AI Augmented Solution Architecture
Solution architecture is where the brief meets the standard. The real work isn't scaffolding a model from scratch — it's getting the design right and proving it conforms before anyone builds from it. We work alongside your team to make AI carry the mechanical legwork, so your architects spend their judgment on the design and your delivery teams get a model they can trust.
More solutions, without cutting the thinking
A solution architect's value is in the design judgment — fitting the right approach to the business need and tracing it through. The bottleneck is everything around it: gathering requirements and context, transcribing the design into the model, and hand-linking it back to business and components. Hand that to AI and your architects produce more designs without thinning the thinking that makes them good.
- The architect personally gathers the requirements and context before any design starts
- The design is transcribed into the model element by element, connector by connector
- Traceability to business drivers and components built up by hand, when there's time at all
- Most of the week goes to scaffolding and producing artifacts — not deciding
- AI carries the requirements and context legwork; the architect starts from a working model
- The design lands in the model already stereotyped and typed to your MDG convention
- Impact analysis and traceability across the real dependency graph in minutes, with the evidence attached
- The architect's time shifts to trade-offs, decisions, and stakeholder conversations
Delivery is asking for more, faster
Delivery keeps asking for more solutions, sooner, with conformance intact — and a hand-built practice can only stretch so far before quality slips. Every brief worked end to end by hand is capacity spent once. Augmenting the work lets the team meet the demand without trading away rigor or burning people out.
- Reclaim your architects' capacityMost of a solution architect's week goes to gathering context and transcribing the design into the model. Give that time back and one architect covers what used to take a team — the "more outcomes with the same people" leadership is asking for.
- Decide on evidence, not memoryA solution call carries real risk: a missed dependency is a failed delivery or a downstream outage. Impact analysis across the real graph, with the evidence attached, makes those decisions defensible — and right more often.
- Answer at the speed of the business"What does this change touch, and will it conform?" drops from a multi-day study to a same-meeting answer. Architecture becomes live decision support, not a review-day gate.
- Raise architecture's standingConformant models delivery teams can actually build from change how the business sees the function — from one that slows projects down to one that helps them ship right the first time.
Where AI lands in solution work
The same four use cases behind AI Augmented Architecture — each one has a specific, high-value shape in a solution practice.
Turn the brief into the model
Point the AI at a project brief and your live repository. It finds existing elements, creates new ones with the correct stereotypes, types connectors to your MDG convention, and lays out a diagram — a working solution model to refine, not an empty package to populate by hand.
Trace the impact before you commit
Ask the repository the questions a solution decision turns on — what this change touches, where the dependencies run, what breaks downstream — by walking the real dependency graph enterprise-wide, in minutes rather than over weeks of manual tracing.
Conformance as you build
Run validation against your MDG and governance rules before the model nears review — wrong connector stereotype, missing tagged value, a dependency on a deprecated component — caught at creation time, with the rule cited and mechanical fixes separated from the calls that need a reviewer.
Brief from the model
Generate a plain-language briefing on the solution — business aliases applied, ownership and criticality pulled from tagged values, dependencies summarized from the actual repository data — so the briefing reflects what was built, not a slide rewritten from memory.
"To use AI agents effectively, you have to know how to do the job. The agents are tools for someone who already understands the discipline. They amplify expertise. They don't manufacture it."
— Ryan Schmierer, The Value Shift
The architect still owns the design
AI can confirm a solution model is complete and conformant — every required tagged value present, every connector typed, every rule satisfied. It cannot tell you whether the model is correct: whether this is the right design for the problem, whether the trade-offs serve the business, whether the dependency it can't see was simply never captured. That gap is exactly the architect's job: the translator between what the business actually needs and what the IT estate actually does. AI makes your team faster at the build and the check; it does not make the design decision, and it does not own the consequences. Tasks get assigned; problems get owned — and a solution is a problem you own.
A consulting and mentoring engagement, on your repository
Not a course — we work the discipline alongside your architects, in your environment, and leave the capability with your team.
Start where you are
We look at your repository and MDG standards, fix the foundation where it needs it, and pick the use cases with the most immediate impact for your solution work.
Build the real solution
We run the use cases on a live brief — brief to conformant model, dependency and impact analysis, and the governance check happening as you go — producing a design backed by evidence, not an empty package and a Thursday review.
Leave the capability behind
We mentor your architects so the way of working sticks — compounding productivity and better solution outcomes long after the engagement ends.
Make your briefs become conformant models.
A conversation first — we'll look at how your solution architecture work runs today and what AI Augmented Solution Architecture would actually change for your team.
Talk to us →