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 →
ReadyMind AI: Industrial AI readiness engine

ReadyMind AI — AI Readiness Diagnostic

Assess whether industrial data, ownership, governance, field completeness, process maturity, and first-use-case conditions are ready for safe AI initiatives before transformation investment. The workflow starts from exported operational data, produces ReadyMind AI AI Readiness Report, and keeps source systems untouched.

Run Free Industrial IQ SnapshotView Sample ReportRequest Diagnostic Pilot
Read-onlyDiagnostic
No ERPWrite-back
Source-filePurge after report generation
HumanReview before action
Evidence summary

Diagnostic evidence path

ReadyMind AI: This engine path connects the operating problem, exported source data, diagnostic logic, evidence output, review boundary, and next action for Industrial IQ buyers. Score operational data quality, source ownership, governance readiness, ERP export fit, and first-use-case practicality before industrial AI adoption.

Run This Engine
Review ownerThe operating, finance, procurement, maintenance, data, and governance leaders accountable for this diagnostic decision.
Input file contextTypical exported operational files, helpful optional fields, sample data, and mapped CSV or workbook evidence.
Diagnostic evidenceSource-backed findings, confidence tiers, score interpretation, report preview, review actions, and recurring-use path.
Recommended actionInspect the sample report, then run the matching engine with bounded exported operational data.
Executive decision snapshot

Problem, data, output, trust boundary, owner, and next action.

ReadyMind AI keeps the product review concrete: operating problem, typical exports, output, review owner, trust boundary, and next action stay visible before upload.

Read-only diagnostics. Source files purged after report generation. Human review before action.
Problem diagnosed

AI Readiness Diagnostic

Data needed

system landscape, sample exports, data ownership model

Output produced

ReadyMind AI AI Readiness Report

System boundary

Read-only; no ERP/EAM write-back.

Review owner

CIO, CTO, COO, Data Governance, and AI Transformation leaders

Next action

Run Snapshot, review sample report, or scope a pilot.

One platform, eight diagnostic engines

ReadyMind AI is one engine inside the Industrial IQ platform.

The selected diagnostic is shown inside the broader Industrial IQ operating model: exported operational data, source-backed evidence, confidence tiers, reports, action tracking, and no ERP write-back.

Compare all engines
CFO, CIO, Procurement, Maintenance, and Materials leaders

Catalog Intelligence

Catalog health score

 CFO, COO, Inventory, Materials, and Supply Chain leaders

Inventory Risk Intelligence

Inventory health score

 CPO, Procurement Director, CFO, and Supply Chain leaders

Procurement Leakage Intelligence

Procurement leakage score

 CFO, Finance Head, Procurement, and Board advisors

Working Capital Intelligence

Working capital score

 Asset Integrity, Maintenance, Reliability, and Operations leaders

Asset-to-Part Intelligence

Asset intelligence score

 Maintenance Director, Reliability Manager, COO, and Plant leaders

Maintenance Readiness Intelligence

Maintenance readiness score

 CIO, CTO, COO, Data Governance, and AI Transformation leaders

AI Readiness Intelligence

AI readiness score

 CISO, CIO, Audit, Governance, and Transformation leaders

Evidence Governance Intelligence

Governance readiness score

Product review card

One diagnostic decision, visible before upload.

ReadyMind AI shows what source data can prove, which findings are ready for review, and what remains buyer-controlled after the report.

Input files to prepare

system landscape, sample exports, data ownership model, governance controls

First diagnostic question

Can your operational data prove which industrial AI use case should be first, and which should wait?

Evidence returned

field completeness, owner coverage, system source, approval status

Review owner

CIO, CTO, COO, Data Governance, and AI Transformation leaders

Trust contract
Export-first Start from buyer-controlled CSV or workbook exports; no production integration is required for the first review.
Evidence before action Findings show source context, confidence, assumptions, limitations, and owner-review status.
Governed boundary No ERP write-back, no uncontrolled remediation, and human review before operational change.
AI readiness

ReadyMind AI makes its source-to-decision path visible before upload.

Industrial AI readiness score, first-use-case fit, and operational data readiness gates.

InputProcess Name, Data Source
OutputReadyMind AI AI Readiness Report
Trust boundaryRead-only diagnostic, no ERP write-back, confidence-tiered evidence, and human review before action.
ReadyMind AI readiness dashboard showing Industrial AI Readiness score, readiness pillars, source-backed diagnostics, and no ERP write-back boundary.
ReadyMind AI assesses Industrial AI Readiness through source-data quality, ERP readiness, operating context, and governance gates.
Industrial Evidence Graph

ReadyMind AI converts source records into governed evidence.

ReadyMind AI follows the same Industrial IQ trace: exported files, field fit, diagnostic lens, confidence marker, human review, read-only boundary, and audit-ready action.

