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The Challenge
The application inventory is built from surveys. Fourteen surveys go out, eleven come back, three come back incomplete. The migration team consolidates responses into a spreadsheet. Duplicates are reconciled. The spreadsheet becomes the current-state picture. Only then does the actual analysis start — at week six, on data that was already aging at week one.
Dependencies drive sequencing, but the dependency data in the surveys is whatever application owners recalled. Wave groupings are built in review workshops. Someone remembers a dependency that was not in the inventory. The plan is revised. The steering committee gets an updated draft. The real dependencies surface as blockers mid-wave.
The migration spreadsheet and the Sparx EA model both describe the application portfolio. They are built at different times, from different sources, and maintained separately. Every update to one requires manual reconciliation with the other. The gap grows throughout the migration program.
When you use AI Augmented Architecture for Cloud Migration Planning
AI Power Tools for EA runs aggregate_portfolio against your existing Sparx EA repository: lifecycle stage distribution, technology platform groupings, business domain assignments, ownership coverage. It runs find_orphan_elements to surface applications with no connector relationships — the applications that would have been missed in any survey. The readiness profile is ready before the first discovery meeting.
AI Power Tools for EA walks the full dependency topology for every application in scope. Applications that share dependencies group together. High fan-in applications get scheduled in earlier waves so they do not block what comes after. The rationale for every grouping is explicit in the output: which dependency relationships produced which grouping, which applications are high fan-in and why, which deprecated downstream dependencies require pre-migration decisions.
The dependency walk identifies applications that depend on platforms with a Deprecated lifecycle status. Each flag carries an explicit note: this is a pre-migration decision, not a mechanical fix. The options are stated. The program office and the architect make the call with full information before the wave is in flight.
Ask AI Power Tools for EA for the steering-committee version: business language throughout, per-wave summary, deprecated-dependency callouts, embedded diagrams. The document is produced from the current model state. The rationale is on every grouping. When a board member asks why an application is in wave two and not wave one, the answer is in the document.
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
No. AI Power Tools for EA reads the Sparx EA model and produces a wave plan grounded in the architecture. If your migration program uses a separate inventory spreadsheet, AI Power Tools for EA does not replace it — it gives you an architecture-grounded basis to validate and update it. Over time, the goal is to reduce reliance on the separate spreadsheet by keeping the EA model current.
Yes. No model is complete. AI Power Tools for EA's orphan detection and dependency walk surface the specific gaps that affect wave planning. The readiness profile tells you exactly what is missing and where. That is a better starting point than a survey inventory, which has the same gaps but does not make them visible until a wave is blocked.
Azure Migrate and AI Power Tools for EA address different parts of the migration picture. Azure Migrate handles cloud-side readiness: server discovery, infrastructure dependency mapping, migration tracking. AI Power Tools for EA handles the architecture-model side: logical dependency relationships, lifecycle metadata, business domain assignments, orphan detection. Both inputs belong in the wave plan. They are complementary.
For an organization mid-migration, the most valuable immediate use is auditing the current wave plan against the current model. get_updates_in_range surfaces changes to the model since a given date. That analysis tells you specifically where the current wave plan has diverged from the current architecture — which is exactly the information needed to decide whether to course-correct before the next wave.
Your architecture models sit in your repository — whether local model files 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. No data is retained between sessions. Nothing leaves your environment through a separate channel.
Watch the four-minute demo, or schedule a call and we will walk through it against yours.
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