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 planning assumptions from diagnostic evidence.

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

PlanningAssumptions labelled
EvidenceGenerated from data
GovernanceReview before action
Industrial AI Readiness research map connecting framework, assessment methodology, evidence standards, glossary, executive playbook, and benchmark methodology.
The Research Center separates methodology, glossary definitions, evidence governance, executive guidance, and benchmark methodology from commercial diagnostics.
Evidence layerHow it is producedGovernance control
Planning rangesPublished as 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 are written as 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.
Executive review lens

Use this page to decide the next evidence step.

Industrial IQ pages are designed to move enterprise buyers from operating pain to source-backed diagnostic evidence, not to force an immediate platform commitment.

Audience

Finance, operations, procurement, maintenance, reliability, ERP/data, security, and executive sponsors.

Evidence to prepare

Relevant ERP, EAM, CMMS, inventory, procurement, asset, work-order, or readiness exports where available.

Output

A diagnostic route, sample proof format, report evidence, confidence tier, owner review path, or commercial next step.

Trust boundary

Read-only diagnostics, no ERP write-back, source-file purge after report generation, and human review before action.