01 Source tile

Exported ERP, EAM, CMMS, inventory, procurement, finance, asset, or work-order records.

02 Evidence trace

Mapped fields, source rows, reason codes, and continuity from file to finding.

03 Diagnostic lens

AI Readiness Intelligence evaluates the operating question with controlled engine logic.

04 Confidence marker

High, moderate, review-required, or insufficient evidence states use labels and shapes, not color alone.

05 Human review gate

Accountable owners review exceptions, limitations, and next actions before remediation.

06 Read-only boundary

One-way export path. No autonomous ERP, EAM, CMMS, procurement, or inventory write-back.

07 Decision / audit node

Owner, action status, evidence source, report output, and audit metadata stay reviewable.

Visual boundary: this is an original AI2COE information-design system. It represents diagnostic evidence flow, not customer proof, benchmark results, automated remediation, or ERP integration.
First diagnostic proof pack

Test ReadyMind AI with the smallest credible evidence pack.

Before a buyer shares private data, this proof pack shows the source export, field-mapping gate, source-fit gate, diagnostic signal, evidence output, and repeat path for AI Readiness Intelligence.

ERP export sample

Source export

Start with material, asset, inventory, work-order, procurement fields.

Required fields

Mapping gate

Confirm Process Name, Data Source. Add Business Unit, Data Owner, Data Quality Score, System Of Record where available.

AI readiness score

Source-fit gate

Weak coverage is labeled as an assumption or limitation before scoring.

ReadyMind AI

Diagnostic signal

Findings show source fit, data owner, quality gap, governance gate, use-case fit, review level, and readiness recommendation.

ReadyMind AI AI Readiness Report

Evidence output

Review field completeness, owner coverage, system source, confidence tiers, assumptions, limitations, and owner actions.

Score history and action tracker

Repeat path

Rerun after owner review to compare score movement and open findings.

View sample report Download sample CSV Mapping template Compare alternatives

Control boundary: read-only diagnostic, no ERP write-back, source-file purge after report generation, confidence-tiered evidence, and human review before action.

Output command console

ReadyMind AI produces a buyer-reviewable output bundle, not a black-box score.

The output UX is designed for executive reading and data-owner inspection: score, evidence table, confidence, report pack, action tracker, score history, export artifacts, and review ownership stay connected.

Open sample output
AI readiness score

Engine score

Score is a diagnostic interpretation, not a certified rating.

field completeness, owner coverage, system source, approval status

Evidence table

Rows show source context, reason codes, confidence, assumptions, and limitations.

High, medium, low, needs review

Confidence and limits

Findings stay separated by source quality before owner action.

ReadyMind AI AI Readiness Report

Executive report pack

Report sections include AI readiness score, data quality gate, governance ownership map, first-use-case recommendation.

Accept, reject, defer, assign, request more data

Action tracker

Output becomes governed work only after buyer review.

Baseline, rerun, movement, open findings

Score history

Recurring runs show what changed after owner decisions.

HTML, PDF, CSV evidence, mapping, dictionary

Output artifact kit

Data owners and executives can inspect the same report package.

CIO, CTO, COO, Data Governance, and AI Transformation leaders

Review owner

The accountable owner reviews evidence before remediation or system change.

HTML sample PDF report Sample CSV Data dictionary Run Snapshot

Output boundary: sample outputs demonstrate structure only. Uploaded-data diagnostics are source-backed, confidence-tiered, no-write-back, and human-reviewed before action.

Product experience

Inspect the upload, mapping, evidence, score, report, and action workflow before private data is uploaded.

These are illustrative Industrial IQ UI previews using sample/demo labels. They show the enterprise workflow buyers should expect: read-only upload, mapped fields, confidence-tiered evidence, executive reporting, and governed action tracking.

Industrial IQ in 2 Minutes
Industrial IQ illustrative upload workflow preview Illustrative product UI preview

Upload operational data

CSV/workbook exports from ERP, EAM, CMMS, inventory, procurement, asset, and maintenance systems. No ERP write-back.

Industrial IQ field mapping preview Illustrative product UI preview

Map fields

AI-assisted column matching exposes required fields, optional fields, source-fit score, and data readiness before the run.

Industrial IQ evidence table preview Illustrative product UI preview

Evidence table

Findings show source row, matched record, reason code, confidence, business impact, and reviewer status.

Industrial IQ diagnostic score preview Illustrative product UI preview

Diagnostic score

Score cards separate duplicate risk, source-fit, capital exposure band, and action priority.

Preview boundary: visuals use sample/demo content and do not represent customer data, approved customer outcomes, or financial commitments.

Product definition

ReadyMind AI is a AI Readiness Diagnostic.

