Enterprise AI Architecture
Move from experiments toward secure, governed, operable AI systems with explicit architecture decisions and ownership.
Private training / Courses for teams
Private enterprise AI training for your team.
Bring one of Ardevant's practical enterprise AI architecture courses to your team. Anton can teach at your location or remotely, with the emphasis agreed around your team's goals.
01 / When this fits
A shared architecture language for your team
Private training gives colleagues practical exercises, a common decision-making method, and space to discuss the architecture questions that matter to them.
Agentic AI Architecture & Security
Design bounded agents, tool use, identity, permissions, memory, human control, and observable failure handling.
Custom architecture working session
Apply the same method to one agreed architecture question, decision, or roadmap without turning the session into an implementation project.
02 / How it works
At your location, with a scope that fits the team
Choose the Enterprise AI Architecture Bootcamp, Agentic AI Architecture & Security, or discuss a focused architecture working session. On-site delivery is the primary format, with remote delivery available when it suits the team better.
The initial focus is Switzerland, and requests from Germany and neighbouring countries are welcome. Participants, language, timing, location and fee are made clear in a written proposal.
Three simple steps
- Tell Anton what the team should learn or decide, the preferred location, and broad timing.
- Use a short conversation to confirm the right course, emphasis and delivery format.
- Receive a written proposal with the scope, timing and fee before you decide.
03 / Useful reading
Start with the architecture question
These practical articles show the methods behind the training and advisory work.
Enterprise AI architecture
Enterprise AI architecture: five layers and three control planes
A practical enterprise AI architecture framework covering five runtime layers, three control planes, and the questions that expose production gaps.
Agentic AI architecture
Bounded autonomy: an architecture contract for AI agents
A practical bounded-autonomy framework for AI agents: goals, scope, authority, budgets, invariants, stop conditions, and evidence before expansion.
04 / Start a conversation
Discuss a private course
Share the team objective, preferred location, and broad timing. A short non-confidential first message is enough.