Every team is building with AI. Few companies can say which models are in use, who has access, or what it costs. In 60 minutes, see how a large, regulated multinational took control on Azure, live.
Our answer: make the governed path the easiest path.
Every team has a use case. Every use case needs a model, a key and a budget. A year in, the questions start:
If this sounds familiar, you are not behind. Each of these can be fixed once. Keeping them fixed while models, APIs and quotas keep changing is the hard part, and it takes a platform team most companies don’t have. Some choose to run it as a managed AI platform.
| Topic | Speaker |
|---|---|
| Why AI sprawl happens, and what it costs | Fabien Vettori |
| What good control looks like, for teams and for IT | David Mateus |
| Live demo: from request to first call | David Mateus |
| What changed at a regulated multinational | Paulo Moreira |
| Where to go from here: running governed AI as a managed AI platform | Fabien Vettori |
| Live Q&A | All speakers |
CIOs and Heads of IT · Heads of AI and data, AI CoE leads · CTOs and IT managers in growing companies · Enterprise architects · IT business partners.
Not sure it is for you? If AI projects in your company outnumber the people who can see them all, it is.
Ask the people who built it. Ten minutes of the hour are yours. Everyone who registers also receives the recording and a short solution brief afterwards.