The starting point
Business challenge
Business analysts had to manually reconstruct requirements, decisions, contradictions, dependencies, and action items before they could prepare GAP-FIT conclusions, roadmaps, developer tasks, and test scenarios. Important context could be lost between discovery, presales, delivery, and support.
Alexander’s role
Work and solution
Alexander developed AI-assisted analysis workflows for processing transcripts and documents, extracting and grouping requirements by business process, identifying inconsistencies, separating business needs from proposed technical solutions, preparing preliminary scope, supporting GAP-FIT analysis, building implementation roadmaps, drafting developer tasks, and generating acceptance and test scenarios. He applied structured context, output schemas, validation rules, and human review so that AI accelerated analysis without replacing accountable solution decisions.
What changed
Project result
Unstructured discussions and source materials could be converted into consistent project artefacts more quickly, while Alexander retained architectural control over scope, priorities, risks, and acceptance criteria.
Business effect
What the work made possible
Shortened the transition from discovery to an actionable delivery plan, reduced repeated manual transcription and restructuring, improved continuity between commercial and technical teams, and lowered the risk that requirements or decisions would disappear during project handoffs.