Enterprise architecture generates a considerable amount of data: applications, dependencies, flows, capabilities, risks. For a long time, that data stayed hard to use — frozen in repositories nobody consulted between architecture committees.

The problem with bolt-on AI

Most platforms on the market added AI recently, as isolated features: an assistant here, a suggestion there. The problem is that this AI stays disconnected from the underlying data model. It answers generic questions but doesn’t truly understand your application landscape.

What native integration changes

At EA-Wizard, AI isn’t a layer on top. It’s wired directly into the dependency graph, the application portfolio and the roadmap. Concretely, that enables three things:

  • Risk analysis automatically identifies the critical components of your landscape, where fragility would have the most impact.
  • Blast radius measures the real propagation of a change before you even decide on it.
  • Modernization recommendations are contextual: they account for the real state of your architecture, not generic best practices.

Architecture data becomes decision

That’s the real point: turning a static map into a living decision tool. Native AI gives architecture teams the leverage to act fast and well — on every module, with full granularity: each AI service can be turned on or off per tenant and per context. For organizations that need absolute sovereignty, air-gap Ollama mode runs AI entirely inside your infrastructure — no architecture data ever leaves your perimeter.