Works from CSV or workbook exports produced from SAP, IBM Maximo, Oracle ERP, Hexagon EAM, Infor, and other ERP, EAM, or CMMS systems. No direct integration or write-back is required — Review data requirements →
Methodology Provenance

How AI2COE separates benchmark assumptions from diagnostic evidence.

A serious industrial AI product must make its evidence boundaries clear: what is benchmarked, what is calculated from uploaded data, what is retained, and what still requires owner review.

BenchmarksAssumptions labelled
EvidenceGenerated from data
GovernanceReview before action
Evidence summary

Buyer evidence resource

AI2COE Methodology Provenance: Use this page to understand the operating question, exported-data evidence path, review boundary, and next Industrial IQ action. Understand AI2COE methodology provenance, source assumptions, benchmark limits, reviewer discipline, and governance boundaries for diagnostic reports.

Run Free Industrial IQ Snapshot
Review ownerExecutive sponsors, operating leaders, finance reviewers, procurement teams, maintenance owners, ERP/data leaders, and governance reviewers who need evidence before approving action.
Input file contextOperational CSV exports, item master fields, inventory, procurement, asset, work-order, finance, readiness, or governance data depending on the page.
Diagnostic evidenceSource-backed evidence, scores, confidence tiers, report outputs, action tracking, score history, and governance context.
Recommended actionRun Free Industrial IQ Snapshot and select the diagnostic engine that matches the operating question.
Evidence layerHow it is producedGovernance control
Benchmark rangesPublished as planning assumptions until replaced by uploaded-data evidence.Shown visibly in public pages and report notes.
Diagnostic evidenceGenerated from CSV uploads using the PartsCleanse AI engine.Source file purged after generation; Open Findings and summary metrics retained.
False-positive controlCritical discriminator classes reduce unsafe part consolidation.Methodology page explains size, material, pressure, model, category, UOM, and subtype controls.
Review disciplineFindings are decision-support evidence, not automatic ERP instructions.Reports separate confidence tiers and preserve owner review requirements.
Authoritative report posture

AI2COE reports should read like board-ready diagnostic evidence, not raw software output.

Public pages use planning ranges to educate the market. Diagnostic reports use uploaded catalog data to compute source-backed SKU count, duplicate groups, duplicate-rate signals, exposure, and confidence-tier interpretation.

That distinction is important because enterprise buyers must defend decisions after the report leaves the portal. A planning assumption can justify investigation; a diagnostic finding can justify review; only owner-approved remediation can justify ERP change. AI2COE keeps those boundaries visible across pages, reports, emails, and methodology notes.

Limits disclosed
No automatic ERP changeClient owners remain accountable for final disposition
Source-file purgeUploaded source files are purged after report generation
Planning values are assumptionsFinancial interpretation depends on uploaded data and governed remediation
Audit trail expectation

Every claim should be traceable to a source layer.

AI2COE content is written so a reviewer can tell whether a number came from a public benchmark, a user-entered estimate, an uploaded catalog field, a calculated report metric, or an admin audit record. This makes the portal safer for CFO review, CIO governance, procurement sign-off, and operational owner validation.

Launch rule: If a page or report cannot explain the source of a value, it should be rewritten before production. Authority comes from clarity, not louder claims.