Discovery and architecture for one agreed operating target
Development/staging and production environments, one runtime and GPU/compute integration
Model gateway, RAG foundation and vector store
One SSO integration, RBAC and secrets management
Logging, observability, IaC and a documented deployment process
Backup/recovery design, agreed restore test, runbooks and administrator training
Sovereign AI platform: one shared foundation for controllable AI applications
Every new AI application brings its own models, access and logs. We build a shared technical foundation in your target environment on which further applications grow in a controlled way.
Starting point
Every AI application brings its own technology
- Several AI applications are planned or running, each with its own model access
- Data and models should stay in an environment you control
- Sign-in, permissions and logs should apply uniformly to all applications
- Your IT should understand the platform after handover and be able to run it
Outcome
A platform on which new AI applications grow in a controlled way
New applications use the same models, the same sign-in and the same logging. Deployment and recovery are documented and tested with a reference workload.
Shared runtime
Test and production environment with one runtime, GPU or compute connection and a model gateway for all applications.Uniform access
One SSO integration, role-based permissions and secrets management instead of separate logins per application.Operations your IT can take over
Logging, observability, infrastructure as code, backup and recovery concept, runbooks and administrator training.
Priorities and target architecture still open? The AI architecture assessment settles both before the build.
View assessmentScope
What the platform covers
Architecture, test and production environments, model access, RAG foundation, identity, logging and a tested recovery concept.
Service boundary
Not included in the platform build
- Hardware, cloud/GPU consumption, HA clusters and 24/7 service
- Multiple applications, complex legacy migration and specialist adapters
Process
From architecture to an accepted platform
The operating target is set first, then the architecture. The build is reproducible, so every environment is created the same way and can be restored.
- 01
Set the operating target
Discovery on target environment, network, identity provider, security requirements and first application.
- 02
Approve the architecture
Describe runtime, model gateway, RAG foundation, permissions and logging and approve them together.
- 03
Build the platform
Provision environments as infrastructure as code and set up SSO, secrets and observability.
- 04
Test and hand over
Function, access and recovery test with a reference workload, runbooks and administrator training.
What we need from you
- A description of the operating target and the first intended application
- Details of the target environment, network, identity provider and security requirements
- A technical contact for infrastructure, operations and approvals
Scope and investment
Cost of a sovereign AI platform
Starting price for one operating target with a reference application. Further business applications, high availability or special adapters increase the scope.
Delivery starts once agreed data, access and stakeholders are available. The binding scope and price are defined in your proposal. Hardware, hosting, model consumption, licences and ongoing operations are quoted separately. Follow-on projects are costed against reusable results. We credit the pilot price when you commission the production rollout; there is no requirement to purchase every stage.
All prices are net and exclude statutory VAT. The offers are addressed to businesses.
Sovereign AI Platform Foundation
Build architecture, environments, model gateway, RAG foundation, SSO, logging and recovery concept as a shared foundation.
from €79,000excluding VAT and separately quoted third-party costs
8–12 weeks
Outcome and verification: Architecture approval, reproducible deployment and documented functional, access and recovery tests with a reference workload.
On the platform
Bringing applications onto the platform and running them
The platform is the foundation. Business applications and operations are commissioned individually and use the existing building blocks.
Internal AI Assistant
Introduce an internal knowledge assistant with sources, roles and permissions on the platform.
View offerAI Agents
Automate workflows with tools, permissions, approvals and logging.
View offerManaged LLMOps
Regularly evaluate answer quality, errors, latency and cost of the applications.
View offerFrequently asked questions about the sovereign AI platform
Definition, target environment, cost and operations
- An AI environment in which you decide where models run, where data is stored and who has access. It includes runtime and model access, a RAG foundation, identity and permissions, logging and an operating and recovery concept.
- New applications do not have to solve model access, sign-in, permissions and logging from scratch each time. Security requirements apply uniformly, and your IT runs one environment instead of several separate solutions.
- In the target environment agreed during discovery: in your own data centre, on your own hardware or on servers in German data centres. Hybrid setups are possible when data paths and access are clearly separated.
- No. Data sovereignty concerns where data is stored and who controls it. Sovereign AI also covers models, runtime, access and operations.
- The build costs from €79,000 excl. VAT for one operating target with a reference application. Hardware, cloud or GPU consumption, high availability and 24/7 service are not included and are quoted separately.
- Your IT receives runbooks and administrator training and can run the platform itself. Further applications and ongoing quality control via Managed LLMOps are agreed separately. With a clear scope, a direct start without a preceding assessment is possible.
Reviews & projects
What clients say about working with us
From a knowledge base with an AI assistant and local AI integration to data sovereignty and ongoing operations.
AI Platform
We were looking for a secure yet easy-to-use alternative to the large American providers and came across WZ-IT. WZ-IT advised us on choosing the right models and implemented the integration for us. Beforehand, we were able to try everything out calmly on a test instance. Today WZ-IT runs Open WebUI for us on our own domain, with a convenient Microsoft login and open-source models hosted by a German provider. Our team can now work productively with AI without resorting to external tools or shadow AI. Working together is straightforward, and questions are answered quickly and clearly. With WZ-IT we also have a partner at our side for further AI projects. (translated)
Carl-Frederic KornHead of E-Commerce & Online Marketing, Krüger Dirndl GmbH
Knowledge Management & AI
The knowledge from many years in the solar industry lived in the head of our former managing director, and it still lives in the heads of our employees today. We wanted to secure it, not as a folder full of notes, but in a way that lets us ask questions in daily work and get reliable answers. WZ-IT advised us from the start and weighed different approaches and knowledge management systems against each other with us before we decided. What was built is a custom knowledge base with an AI assistant that brings together conversations, notes, documentation and manuals: from the platform through onboarding our team to support in operation. Conversations are transcribed and facts are extracted; we review and correct everything ourselves before it is stored, because we do not want to trust an AI blindly. The system runs in our own environment, and the data stays with us. What surprised us was how efficient it was: WZ-IT used existing open-source software and extended it specifically for our requirements, instead of selling an expensive custom build from scratch, as is often usual with IT service providers. Timo and Robin understood our actual problem, preserving knowledge during the generational handover, and implemented it step by step: from the proof of concept through setup and validation with our own data to productive operation, explaining everything clearly along the way. Next, we want to extend this to the knowledge of our employees, so that this does not depend on individual people either.
Joshua von AmelnManaging Director, solarwerkstatt berlin GmbH
Read client reviews
International
Selected projects
- LiveRemote access platform for distributed water treatment plantsABCO Water Systems · Australia · Secure Access & OT
- 81%AWS migration with substantially lower operating costsEVA Real Estate · UAE · Cloud exit & infrastructure
- 98%Provision new sites in minutes instead of hoursnextGYM GmbH · Germany · Automation & IoT
WZ-IT designs, develops and operates infrastructure and software for clients in Germany and internationally. We deliver projects remotely and continue supporting them in ongoing operations after go-live.
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Tell us your target environment, identity provider, planned applications and security requirements.
