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Case Studies

Representative diagnostic patterns for industrial buying committees.

These anonymized operating patterns show how AI2COE converts catalog disorder into CFO, procurement, operations, CIO, and governance decisions. They are proof-of-structure examples, not customer endorsements.

Enterprise trust posture

Proof controls buyers expect before they upload operational data.

Source purge Uploaded catalog files are deleted after report generation; only summary metrics and Open Findings remain.
No ERP write-back The diagnostic creates evidence for review. It never changes, deletes, merges, or overwrites ERP records.
Local currency Reports display money in the user's selected or country-derived currency, while USD remains the base audit calculation.
Audit trail Report ownership, access, quota, and feedback events are retained for governed review.
Session downloads Excel, Word, PDF, and CSV downloads are available only in the active generation session.
Open Findings Browser findings remain available without retaining the original source catalog rows.
Representative evidence library

How different industrial buyers would interpret the same diagnostic evidence.

How to read these pages

They show the decision pattern, not confidential customer data.

AI2COE is still building its public evidence base. Until named customer approvals are available, these pages use anonymized, representative diagnostic patterns that mirror realistic industrial catalog conditions: multi-site ERP history, inconsistent descriptions, supplier aliases, duplicate families, and role-specific governance needs.

Evidence boundary: Public case-study pages should never imply a named customer result unless the customer has approved publication. Live reports replace these patterns with uploaded-data findings.
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