ReadyMind AI is the Industrial IQ diagnostic for AI readiness. It reviews exported ERP, EAM, CMMS, procurement, inventory, and governance inputs to identify data-quality gaps, ownership gaps, process-readiness limits, and first-use-case suitability before AI transformation or automation programs are funded.

Who should use it: This page is for CIOs, CTOs, AI transformation leaders, COOs, CFOs, and governance teams who need to know whether industrial data and process controls are ready for AI use cases before investment.
First 10-second answer
What it diagnosesAssess whether industrial data, ownership, governance, field completeness, process maturity, and first-use-case conditions are ready for safe AI initiatives before transformation investment.
What it producesReadyMind AI AI Readiness Report, evidence rows, confidence tiers, score interpretation, action queue, and owner review status.
Why it is safeRead-only diagnostic, no ERP write-back, source-file purge after report generation, and human review before action.
Operating problem

Real industrial symptoms this engine is designed to inspect.

Operating problem

AI use-case lists are funded before source data completeness and ownership are proven.

Operating problem

ERP migration teams discover missing fields, inconsistent owners, and weak export quality late.

Operating problem

Operations and IT disagree on which system is authoritative for material, asset, inventory, or work-order data.

Operating problem

Data quality scores exist in BI, but they do not show whether AI use cases are safe to pursue.

Operating problem

Business units propose copilots without clear review controls, action owners, or source boundaries.

Operating problem

Master-data cleanup is scoped broadly because no one has evidence for which domain should go first.

Typical exported data

Start with files the buyer can export safely.

These fields describe the practical evidence pack for the diagnostic. They are not mandatory integration requirements, and they do not authorize ERP, EAM, CMMS, procurement, inventory, finance, or production-system write-back.

Exported field

system landscape

Exported field

sample exports

Exported field

data ownership model

Exported field

governance controls

Exported field

data-quality signals

Exported field

process ownership

Exported field

current AI use-case goals

Diagnostic logic

How ReadyMind AI turns exports into review evidence.

This is a high-level product explanation, not proprietary algorithm disclosure. Findings remain confidence-tiered and require owner review before operational action.

Diagnostic layerHow it works
Map system and process context Confirm system landscape, data sources, owners, update cadence, approval status, quality signals, and candidate AI use cases.
Score data readiness Evaluate completeness, freshness, ownership, field stability, relationship quality, and source-fit across operational domains.
Assess use-case fit Separate practical first use cases from blocked, risky, or premature automation ideas.
Apply governance gates Check owner accountability, review boundaries, data handling, and no-write-back posture before recommendations.
Create readiness roadmap Route gaps to CIO, CTO, process owners, data governance, and transformation sponsors.
Sample output preview

Illustrative evidence rows show the report format before private data is uploaded.

Rows below are sample/demo examples. Uploaded-data diagnostics replace illustrative rows with mapped source records, confidence tiers, assumptions, limitations, and owner review status.

Finding typeConfidenceSource evidenceRecommended review actionBuyer interpretationLimitation
AI readiness scorecard Derived Source-fit, data owner, completeness, governance context CIO and transformation review Leadership can sequence first use cases from evidence Score is a diagnostic signal, not a broad readiness approval.
Governance ownership gap Needs review Owner field, approval status, process owner, last updated Assign readiness owner CISO/CIO can block unsafe automation until ownership exists Organizational readiness requires human confirmation.
What this product does not do

Credible diagnostics need visible boundaries.

Industrial IQ creates review evidence. It does not become an uncontrolled remediation system.

No broad readiness approval Does not certify the enterprise as ready for all AI use cases.
No model deployment Does not build, deploy, or operate AI models, agents, or copilots.
No data platform build Does not build pipelines, lakehouses, or integrations.
No autonomous transformation Does not approve transformation spend or automate process changes.
No governance bypass Does not bypass CISO, legal, data-owner, or operational review.
Trust and data lifecycle

ReadyMind AI moves from exported data to owner-reviewed action.

AI2COE uses exported operational data for diagnostic review. The workflow is read-only, does not write back into ERP, EAM, CMMS, procurement, finance, inventory, or production systems, and source files are purged after report generation. Open Findings, summary metrics, report ownership, continuity metadata, and audit events may be retained where needed for governance and reporting.

View Security Brief
01 Exported data Buyer-controlled CSV or workbook exports start the diagnostic.
02 Read-only diagnostic Industrial IQ inspects mapped fields and never writes back to source systems.
03 Evidence-backed report Findings include source context, confidence, assumptions, limitations, and owner action.
04 Source-file purge Source files are purged after report generation according to disclosed handling boundaries.
05 Governance metadata Open Findings, summary metrics, ownership, continuity metadata, and audit events may be retained where required.
Commercial path

Choose the next action by buyer readiness.

