Build

Get AI Power Tools for EA running, connected to your Sparx EA environment via MCP

Build configures and deploys AI Power Tools for EA on your architects' workstations. Skills Library loaded. Governance rules sidecar populated with your MDG standards. Reference repository extended or built. Connected to your running Sparx EA session via MCP.

The Challenge

Enterprise architecture teams face real friction

⚙️

Setup that does not fit your MDG

Generic AI tool configuration produces outputs that architects have to fix. Build aligns AI Power Tools for EA to your metamodel from the start, so outputs reflect your actual standards.

📋

Governance rules missing from the sidecar

Without your modeling standards in the governance rules sidecar, AI tools do not know what good looks like in your environment. They improvise, and architects spend time correcting the results.

🏗️

No reference architecture to work from

AI-assisted modeling works best from a reference architecture built from your own standards and patterns. Without one, every output needs correction. Build extends or builds your reference repository as part of deployment.

What you get

What's included

The process

How it works

  1. Environment review

    We confirm your AI platform, Sparx EA version, repository type, and technical environment against the Plan findings. This step catches any prerequisites that need to be in place before deployment begins.

  2. Installation and MCP configuration

    AI Power Tools for EA is installed on architects' workstations and connected to your Sparx EA repository via MCP. We configure the tool to your environment, not a generic default.

  3. Skills Library and rules sidecar setup

    We load your Skills Library into your AI platform and populate the governance rules sidecar with your MDG standards, connector types, and modeling conventions. This is what makes AI outputs match your architecture practice rather than generic patterns.

  4. Reference repository extension

    We build or extend your reference architecture to give AI tools the right starting point for your target scenario types. Architects building models get a governed foundation rather than a blank canvas.

  5. Verification and handover

    We run end-to-end tests across your target scenarios and hand over documentation, quick-start guides, and a verified, working deployment that your architects can start using immediately.

FAQ

Common questions about Build

AI Power Tools for EA is designed to work with Claude (via Anthropic's API or Claude Cowork) and Microsoft Copilot. Build configures the deployment for whichever platform your organization runs. We discuss platform choice during scoping.
Plan is the recommended starting point. It establishes that your repository and MDG are ready to support AI tools. If you already have a clear picture of your environment and readiness, Build can proceed without a formal Plan engagement.
MCP (Model Context Protocol) is the integration layer that connects AI tools to your running Sparx EA session. It gives AI tools direct read/write access to your actual repository (your elements, your MDG, your governance rules) rather than working from exported data or generic training. The quality of Build output depends on a correctly configured MCP connection.
We assess MDG readiness at the start of Build and flag gaps that need to be closed before deployment will deliver reliable results. If significant MDG work is needed, we scope that as part of Build or recommend it as a prerequisite.
Most Build engagements run three to six weeks. The main variable is reference repository scope. Extending an existing reference repository is faster than building one from scratch.
Train takes architects from a working installation to confident, consistent daily use. Structured coaching, individual mentoring, and Sparx Office Hours sessions build the habit across the team.

Ready to get AI Power Tools for EA running in your environment?

Schedule a discovery call and we will scope a Build engagement for your Sparx EA deployment.