AI solutions for business: from pilot to production
Many AI projects in mid-sized companies end as a demo: the data must not go to the cloud, the pilot has no path into production, and nobody owns it afterwards. WZ-IT takes AI projects from the first assessment to ongoing operations, in your own network or in German data centres.
- Four stages, each bookable on its own
- Local, dedicated or hybrid
- Open open-source stack
The Problem
Why AI projects in mid-sized companies get stuck
Three patterns that one more tool rarely solves.
The data must not go to the cloud
Contracts, customer data and internal knowledge sit across documents, wikis, tickets and business systems. Cloud AI is not an option for them, so AI stays forbidden or is used without rules.
The pilot has no path into production
A prototype impresses in the demo but sits next to the processes. Roles, sources, permissions and the connection to portals and workflows were never planned in.
Nobody operates it
After the project there is no monitoring, no updates, no cost control and nobody responsible for answer quality and model changes.
Our Approach
From AI Opportunity Check to operations: four stages
Each stage can be commissioned on its own and ends with a verifiable result. A well-founded no is a result too. You start where your project stands. All prices are net and exclude statutory VAT. The offers are addressed to businesses.
AI Opportunity Check
One process with its data, systems and risks is assessed. You receive a reasoned decision and a pilot plan.
from €3,900 excl. VATView the Opportunity Check Stage 2RAG Proof of Value or pilot
A defined knowledge base or workflow is tested with real data and agreed reference cases. It ends with a quality report and a recommendation to expand or stop.
from €9,900 excl. VATView the Proof of Value Stage 3Go into production
Assistant, agent or workflow run in day-to-day work with permissions, integrations and approvals, on the AI Cube, a dedicated GPU or your platform.
Knowledge assistant from €34,900 excl. VATView the knowledge assistant Stage 4Operations
Servers, runtime and models are maintained; answer quality, cost and changes are checked continuously. Operations by WZ-IT are optional.
LLMOps from €1,990 excl. VAT / monthView LLMOpsSignpost
Which AI solution fits your situation?
Six starting points we see again and again in AI projects. Each one leads to the offers built for it.
Find the right process
We do not know where AI would genuinely help us.
Assess one recurring workflow with its data, systems and risks, then decide: AI, conventional automation or a deliberate no.
Make knowledge usable with sources
The knowledge exists, but nobody finds the right passage.
Make documents, manuals and expertise searchable, with citations and permissions that apply before retrieval.
Automate recurring work
Orders, documents and requests are retyped by hand.
Capture incoming items, check them against master data and hand reviewable drafts to ERP, CRM, accounting or ticketing.
Integrate AI into software and agents
AI should take action or be built into our own software.
Agents with reviewed permissions, AI features in existing software and AI-generated applications that need to go into production.
Run AI locally or on a dedicated GPU
Our data must not go to a cloud AI service.
Run models in your own network or on a dedicated GPU in a German data centre, without passing data to model providers.
Hand over operations and quality
The AI is running, but nobody owns operations and quality.
Have servers, runtime and models maintained, keep checking answer quality, cost and changes, and consolidate several applications on one platform.
Start locally without a project: the AI Cube is the prepared AI platform for your own network, with chat, local models and knowledge spaces in Open WebUI. Device: from €6,490 excl. VAT one-time.
Expertise & operations
Private AI for your business: an open stack that belongs to you
We plan application, knowledge, inference and operations together so that the pilot becomes a system. WZ-IT runs cloud, open-source and software stacks in production, and that operations experience goes into every AI project. The systems run on your hardware, on the AI Cube or on WZ-IT infrastructure in German data centres.
Application
Prompt and model versions traceable, quality measured via evaluations
- Open WebUI
- AnythingLLM
- n8n
Knowledge
RAG indexes kept current, LLM traces and data flows auditable; monitoring, updates, backups and security as part of the architecture
- Qdrant
Inference
Open stack built from open-source components, models chosen by use case, data protection and load. Model switches and API fallbacks planned in from the start, cost control per team, user or application
- Ollama
- vLLM
- LiteLLM
Operations
Handover with infrastructure as code, runbooks, documentation and training; self-takeover is a documented path
- Langfuse
Reviews & projects
What clients say about working with us
From local AI integration to architecture, data sovereignty and ongoing operations.