Visitor situationRecommended next stepWhy
I want to see proof first View Sample Report Inspect sample findings, confidence tiers, assumptions, limitations, and owner actions.
I have exported data ready Run Free Industrial IQ Snapshot Upload a bounded file, map fields, and route the question to the right engine.
I need executive review Request Founder-Led Pilot Scope a 15-day diagnostic with accountable reviewers, data readiness, security review, and report expectations.
I need commercial terms View Pricing Review diagnostic and recurring intelligence paths without changing trust or data-retention language.
I need security review Read Trust Center Review no-write-back, source-file handling, confidence tiers, human review, DPA, SLA, and security brief paths.
AI-readable summary

Concise entity definition for search and AI assistants.

ReadyMind AI is the Industrial IQ industrial AI readiness diagnostic. It reviews operational exports, system context, ownership, governance, field completeness, process maturity, and AI use-case goals to score readiness and recommend first diagnostic paths. It is read-only and does not deploy models or certify AI readiness.

Product decision room

Can your operational data prove which industrial AI use case should be first, and which should wait?

Choose your first industrial AI use case from operational evidence, not generic AI ambition.

field completenessowner coveragesystem sourceapproval statusreadiness gap
Decision path Use the hero actions or final buyer journey panel to run the engine, inspect a sample report, see required data, or request pilot scoping.
Buyer intent
Assess ERP export readinessChoose first industrial AI use caseFind data quality blockersShow governance readinessPrioritize transformation safely
What this does not replace: Enterprise AI strategy. It does not replace strategy work. It grounds strategy in exported operational evidence.
Export readiness

Prepare the minimum practical evidence pack before the diagnostic review.

System landscape ERP, EAM, CMMS, procurement, inventory, finance, and ownership context
Sample operational exports representative catalog, inventory, procurement, asset, or work-order files
Governance context data owner, approval status, last updated, process owner, AI use-case goals
After-report action path

Use the report to decide what should happen next.

01 Select the first industrial AI use case from export quality, owner readiness, and governance evidence.
02 Create a readiness backlog for missing fields, unclear owners, and blocked use cases.
03 Sequence data, ERP, governance, and diagnostic work before automation expands.
Product workflow

ReadyMind AI is inspectable before private data is uploaded.

The product flow keeps the buyer's review sequence visible: source data, diagnostic logic, evidence, report, governance boundary, and next action.

1SelectStart with AI Readiness Intelligence or a buyer pack.
2UploadUse sample data first or map a private CSV/workbook export.
3ValidateCheck required fields, missing values, aliases, and readiness score.
4AnalyzeRun deterministic diagnostics with assumptions and limitations labeled.
5ReviewInspect evidence, review levels, action owners, and trust controls.
6ReportShare report output, score history, and next owner action.
Run Free Industrial IQ Snapshot View Sample Report Review Required Data
Best-fit ICPCIO, CTO, COO, Data Governance, and AI Transformation leaders
Minimum dataProcess Name, Data Source
Report outputReadyMind AI AI Readiness Report
Trust controlNo ERP write-back, owner review, review levels, and source-row evidence.
Report Preview and Output Contract

ReadyMind AI AI Readiness Report tells leadership what happened, why it matters, and what to do next.

Every report separates sample or benchmark assumptions from uploaded-data evidence. It is designed for executive reading, analyst inspection, and owner-assigned review without automatic ERP change.

AI readiness score Source-backed section used by the buyer committee before action is approved.
data quality gate Source-backed section used by the buyer committee before action is approved.
governance ownership map Source-backed section used by the buyer committee before action is approved.
first-use-case recommendation Source-backed section used by the buyer committee before action is approved.
readiness backlog Source-backed section used by the buyer committee before action is approved.
Open Sample Report Download Sample PDF Sample CSV
Evidence table preview
Field CompletenessVisible in the evidence table, score interpretation, or owner review queue.
Owner CoverageVisible in the evidence table, score interpretation, or owner review queue.
System SourceVisible in the evidence table, score interpretation, or owner review queue.
Approval StatusVisible in the evidence table, score interpretation, or owner review queue.
Readiness GapVisible in the evidence table, score interpretation, or owner review queue.
Buyer pack fit

ReadyMind AI sits inside the eight-engine Industrial IQ platform.

Role-based packs make each engine commercially understandable for the buying committee while preserving the one-platform story.

Buyer packDecision supportedCompanion engines
CIO / ERP Pack Prove ERP, data, governance, and AI readiness before integration, automation, or migration decisions. Evidence Governance Intelligence, Catalog Intelligence, Asset-to-Part Intelligence
CISO / Legal Pack Review no-write-back boundaries, source traceability, confidence tiers, limitation language, and audit evidence before industrial AI adoption expands. Evidence Governance Intelligence, Working Capital Intelligence
18-industry product readiness map

ReadyMind AI applies across asset-intensive environments without changing the no-write-back model.

