Architecture and migration
Sizing, target environment, data transfer, cutover and recovery are resolved before production operations.

WZ-IT plans, installs and operates Ollama as managed hosting, in your cloud or on premises. Depending on the target design, we also provide migration, secure network and identity integration, monitoring, backups, updates, integrations and further development.
Companies worldwide trust WZ-IT

Ollama is the inference layer for local language models. Instead of sending company data to external AI services, models such as Llama, Mistral, Gemma or Qwen run on your own infrastructure.
We operate Ollama for production use: with GPU tuning, model management, API gateways, monitoring, backup strategy and clean integration into Open WebUI, AnythingLLM, RAG pipelines and internal applications.
Ollama is easy to start, but production operations need more than a Docker container. We plan hardware, model sizes, VRAM budget, access paths, updates and observability around your use case.
The software is licensed under MIT. That makes Ollama a strong open foundation for sovereign AI infrastructure, provided security, operations and model governance are handled properly.
Models can run on your own hardware, in your own data centre or in a European cloud. With exclusively local models and services, prompts and outputs can remain in controlled infrastructure.
We size VRAM, CPU, RAM and storage around model size, context window, user count and response-time requirements.
Clean handling of model versions, pull processes, approvals and rollbacks for reproducible AI environments.
On-premise, AI Cube, GPU server or private cloud: Ollama is operated so data protection, availability and access control fit together.
We connect Ollama to Open WebUI, AnythingLLM, LiteLLM, internal applications, automations and RAG pipelines.
Monitoring, updates, backups, model tests, security hardening and support turn a local demo into a reliable AI platform.
Ollama handles local model execution and forms the technical base for chat, RAG, agents and internal AI APIs.
We handle model changes, updates, GPU utilization, health checks and clear processes for production environments.
Access is provided through VPN, SSO, internal networks or API gateways. External models, integrations and update services are documented as separate data flows.
We do more than provide an application. WZ-IT designs the technical architecture, integrates network and identity, operates the agreed scope and develops integrations when the standard product is not enough.
Sizing, target environment, data transfer, cutover and recovery are resolved before production operations.
SSO, secure access, internal systems and existing security components are integrated appropriately.
Updates, backups, technical monitoring and response paths follow a transparent operational scope.
APIs, automation and custom extensions can be delivered beyond basic deployment.
The exact scope depends on the application, edition, infrastructure and criticality. Vendor licences and non-standard components are quoted separately.
AI applications need controlled model access, knowledge sources, permissions and observability in addition to the user interface. We design these data flows as one coherent stack.
Teams, business applications and API clients use defined interfaces and endpoints.
TLS, firewall rules, reverse proxies or private network paths are designed around the platform's exposure.
Local accounts, SSO, directories, service accounts and emergency access are connected through clear roles.
Application logic, model access, roles and approved capabilities run in a controlled environment.
Local or external models, GPU/CPU resources, routing, limits and cost controls.
Documents, databases, vector search and traceable data paths for RAG and search.
Reviewed tools, APIs, logging, metrics and technical quality controls.
Models, extensions and data sources are not enabled indiscriminately. Permissions, data exposure, cost and professional oversight are assessed per use case.
A clearly defined operating scope instead of an opaque hosting flat fee.
Compute, applications, storage and response are shown separately. You can see what ongoing operations include and which requirements need a technical assessment.
We also design custom Ollama architectures, integrations and migrations. Contact us for a technical assessment.
Select a technical starting point, additional storage and the required service level. We then validate the selection against the application, load profile, integrations and target architecture.
A workload is one compute instance with the applications agreed for it.
One standard app per workload is already included. Additional dedicated servers count as separate workloads.
Indicate additional storage for data, artifacts and backups.
Enquiry
Briefly describe the current state and objective for Ollama. We assess infrastructure, integration, and ongoing operations.
The AI Cube covers the compact entry point. For larger models, rackmount or high concurrency, we design custom GPU systems.
Powerful GPU servers with dedicated hardware for compute-intensive LLM workloads. Fully managed, scalable, and optimized for maximum performance.
Compact NVIDIA GB10-based local AI server. Fully configured, hardened and prepared with a local model agreed in advance.
25.08.2026
The question of the right inference server is almost always framed as a speed question and almost always answered wrongly, because one figure is missing:...
10.05.2026
Three unauthenticated API calls. No login, no exploit framework, no privilege escalation. Three POST requests to a default port, and the machine's memory is on...
24.11.2025
OpenAI released GPT-OSS 120B as an open-weight reasoning model on 5 August 2025. Its native MXFP4 quantisation allows OpenAI to position the model for a...
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Whether a specific IT challenge or just an idea - we look forward to the exchange. In a brief conversation, we'll evaluate together if and how your project fits with WZ-IT.