We do not build AI demos. We build operable software: with data access, permissions, guardrails, monitoring and the right local or European infrastructure.
Answers from own data
Tool use with boundaries
Tracing, monitoring, operations
Leading companies worldwide trust WZ-IT
Many AI projects fail not because of the model, but because of integration, data access, permissions, quality assurance and operations. That is where our software and infrastructure experience meet.
AI accelerates development and processes. Our job is to turn that into maintainable, secure and operable software - not just prompts that look good in a demo.
AI becomes valuable when it is embedded into existing processes, portals and data flows. We build the application layer and operate the stack behind it.
Assistants for support, sales, operations or engineering - connected to your documents, APIs and permission models.
Documents, databases, wikis and business systems become searchable LLM context - with sources, access control and update processes.
Agents that can use tools: create tickets, check data, prepare drafts or trigger processes via APIs - with clear boundaries.
Add AI features directly into portals, dashboards, admin UIs and business apps instead of adding another separate tool.
Prompt versions, test sets, tracing and review flows so answers improve measurably and errors stay visible.
Tenant isolation, roles, PII reduction, rate limits and safe tool use - especially important for agents and internal data.
We deliberately separate experiment, productization and operations. This keeps AI fast enough for prototypes, but stable enough for real users.
Which task should AI really take over, which data does it need, and what must it never do?
No slideware demo stack: we test early with realistic documents, APIs and user roles.
Auth, permissions, logging, tests, tracing, UX and deployment become the actual software.
Monitoring, updates, cost control and model changes become part of ongoing operations.
Production AI needs evaluation, logging, cost control, updates, permissions and incident response. That is why we design AI applications with operations, monitoring and security from the start.
Answers about RAG, agents, local models and production operations.
Both. We add AI features to portals, dashboards, internal tools and existing software - and can also operate the matching infrastructure, from LiteLLM and Langfuse to local GPU servers.
RAG makes sense when answers should be grounded in your own documents, databases or APIs. Source attribution, permission checks, data updates and answer evaluation are essential.
Yes, but with control. An agent only receives the tools and permissions it actually needs. Critical actions can include review steps, approvals or audit logs.
Not always. Local AI makes sense for sensitive data, stable workloads, compliance requirements or cost control. For other use cases, a hybrid setup with local infrastructure and selected APIs may be better.
We treat AI as production software: versioning, tests, observability, rollback, access control and an operations concept are included from the start.
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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.
Leading companies trust WZ-IT
Timo Wevelsiep & Robin Zins
Managing Directors of WZ-IT