The full industry ecosystem remains available in the industry hub. The first scan stays focused on representative contexts and the buyer decision.

Oil & Gas

AI Readiness Intelligence fit for Oil & Gas

Use exported operational data to test source-backed diagnostic readiness before action.

Manufacturing

AI Readiness Intelligence fit for Manufacturing

Use exported operational data to test source-backed diagnostic readiness before action.

Food & Beverage

AI Readiness Intelligence fit for Food & Beverage

Use exported operational data to test source-backed diagnostic readiness before action.

Pharmaceuticals

AI Readiness Intelligence fit for Pharmaceuticals

Use exported operational data to test source-backed diagnostic readiness before action.

Healthcare Facilities

AI Readiness Intelligence fit for Healthcare Facilities

Use exported operational data to test source-backed diagnostic readiness before action.

Higher Education Campuses

AI Readiness Intelligence fit for Higher Education Campuses

Use exported operational data to test source-backed diagnostic readiness before action.

Industry fit summary

Use the full engine route when the buying committee needs deeper matrices.

The first scan keeps attention on source exports, evidence output, buyer interpretation, trust boundaries, sample reports, and next action. Deeper scorecards and industry matrices remain available in the platform engine view.

Testing boundary: product and industry coverage is synthetic QA coverage and public-fit guidance, not customer proof, benchmark result, ROI claim, or certification.
Oil & GasMiningManufacturingFood & BeveragePharmaceuticalUtilitiesData CentersAviation MRO / AirlinesHealthcare SystemsRail, Metro & TransitTelecom Network OperatorsPorts, Marine Terminals & ShippingAerospace & Defense Maintenance DepotsWarehousing, Distribution Centers & 3PLCommercial Fleet, Trucking & LogisticsConstruction & Heavy Equipment FleetsHigher Education & Multi-Campus FacilitiesHospitality, Resorts & Gaming
View all industries View sample report
Diagnostic outcome evidence

What buyers inspect when they run ReadyMind AI.

These cards show the decision frames, inputs, outputs, and proof status a buyer committee should expect. Benchmark and sample frames are labeled; uploaded data replaces assumptions with customer-specific evidence.

Evidence contract
CIO readiness frame Sample diagnostic frame

ReadyMind AI

Manufacturing and industrial portfolios · ERP export sample, ownership fields, data freshness, and first-use-case evidence

6 readiness gates
1 recommended first use case

"ReadyMind grounds AI readiness in actual operational data, not generic maturity survey answers."

CIO, CTO, and transformation office

Primary action: use the ReadyMind AI Snapshot CTA above.
CISO / governance frame Benchmark-labeled frame

ReadyMind AI

Pharmaceuticals · Approval status, data owner, last updated, review rules, and source-field completeness

Owner accountability signal
Freshness data-quality gate

"The diagnostic shows whether AI adoption has enough data ownership and review control to proceed safely."

CISO, CIO, quality, and governance

Primary action: use the ReadyMind AI Snapshot CTA above.

Claims discipline: public examples are benchmark/sample frames unless marked as approved customer evidence. Savings or remediation outcomes require uploaded-data diagnostics and human review.

Answer-first product brief

What ReadyMind AI diagnoses.

ReadyMind AI diagnoses industrial AI and ERP readiness from exported operational samples, data-quality fields, system ownership, governance context, and first-use-case goals before automation or migration spend.

Recommended first diagnostic: Start with system landscape, sample operational exports, data owners, quality signals, process ownership, approval status, and AI or ERP use-case goals.
Trust boundary
Read-onlyStarts from exported files; no production integration is required to begin.
No ERP write-backNo ERP, EAM, CMMS, procurement, inventory, or asset record is changed by the diagnostic.
Source-file purgeSource files are processed to generate the diagnostic report pack and then purged.
Human reviewFindings remain confidence-tiered and owner-reviewed before operational action.
Industry operating symptoms

Signals real industrial buyers recognize before they name the product.

Operating symptom

AI use-case lists are funded before source data completeness and ownership are proven.

Operating symptom

ERP migration teams discover missing fields, inconsistent owners, and weak export quality late.

Operating symptom

Operations and IT disagree on which system is authoritative for material, asset, inventory, or work-order data.

Operating symptom

Data quality scores exist in BI, but they do not show whether AI use cases are safe to pursue.

Operating symptom

Business units propose copilots without clear review controls, action owners, or source boundaries.

Operating symptom

Master-data cleanup is scoped broadly because no one has evidence for which domain should go first.

