What is this resource for?

It helps buyers, sellers, internal champions, or investors understand AI2COE Industrial IQ using evidence-led, no-hype language.

Does Industrial IQ write back to ERP?

No. Industrial IQ produces diagnostic evidence, confidence tiers, reports, actions, and score history without ERP write-back.

Are ROI values final before review?

No. Benchmark and estimate language remains planning context until replaced by uploaded-data diagnostic evidence and human review.

AssetMind AI Product Brief | AI2COE Whitepaper

Product brief

AssetMind AI for sales, marketing, and buyer champions.

Asset-to-part linkage, critical spare coverage, obsolete asset spares, and plant risk heatmaps.

This brief helps the seller explain what the engine does, what data is needed, what output is delivered, what report is produced, what value lever is affected, and what next action the buyer should take.

InputAsset Id, Description + Material Id, Asset Status, Criticality, Equipment Class, Site

DiagnosticAsset-to-part linkage, plant-register relevance, critical asset spare coverage, obsolete asset spare exposure, and asset risk heatmap.

OutputAsset intelligence score, evidence table, confidence tiers, report, actions, and score history.

ValueEquipment hierarchy risk heatmap, retired-asset stock queue, equipment-class gaps, and criticality-weighted exposure. Asset criticality matrix and spares coverage index by plant, line, equipment class, and location.

Product brief matrix

How to position AssetMind AI.

One-line value proposition	AssetMind AI turns uploaded operational data into Asset intelligence score, evidence, report output, actions, score history, and governance context.
Operating problem	Asset-to-part linkage, critical spare coverage, obsolete asset spares, and plant risk heatmaps.
Input files	Asset Id, Description
Optional fields	Material Id, Asset Status, Criticality, Equipment Class, Site, Last Used Date
Diagnostic output	Asset intelligence score, evidence rows, confidence tiers, assumptions, limitations, and action recommendations.
Report delivered	AssetMind AI Asset-to-Part Risk Report
Value lever	Equipment hierarchy risk heatmap, retired-asset stock queue, equipment-class gaps, and criticality-weighted exposure.
CTA	Run Asset-to-Part Intelligence

Required fields

Minimum viable fields and engine-specific context.

Engine	Required Data File	Required Fields	Optional Fields	Output Generated	Minimum Viable Upload	Engine-Specific Context
AssetMind AI	Asset register	Asset Id, Description	Material Id, Asset Status, Criticality, Equipment Class, Site, Last Used Date, Quantity, Unit Cost	Asset intelligence score, evidence, report, actions, score history	Asset Id, Description	Material Id, Asset Status, Criticality, Equipment Class, Site, Last Used Date, Quantity, Unit Cost

Engine operating brief

How this diagnostic works for a decision owner.

Readiness label	Public synthetic demonstration
Business problem	Asset-to-part linkage, critical spare coverage, obsolete asset spares, and plant risk heatmaps.
Buyer role	Asset Integrity, Maintenance, Reliability, and Operations leaders
Trigger event	Asset register cleanup, BOM readiness, asset-to-part linkage gaps, obsolete asset spares, or critical equipment coverage reviews.
Core source export	Asset Id, Description
Optional fields	Material Id, Asset Status, Criticality, Equipment Class, Site, Last Used Date, Quantity, Unit Cost
Upload workflow	Upload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat
Column mapping	Industrial IQ profiles source-fit, suggests field matches, asks the user to normalize unmapped required fields, then recalculates mapping readiness before the engine runs.
Evidence generated	Source-backed evidence rows, reason codes, confidence tiers, review status, assumptions, limitations, and action-owner context.
Score output	Asset intelligence score
Report output	AssetMind AI Asset-to-Part Risk Report
Confidence tiers	High-confidence findings can move to review; weak or unsafe matches stay in human-review queues.
Recurring use case	Monthly or quarterly re-uploads create score history, action progress, planning comparison, and renewal value reporting.

Public proof assets

Sample outputs a Asset-to-Part Intelligence buyer can inspect before sharing private data.

These assets use synthetic public sample data. Customer screenshots, customer logos, real results, security questionnaires, and data-room artifacts require written approval before external use.

PDF download

PartsCleanse AI sample executive report

Review the report structure, evidence framing, assumptions, limitations, confidence tiers, and leadership summary.

Browser preview

Interactive sample diagnostic

Inspect how Industrial IQ presents score, evidence, action context, and no ERP write-back governance.

Sample CSV

Sample dataset for trial evaluation

Use a synthetic file to test the upload, mapping, validation, and sample diagnostic journey.

View All Sample Reports View Sample Datasets

Industrial IQ platform bridge

How this connects to AI2COE Industrial IQ

Asset-to-Part Intelligence is not treated as an isolated content topic. Industrial IQ connects it to uploaded data, engine evidence, confidence tiers, executive reports, actions, score history, and governance review.

Run Free Industrial IQ Snapshot Explore 8 Diagnostic Engines

PartsCleanse AIcreates catalog evidence and duplicate-family findings.

InventoryMind AIextends catalog signals into inventory risk, dead stock, excess stock, and stockout exposure.

ProcureMind AIconnects supplier and purchase signals to emergency buying, repeat purchases, and leakage.

FinanceMind AItranslates operating findings into working-capital exposure, carrying-cost assumptions, and finance-review scenarios.

AssetMind AIconnects parts to asset relevance, equipment coverage, and plant-register context.

ReliabilityMind AIconnects spare availability to maintenance readiness, false-stockout risk, and shutdown planning.

ReadyMind AIevaluates ERP, data, governance, and AI readiness gaps before transformation spend.

GovernanceMind AImanages confidence, evidence traceability, human review, and auditability.

Resource map

Find the operating task, evidence format, and review path.

Resources and docs help reviewers move from methodology to templates, proof format, trust review, and pilot decision without hunting through long text blocks.

Download Data Templates

Methodology

Research and framework pages define terms, readiness pillars, and evidence boundaries.

Required fields

Data templates clarify the source files and fields each diagnostic engine can evaluate.

Sample outputs

Sample reports show how evidence, scores, confidence tiers, and open findings are presented.

Review controls

Trust pages explain no ERP write-back, source-file handling, human review, and procurement review language.

Resource guide

Use this page to prepare source files, proof review, and the next evidence step.

Resource review reduces friction: what data is needed, how reports look, how evidence is reviewed, and which route the buyer can take next.

Audience

Implementation leads, data owners, procurement reviewers, and product champions.

Evidence to prepare

Required fields, CSV templates, user manuals, buyer guides, sample reports, diagnostic scenarios, and trust controls.

Output

A prepared evaluation path that leads to sample proof, data templates, upload, or a scoped diagnostic discussion.

Trust boundary

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

Download data templates View sample reports Required fields by engine Buyer evaluation guide