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 →
Buyer-ready product brief

InventoryMind AI Product Brief

InventoryMind AI sales brief for value proposition, buyer pain, required data, diagnostic output, report delivered, value lever, and CTA.

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8Diagnostic engines
18Industries
0ERP write-back
AI adoption maturity roadmap showing discovery, diagnostics, governance, pilot prioritization, and enterprise scaling stages.
Documentation explains how exported data becomes evidence, reports, actions, and recurring score history.
Product brief

InventoryMind AI for sales, marketing, and buyer champions.

Dead stock, slow-moving stock, excess, stockout risk, and duplicated stock exposure.

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.

InputMaterial Id, Quantity + Description, Unit Cost, Stock Value, Last Movement Date, Movement Qty
DiagnosticDead stock, slow-moving stock, excess inventory, stockout risk, critical spare coverage, and duplicate stock exposure.
OutputInventory health score, evidence table, confidence tiers, report, actions, and score history.
ValueABC/XYZ segmentation, site transfer candidates, inventory policy exceptions, and critical understock queue. Service-level scenario simulator with stock-reduction, stockout-risk, and critical-spare protection assumptions.
Product brief matrix

How to position InventoryMind AI.

One-line value propositionInventoryMind AI turns uploaded operational data into Inventory health score, evidence, report output, actions, score history, and governance context.
Operating problemDead stock, slow-moving stock, excess, stockout risk, and duplicated stock exposure.
Input filesMaterial Id, Quantity
Optional fieldsDescription, Unit Cost, Stock Value, Last Movement Date, Movement Qty, Demand
Diagnostic outputInventory health score, evidence rows, confidence tiers, assumptions, limitations, and action recommendations.
Report deliveredInventoryMind AI Inventory Risk Report
Value leverABC/XYZ segmentation, site transfer candidates, inventory policy exceptions, and critical understock queue.
CTARun Inventory Risk Intelligence
Required fields

Minimum viable fields and engine-specific context.

EngineRequired Data FileRequired FieldsOptional FieldsOutput GeneratedMinimum Viable UploadEngine-Specific Context
InventoryMind AI Inventory balance CSV Material Id, Quantity Description, Unit Cost, Stock Value, Last Movement Date, Movement Qty, Demand, Criticality, Min Stock Inventory health score, evidence, report, actions, score history Material Id, Quantity Description, Unit Cost, Stock Value, Last Movement Date, Movement Qty, Demand, Criticality, Min Stock
Engine operating brief

How this diagnostic works for a decision owner.

Readiness labelAvailable through scoped diagnostic
Business problemDead stock, slow-moving stock, excess, stockout risk, and duplicated stock exposure.
Buyer roleCFO, COO, Inventory, Materials, and Supply Chain leaders
Trigger eventDead stock review, excess inventory pressure, stockout risk, slow-moving stock, or critical spare coverage questions.
Core source exportMaterial Id, Quantity
Optional fieldsDescription, Unit Cost, Stock Value, Last Movement Date, Movement Qty, Demand, Criticality, Min Stock, Max Stock, Site, Currency
Upload workflowUpload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat
Column mappingIndustrial IQ profiles source-fit, suggests field matches, asks the user to normalize unmapped required fields, then recalculates mapping readiness before the engine runs.
Evidence generatedSource-backed evidence rows, reason codes, confidence tiers, review status, assumptions, limitations, and action-owner context.
Score outputInventory health score
Report outputInventoryMind AI Inventory Risk Report
Confidence tiersHigh-confidence findings can move to review; weak or unsafe matches stay in human-review queues.
Recurring use caseMonthly or quarterly re-uploads create score history, action progress, planning comparison, and renewal value reporting.
Public proof assets

Sample outputs a Inventory Risk 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

Inventory Risk 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 templatesView sample reportsRequired fields by engineBuyer evaluation guide