Operating symptom

Automation readiness varies by plant, region, or business process with no comparable score.

Operating symptom

CISO, legal, and governance teams need a bounded path before private operational data is used.

Required source files

Practical exports to prepare for AI Readiness Intelligence.

File groupFields that improve diagnostic confidence
System landscape ERP, EAM, CMMS, procurement, inventory, finance, and ownership context
Sample operational exports representative catalog, inventory, procurement, asset, or work-order files
Governance context data owner, approval status, last updated, process owner, AI use-case goals
Diagnostic method

How the engine turns exports into review evidence.

LayerHow it works
Map system and process context Confirm system landscape, data sources, owners, update cadence, approval status, quality signals, and candidate AI use cases.
Score data readiness Evaluate completeness, freshness, ownership, field stability, relationship quality, and source-fit across operational domains.
Assess use-case fit Separate practical first use cases from blocked, risky, or premature automation ideas.
Apply governance gates Check owner accountability, review boundaries, data handling, and no-write-back posture before recommendations.
Create readiness roadmap Route gaps to CIO, CTO, process owners, data governance, and transformation sponsors.
Evidence outputs

What buyers receive after the diagnostic run.

OutputWhat it contains
AI readiness scorecard Data readiness, owner readiness, governance readiness, source-fit, and first-use-case fit.
ERP/migration readiness backlog Missing fields, weak owners, system conflicts, freshness gaps, and blocked-use-case reasons.
First diagnostic recommendation Which Industrial IQ engine should run first based on evidence rather than ambition.
Business problem

AI Readiness Diagnostic.

ERP data quality, governance readiness, operational readiness, and first-use-case recommendation.

ReadyMind AI is evaluated as a diagnostic workflow: upload, preview, field mapping, validation, analysis, source-backed evidence, score, report, action queue, owner review, and score-history movement inside the Industrial IQ portal.

Best-fit buyer rolesCIO, CTO, COO, Data Governance, and AI Transformation leaders
Trigger eventERP migration, AI readiness, working-capital pressure, procurement leakage, reliability risk, audit readiness, or recurring operational review.
Input data requiredProcess Name, Data Source
Upload workflowUpload CSV, preview fields, confirm AI-recommended mappings, validate required coverage, normalize where needed, then run the engine.
Diagnostic logicFindings show source fit, data owner, quality gap, governance gate, use-case fit, review level, and readiness recommendation.
Sample evidence tablePublic sample mode exposes mapped evidence rows before the customer uploads private data.
Score outputAI readiness score: lower values mean weaker ERP export usability, data quality, governance ownership, and first-use-case readiness.
Executive report previewSample report pages show the decision narrative, evidence rows, review levels, assumptions, limitations, PDF export, and next actions before private upload.
Report outputReadyMind AI AI Readiness Report with HTML, CSV evidence, PDF, and report email status for authenticated runs.
Governance controlsNo ERP write-back, no autonomous supplier outreach or system update, owner routing, audit metadata, and clear sample-versus-uploaded-data labeling.
Workflow review pack Upload, runbook, and sample-proof path for AI Readiness Intelligence

Open for the step-by-step workflow, diagnostic runbook, and public sample proof path.
Upload workflow

Upload -> Validate -> Analyze -> Evidence -> Score -> Report -> Action -> Repeat.

StepLayerCustomer experience
1UploadCSV export enters the parser. Source file retention rules are disclosed.
2MapERP/CMMS aliases are inferred, then corrected or confirmed by the user.
3ValidateRequired fields, completeness, missing values, and confidence reducers are shown before run.
4AnalyzeEngine-specific analyzers generate findings, evidence, and impact estimates.
5GovernFindings receive review levels and owner-decision status before any action.
6ReportExecutive report, evidence table, action tracker, and score snapshot are produced.
Engine diagnostic runbook

ReadyMind AI operating path from uploaded data to reviewed action.

This runbook makes the engine functional for buyers before a pilot: what to upload, what must pass, what the engine analyzes, what evidence is produced, and what owner decision is required.

StepGateEngine artifactBuyer decision
1 Minimum source ERP export sample Start with Process Name, Data Source. Best first run adds material, asset, inventory, work-order, procurement fields.
2 Source-fit gate Confirm required fields, aliases, completeness, and weak mappings. Context fields such as Business Unit, Data Owner, Data Quality Score, System Of Record, Automation Readiness improve confidence and reduce assumptions.
3 Operational analysis path ReadyMind AI ERP data quality, data freshness, owner accountability, governance readiness, and first-use-case recommendation. Field completeness, consistency, duplicate-rate, site context, valuation, and review workflow scoring. ERP/AI readiness output that labels what is proven, missing, assumed, and blocked.
4 Evidence output ReadyMind AI AI Readiness Report Score, findings, evidence rows, confidence tiers, assumptions, limitations, action queue, and score-history snapshot.
5 Acceptance gate Human-reviewed diagnostic Owner accepts, rejects, defers, or requests more data before remediation, optimization, or system change.
6 Repeat path Recurring intelligence Rerun after review actions to compare score movement, open findings, and unresolved evidence.
Control boundary: diagnostic outputs are decision evidence. They do not create ERP write-back, automatic deletion, supplier outreach, stocking-rule changes, or unreviewed remediation.
Public proof before account creation

Customers can inspect samples before uploading their own data.

