LLM-specific metrics: inference latency (p50, p95, p99), tokens per second, GPU utilisation, queue depth, and estimated cost per request. Alerting rules notify your team and our 24/7 operations centre when metrics breach thresholds, so performance issues are caught before they affect users.
How do I get started with LLMOps services?
Contact us through the form below or email aarno@aukia.com for an initial consultation. We assess your current LLM workloads, platform requirements, and compliance constraints, then propose an architecture running on APPUiO, OpenShift, or your preferred infrastructure. Most customers go from initial consultation to a running production platform in four to six weeks.

Get in touch

Ready to run your LLM workloads on European infrastructure? Contact us for a free initial consultation. We assess your requirements and propose a platform architecture tailored to your models, compliance needs, and budget.