AI hosting · Managed AI infrastructure

Run your AI on European servers without paying for idle capacity

We host n8n, open models on Ollama or vLLM and your AI applications on VPS, dedicated or GPU servers, and run them securely. For companies that want control over their data and spend.

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30 minutes · free of charge · we'll be in touch to schedule

From improvised infrastructure to AI in production

Today
With HolaPolska!
Your n8n or Docker VPS runs out of memory, containers restart and automations fail without warning.
A team diagnoses, fixes and monitors the server, and you receive documentation and status reports.
Every month brings new charges for servers, APIs and GPUs you only use for a few hours.
We compare API and self-hosted options on total cost and size the infrastructure to your actual consumption.
Your AI agents can reach email, CRM and documents with no clear limits.
Per-action permissions, input and output validation, usage caps and human approval for sensitive actions.

What well-hosted AI gives you

Total cost (TCO)

API or your own server, by the numbers

With low or irregular usage, an API is usually cheaper; with high, sustained load, a self-hosted model can compete. We measure before you decide.

Data in the EU

Control over your data

We define where each piece of data is processed and stored, which providers are involved and when external APIs are used.

Open models

No dependence on a single platform

We deploy compatible models on Ollama or vLLM under their licences, and combine them with external APIs where they add value.

Deliverables

What you get

Everything is set out in writing in the proposal: scope, deliverables, owners and acceptance criteria.

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Proposal · AI hosting

  • Assessment and sizing Users, load, concurrency and response time, to choose between VPS, dedicated or GPU.
  • API versus own-server comparison Total cost of ownership for each option, using your real volumes.
  • Prepared, hardened server Operating system, Docker, certificates, firewall, access control and secrets management.
  • Managed n8n Installation, database, updates and protection of the credentials used in your workflows.
  • Deployed models Ollama or vLLM with the VRAM and concurrency suited to the model you choose.
  • Document search (RAG) PostgreSQL with pgvector so your AI can search your documents while respecting permissions.
  • AI-specific security Controls against prompt injection, least-privilege agents and usage caps.
  • Monitoring, backups and SLA Resource monitoring, tested restores and RPO and RTO defined per application.

How we work

How we move your AI onto managed infrastructure

  1. 01 30 min

    Assessment

    We review your systems, versions, resources, current costs and what you want AI to achieve.

  2. 02

    Design

    We decide whether to keep your server, move to a VPS, dedicated or GPU server, or combine them in a hybrid architecture.

  3. 03

    Preparation and migration

    We configure the infrastructure and move applications and data, with functional, security and recovery testing.

  4. 04

    Go-live

    A documented cutover and, for critical systems, a rollback plan in case anything fails.

  5. 05

    Ongoing management

    Monitoring, maintenance, usage reviews and extra capacity only when usage justifies it.

Who it is for

What we manage and what we don't

We manage the infrastructure, operating system and agreed services. The quality of a model's answers and your application code are separate matters: if you need development work, we scope it separately and in writing.

  • Companies with unstable n8n or DockerYou already have automations or a VPS, and managing them eats up hours.
  • Teams with rising AI billsYou pay for APIs, cloud and GPUs without knowing which part of the spend delivers value.
  • Companies wanting their own AIA private assistant or search across your documents, starting with a small project.
  • Bespoke software with AIERP, CRM or SaaS that needs a managed dedicated server and AI features.
  • Firms handling confidential dataStrict access control, encryption, audit logs and retention policies.

Frequently asked questions

Before you decide

Straight answers to the questions we are usually asked. If anything is still unclear, write to us.

They are different approaches. On a commercial platform you use the provider's models and infrastructure; here you get managed infrastructure for your applications, compatible models and integrations, with more control over the architecture and data. The two can be combined in a hybrid architecture.

It depends on what you run. For n8n, chatbots connected to an API or document search using external models, a managed VPS is usually enough. For demanding language models or many simultaneous requests, a GPU server makes sense.

Only in certain scenarios. With low or irregular usage the API usually wins; with continuous, predictable, high-volume processing, a self-hosted model can be competitive. We compare on total cost, including support, redundancy and maintenance.

It helps, but it is not enough on its own. What data you process, for what purpose, who has access and which safeguards you apply all matter too. We help you document the processing chain, the data processing agreement and sub-processors.

In many cases, yes. We assess its condition, fix configurations, strengthen security and take over its management without a full migration, if that is the most sensible route.

Want to dig deeper before deciding? Read the guide

Put your AI to work on a stable foundation

In 30 minutes we review what you already use, what you pay and what you want to achieve, and tell you which infrastructure makes sense. Free of charge, no commitment.

Book your free AI assessment