Every sample result is labeled as sample mode. It demonstrates mapping, validation, scoring, evidence, confidence, report structure, action logic, and recurring-review context without claiming customer-specific exposure.

Sample reportPDFCSVMappingDictionaryDiagnostic page

Input-file detail Field dictionary and diagnostic data pack for AI Readiness Intelligence

Open when the buyer needs column-level mapping, aliases, and source-context examples.
Input files and field dictionary

Accepted fields, aliases, and mapping expectations.

InputNeedCommon aliasesMeaning
Process Name Yes process_name; process; workflow; business_process; use_case_process; diagnostic_process Process Name used by the selected Industrial IQ diagnostic engine.
Data Source Yes data_source; source_system; source; system; export_source; system_name Data Source used by the selected Industrial IQ diagnostic engine.
Business Unit Recommended business_unit; business_area; division; department; operating_unit Business Unit used by the selected Industrial IQ diagnostic engine.
Data Owner Recommended data_owner; owner; data_steward; business_owner; process_owner Data Owner used by the selected Industrial IQ diagnostic engine.
Data Quality Score Recommended data_quality_score; quality_score; dq_score; completeness_score; data_readiness_score Data Quality Score used by the selected Industrial IQ diagnostic engine.
System Of Record Recommended system_of_record; record_system; source_of_record; master_system; official_system System Of Record used by the selected Industrial IQ diagnostic engine.
Automation Readiness Recommended automation_readiness; readiness; automation_score; workflow_readiness; decision_automation_readiness Automation Readiness used by the selected Industrial IQ diagnostic engine.
Governance Owner Recommended governance_owner; governance_lead; approval_owner; control_owner; risk_owner Governance Owner used by the selected Industrial IQ diagnostic engine.
Ai Use Case Recommended ai_use_case; use_case; ai_case; copilot_use_case; decision_use_case Ai Use Case used by the selected Industrial IQ diagnostic engine.
Risk Level Recommended risk_level; risk; risk_rating; risk_class; control_risk Risk Level used by the selected Industrial IQ diagnostic engine.
Site Recommended site; plant; werks; location; storeroom; warehouse; depot; facility Plant, site, warehouse, storeroom, region, location, or operating unit.
Owner Recommended owner; data_owner; steward; responsible; approver; data_steward; business_owner Process owner, data owner, reviewer, buyer, planner, or accountable role.
Approval Status Recommended approval_status; status; approved; review_status; approved_status Approval, workflow, governance, review, or master-data change status.
Last Updated Recommended last_updated; changed_on; updated_at; modified_date Date the source record was last updated, approved, changed, or reviewed.
Business impact model

Why this matters to the buyer committee.

AI readiness

AI readiness model

Data quality, ERP export usability, governance ownership, first-use-case fit.

Transformation risk

Transformation risk model

Unclear ownership, missing fields, weak review rules, ungoverned AI ideas.

Diagnostic evidence

Diagnostic evidence model

AI readiness score, operational readiness score, readiness gap report.

Evidence detail Report evidence and buyer interpretation for AI Readiness Intelligence

Open when the buyer committee wants the output layers, confidence model, and role-by-role interpretation.
Evidence and confidence

What the report proves.

Output layerExampleWhy it matters
ScoreAI readiness score0-100 signal with risk level and trend-ready snapshot.
Score formulaDeterministic calculationThe report exposes the scoring formula and component inputs; random scores are not used.
FindingReadyMind AI AI Readiness ReportIssue title, severity, source engine, and owner-facing action.
EvidenceMapped source recordsSource-row references, relevant fields, analyzer reason codes, and review level.
Evidence graphSource -> finding -> evidence -> actionThe result carries an evidence graph for review, report, action, and score-history continuity.
ConfidenceHigh / Medium / Needs ReviewCoverage, completeness, source-field quality, and analyzer agreement.
ActionOwner review itemOwner action, priority, due window, and review status.
Renewal valueRecurring management viewThe report shows exposure identified, review queue size, actions created, and next review cadence.
Buyer interpretation

One diagnostic, multiple executive decisions.

