Put it to work

Configure the Solution

Sparx Systems, Anthropic, Microsoft — they'll sell you the licenses you need. They won't assemble the solution in your environment or make sure the data foundation is there to do the work. We help you select and implement the best technologies for your needs, configure them to your Sparx EA, get the data ready, and define the process and governance changes to support where you're going.

Schedule a discovery call → Start with Paralysis to a Plan
What we do

We assemble the solution — you own the result

Buying software licenses is the easy part. Putting the pieces together into something that actually works, that's more challenging. The work that actually makes AI Augmented Architecture real is selecting the right approach, wiring it into your environment, and getting the data ready. We're technology-independent: our job is the best fit for you, not the sale of one product.

Select

The right technologies for your needs

Sparx gives you multiple paths to add AI — AI inside EA, a stakeholder and web layer, Claude, GitHub Copilot, Microsoft 365 Copilot, and more. We help you choose the combination that fits your architecture, your use cases, your policies, and your people.

Configure

Configured to your Sparx EA

We stand up the AI capabilities you chose and configure them to your repository, your metamodel, and your standards — so the first outputs reflect how your practice actually works, not generic defaults.

Data foundation

The data ready to work with

AI is only as good as the data underneath it. We assess and remediate — gaps, inconsistencies, duplication, unstructured content — and connect the enterprise sources your architects need.

How it works

  1. Confirm the approach. Start from the Plan findings: the AI option(s) selected, your Sparx EA version and repository type, your environment, and the constraints that shape the build.
  2. Configure and integrate. Stand up the chosen AI capabilities and connect them to your live Sparx EA — configured to your environment, your metamodel, and your standards.
  3. Set the data foundation. Assess and remediate the data, structure what's unstructured, and connect the enterprise sources the work depends on so answers are grounded in real data.
  4. Define the operating changes. Work with you to define the process, policy, and governance changes that support the new way of working — the operating model behind Outcome-Driven Architecture.
  5. Verify and hand over. End-to-end tests across your target use cases, plus documentation and a quick-start guide — a working practice your team can use immediately.

Get it working in your environment.

Then enabling the team take your architects from a working solution to confident daily use.

Talk with us →