Designing a closed-loop AI report-generation platform from scratch

Context

Multi-company, multi-country corporate structure (holding scale) · executive reporting

Problem

Data tracking the organisation’s external visibility existed, but no system turned it into reports top management would use. The need was not a fixed template but a closed-loop platform that produces any report requested in natural language, from in-system data only, with sources shown and an audit trail.

Approach

I built the design from product definition to target architecture: system boundary (what it does / does not do), single-admin user model, a data-processing layer with a 35-field master data schema (language, topic, sentiment, risk, reportability, QA status…), a prompt architecture on the “orchestrator + single-purpose module agents + report state object” principle, source/confidence/audit rules, PDF-PPTX-Excel-web export. I also wrote the business case presented to management, the data request document, the module guide, the roadmap and the budget plan.

Impact

A 10+ document end-to-end design package the software team could start building from; the principle “AI relies only on in-system data; no unsourced claim enters a report” sits at the core of the architecture. Project at corporate decision stage.