WZ-IT moved our studio infrastructure from decentralised individual devices to a central platform: every site is securely connected via VPN, new devices are onboarded automatically and an entire site is provisioned from a template, without manual steps on location. What impressed me most is the breadth and depth of their knowledge: Timo and Robin are not a typical IT provider who sets up a server and leaves. The two of them think their way into highly complex infrastructure and software topics, work through every requirement we put in front of them, and build networking, provisioning and operations so that everything fits together in the end. WZ-IT is an excellent partner for complex software, network and architecture projects.
Steve KirchnerManaging Director, nextGYM GmbH
International
Built in Germany's Ruhr Valley. Running worldwide.
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.
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
Read client reviews
- Integrate a local AI solution
- Modernize your infrastructure - sovereign
- Design an open-source AI architecture
- Plan a sovereign open-source stack
- Secure your Proxmox & backup setup
- Modernize your legacy software
- Cut cloud cost - up to −81%
- Build a high-availability Proxmox cluster
- Virtualize with Managed Proxmox
- Get collaboration fully managed
- Ship your prototype to production
- Connect sites and clusters securely
Knowledge base
In-depth guides on this topic
Guides
Related tutorials & guides
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Frequently asked questions about AI solutions for business
Answers to the most important questions
- It depends on the stage. The AI Opportunity Check costs from €3,900 excl. VAT, a RAG Proof of Value from €9,900 excl. VAT and a production knowledge assistant from €34,900 excl. VAT. Ongoing quality control with Managed LLMOps costs from €1,990 excl. VAT / month. Hardware, hosting, model usage and licences are shown separately.
- Assessment, validation, production applications, platforms and operations each have their own scope. Start where your project stands today. If one recurring process is the topic, the AI Opportunity Check comes first; if existing knowledge should become usable, a RAG Proof of Value. Both end with a verifiable result and a recommendation for the next step.
- Recurring workflows with emails, documents, validation rules and clear target systems are often suitable. Examples include document processing, order entry, ticket and inbox automation, and custom workflows. The AI Opportunity Check first determines whether AI, fixed rules or conventional automation fit.
- Document processing extracts and validates data from different inputs. Automated order entry processes incoming customer orders for ERP or CRM. The quotation assistant instead uses your product and historic data to prepare new outgoing quotation drafts.
- Retrieval-augmented generation connects the language model with your documents: before each answer, relevant passages are retrieved and provided. The system answers with your knowledge without training a model, and permissions can be enforced technically before the search, not just in the prompt.
- Local or dedicated model operation makes sense where data paths, model choice, latency or running costs have particular requirements. Not every use case needs dedicated GPUs: the relevant factors are data protection, latency, cost, model size, concurrency and who is responsible for operations. We size the stack, local, dedicated or hybrid, to the risk and workload.
- Managed GPU Server provides a dedicated GPU in a German data centre with an agreed model and inference runtime. AI server maintenance & operations takes over existing AI infrastructure such as GPU, operating system, drivers, containers and inference runtime. Managed LLMOps covers the application above it: traces, quality, retrieval, cost, latency and changes to models, prompts or knowledge sources.
- No. Local operation can constrain data paths and improve technical control. Purpose, legal basis, user rights, deletion, human oversight and the applicable risk framework still need to be assessed and documented for the concrete use case.
Enquiry
Request a technical assessment of your AI project
Describe the objective, data, and existing systems. We assess the solution, infrastructure, and next step.
- Straight with Timo and Robin - no sales team, no pitch
- An honest take, including when we are not the right fit
- Concrete next steps for infrastructure, software or AI
No risk: worst case, you leave with a clearer understanding of your project than before.
WZ-IT's advice on our Azure migration was technically sound and completely non-binding right from the intro call - we took away a great deal.
Jakob ÖschlbergerInno7 GmbH
WZ-IT's advice on our Azure migration was technically sound and completely non-binding right from the intro call - we took away a great deal.