ITQonnect Days & ITQon! 2026

An overview of how AVI enhances VKS and provides advanced Layer 4 and Layer 7 capabilities, including GSLB, Gateway API, ...

Building an AI proof of concept today is surprisingly easy. With the right tools and platforms, you can get something working in no time.

But turning that PoC into a production system is where the real work begins.

Suddenly, it’s about privacy, scalability, reliability, cost, and automation. Tools that worked fine in a prototype start to show their limits.

In this talk, I’ll walk through what to consider in that transition based on a ‘how-not-to’ and how to move from a quick demo to a robust, scalable AI solution.

In this short talk I'll show a small agent implementation and demystify the word "agent" from a technical angle.

There will be code, but there will also be thorough explanations!

We have seen or been there: an afternoon of vibecoding and you've got an app with an AI feature that actually impresses people. Then the real questions start. Where does the model run, and is it allowed to see that data? How does it reach our tools? Who stops it from saying something embarrassing to a customer? The one-day demo quietly turns into a quarter of platform work — while AI itself moves on weekly.

The ITQ AI Use Case Factory is built for that exact moment: the plumbing (models, tool access, retrieval, guardrails) solved once, on private infrastructure, so an app with Private AI features goes from laptop to production in a day, not a quarter. Internally first, then at our customers.

This talk is for you if you:

• build or vibecode apps and want your AI feature hosted, secured and used by real people — not stuck on your laptop
• sell, and keep hearing "great PoC, but how do we get this into production?"
• lead a team or the business and want a concrete picture of where AI at ITQ is heading

I will open the hood for an honest tour: what's inside, what we dropped, and what we'd build differently.

I want to talk about the differences between traditional (VMware) and cloud-native (Kubevirt) virtualization. In doing so, I want to show the WoW, the skills, the use case, and possibly the actual implementation. I especially want to give our VMware people a behind-the-scenes look, as this is often still a blind spot.

This is not a session to convince people of KubeVirt, but primarily to show how cool it is in a Cloud-Native environment.

Security and Compliance does not always require endless spreadsheets, PDFs, Docs and manual tasks.
In this session we explore how the MITRE Security Automation Framework (SAF) can support use cases which require a standardized, automated compliance pipeline. An approach to be able to scale with the infrastructure and remove human errors.

We will walk you through a use case auditing an environment which needs to fulfill special security requirements by extending VMware DISA STIG compliance checks.

You will be introduced to a framework built on open source tooling.

Your takeaways:
- Understanding of MITRE SAF
- How to extend existing STIG profiles
- A live demo of a framework built on open source toolsets