BuyerDecision questionEvidence source
CEOAI investment sequencing: choose a funded AI starting point based on evidenceAI readiness board note
CIOERP export and data readiness: decide whether data can support AI or migration workreadiness scorecard
CTOarchitecture and use-case feasibility: sequence use cases that can be supported nowfirst-use-case recommendation
CISOsafe AI boundary: approve bounded diagnostics before automationgovernance-readiness view
ERP / data governanceownership and stewardship gaps: create a remediation backlog before AI expansionreadiness backlog
Trust controls

This engine is governed before operational action.

Trust control

No ERP write-back

Findings are recommendations and review items, not autonomous ERP changes.

 Trust control

Evidence traceability

Every finding links back to source records, mapped fields, and reason codes.

 Trust control

Evidence confidence

High, medium, low, and needs-review logic is visible before action.

 Trust control

Owner review

Owners can accept, reject, defer, assign, or request more data.

 Trust control

Audit trail

Report exports, reviewer actions, and status changes remain traceable.

FAQ

Questions buyers ask before running ReadyMind AI.

What problem does ReadyMind AI solve?

It diagnoses whether operational data, owners, systems, and governance controls are ready enough for industrial AI, ERP migration, automation, or diagnostic expansion.

What data files are needed?

Start with system landscape, representative exports, data ownership, data-quality signals, process owner, approval status, update cadence, and candidate AI or ERP use cases.

Does ReadyMind AI replace enterprise AI strategy?

No. It grounds strategy in operational evidence and helps decide which use case or diagnostic should run first. Strategy, architecture, and governance remain buyer-owned.

Does it build pipelines, copilots, or automation?

No. It scores readiness and produces a backlog. It does not build data platforms, deploy AI agents, or automate operational decisions.

What output does the buyer receive?

An AI readiness score, source-fit score, governance-readiness view, blocked-use-case reasons, ERP readiness backlog, and first diagnostic recommendation.

Who should own the review?

CIO, CTO, CDO, data governance, transformation leaders, process owners, CISO/legal, and operations should review the readiness evidence together.

How is this different from a survey assessment?

It does not stop at interview answers. It connects readiness to source exports, field completeness, ownership, governance gates, and diagnostic output options.

What is the safest first step?

Run a readiness review on representative exports and governance context before funding broad AI automation, ERP migration acceleration, or data-platform work.

Recommended next step

Move from product interest to buyer-ready evidence.

ReadyMind AI should help a buying committee answer one practical question: what can your exported data prove, which findings are confidence-tiered, who must review them, and what action is safe after the report. Choose the next step based on buyer readiness, not a generic demo sequence.

Run Free Industrial IQ Snapshot View Sample Report See Required Data Request Diagnostic Pilot
Boundary: sample and benchmark outputs are not customer-specific findings. Uploaded-data diagnostics remain no-write-back, confidence-tiered, source-backed, and human-reviewed before action.
Buyer journey

Choose the next action by buyer readiness.

Choose the next action based on where the buying committee is now: proof review, data readiness, pilot scoping, or security validation.

Open evaluation guide
Stage: Need proof first View sample diagnostic reports

Inspect evidence rows, confidence tiers, limitations, scores, and owner actions before sharing private data.

View Sample Reports Stage: Have an export ready Run an Industrial IQ Snapshot

Start with exported operational data or sample data and route the issue to the right diagnostic engine.

Run Snapshot Stage: Need committee alignment Download the buyer evaluation guide

Use the finance, operations, technology, procurement, maintenance, and security checklist for internal review.

Download Buyer Guide Stage: Active initiative Request a founder-led pilot

Use this path when ERP migration, inventory action, procurement leakage, or AI readiness needs a scoped diagnostic.

Request Pilot Stage: Security review Review the security brief

Validate no ERP write-back, source-file purge, human review, access controls, DPA/SLA path, and retention boundaries.

Review Security Brief

Trust boundary: No ERP write-back. Source files purged after report generation. Human review before action. Sample reports use demonstration data until replaced by uploaded-data diagnostics.

Diagnostic evidence path

Choose the next step that matches your buying stage.

Industrial IQ is designed for evidence-first buyers. Review sample proof, run a bounded Snapshot, align the buyer committee, or request a founder-led diagnostic pilot when the operating problem is ready for review.

Read-only diagnostics · No ERP write-back · Source files purged after report generation · Human review before action
Still evaluating View Sample Reports

See what the report looks like before sharing internal data.

 Have a data export Run AI Readiness Intelligence

Start with an export-first diagnostic path and no ERP write-back.

 Need committee alignment Download Buyer Evaluation Guide

Give finance, operations, procurement, ERP, security, and maintenance the same evaluation frame.

 Ready for review Request Founder-Led Pilot

Ask for a founder-led pilot review when the problem has an owner and source data is available.

AI2COE Copilot