The situation
Enterprise AI proposals depend on more than a convincing use case. The assessments checked how each proposal fit the organisation's systems, and how ready it was.
The architecture contribution
Dimitar's experience includes evaluating AI opportunities, data and integration dependencies, architecture options and readiness considerations with business and technology leaders.
Why this experience matters
It shapes how we frame AI questions today: start from the decision, then test it against the real system.
The architecture lesson
Turn a broad AI ambition into a decision that can be tested against system evidence and operating constraints.
Assessment work by Dimitar Stoyanov before Sparkling was founded.
