SEE IT IN ACTION
The Challenge
Before an architect makes a single decision on a new brief, they spend the first hour or two on setup: finding elements in the repository, checking connector types against the MDG, verifying package placement. The architectural thinking starts once the scaffolding is done.
Wrong connector stereotype. Missing tagged value on a mission-critical element. New dependency on a deprecated component. These get caught on Thursday afternoon, after the model was built on Monday. The rework costs two days and interrupts the next brief.
Diagram labels written for architects need rewriting for business readers. Ownership and criticality data in the model has to be manually cross-checked in the slides. A four-hour briefing preparation produces a thirty-minute meeting.
When you use AI Augmented Architecture for Solution Architecture
Paste a project brief into the Claude interface alongside Sparx EA. AI Power Tools for EA queries your repository, finds existing elements by name, creates new ones with the correct stereotypes, types the connectors to your MDG Quick Linker convention, lays out a diagram, and renders it back. Under five minutes for a working starting point an architect can evaluate and refine.
Before the model goes to review, run validation against your MDG and governance rules. Findings surface with the specific rule cited, a suggested fix, and a clear distinction between mechanical corrections and architectural decisions that need a senior reviewer. Mechanical errors get resolved before review. The review conversation is about the one finding that actually requires judgment.
Ask AI Power Tools for EA for a plain-language briefing on an initiative. It applies MDG-defined business aliases throughout, pulls ownership and criticality from tagged values, and generates a dependency summary from the actual repository data. Forty minutes instead of four hours.
When governance errors surface immediately with the rule cited, architects start checking for issues before asking for review. Standards internalize through the work rather than through Thursday afternoon feedback.
AI POWER TOOLS FOR ENTERPRISE ARCHITECT
86 tools. Full read/write access to your Sparx EA model. Seven-day free trial. No credit card required to start.
HOW TO GET STARTED
Understand your starting point
Get AI Power Tools for EA running
Build the habit across your team
FREQUENTLY ASKED QUESTIONS
Yes — but in a good way. AI Power Tools for EA is about teaching architects how to use AI to do their jobs more efficiently. Sparx EA stays exactly as it is. What changes is that architects learn to work alongside AI to handle the mechanics of modeling, so their time goes to the architectural decisions that actually require their judgment.
General-purpose AI tools have no knowledge of your Sparx EA repository, your MDG, or your governance rules. When they try to help with architecture modeling, they improvise from training data. AI Power Tools for EA connects directly to your running Sparx EA session and operates against your actual repository, your actual MDG, and your actual governance standards. The answers come from your models, not from guesses.
If you already have an MDG Technology defined, AI Power Tools for EA uses it directly. If you do not have one, AI Power Tools for EA can analyze your repository and walk you through a workflow to create a custom MDG Technology from what is already there.
For most architects, AI Power Tools for EA can be up and running in a few hours. What introduces delay is platform readiness. If your repository elements have only names and no supporting detail, if your modeling is inconsistent, or if you do not have modeling standards defined, there may be some iterations to get your AI-augmented modeling up to full power. That is exactly what the Plan engagement addresses.
Your architecture models sit in your repository — whether that is local model files on your computer or a shared DBMS repository. AI Power Tools for EA runs on top of your Enterprise Architect client and connects to your data using the same methods modelers use through the UI. Nothing leaves your environment through a separate channel.
That depends on which AI platform you use. This solution was designed to work with Claude Cowork and M365 Copilot Cowork, both of which are subscription-based at a fixed monthly cost. If you choose a token-based platform such as GitHub Copilot for VS Code, your costs will vary with usage. Bring this up on a discovery call and we will help you choose the right model for your environment.
Watch the four-minute demo, or schedule a call and we will walk through it against yours.
Schedule a Discovery Call