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 →
AI2COE — AI to Centre of Excellence

Build an Industrial AI Centre of Excellence on evidence.

Agentic AI Readiness and Industrial Decision Intelligence for asset-intensive operations. Industrial IQ turns exported ERP, EAM, CMMS, inventory, procurement, asset, maintenance, and finance data into source-backed diagnostic evidence across eight engines and 18 industries, helping enterprises prioritise AI investments, govern human decisions, and prepare safely for bounded Agentic AI.

One operating model: use-case portfolio, source records, engine selection, evidence class, confidence, human owner, decision state, and no-write-back boundary before a pilot or scale decision.

Assess AI CoE Readiness Explore Industrial IQ Assess Agentic AI Readiness
Read-only diagnostics
No ERP write-back
Source files purged after report generation
Human-reviewed evidence
AI2COE Agentic AI robots reviewing operational evidence inside a product-led Centre of Excellence workflow with source records, engine selection, confidence, human review, pilot decision, and no-write-back boundary.
Inspectable CoE workflow: use-case portfolio to source evidence, engine fit, confidence, owner review, and pilot decision.
Evidence before agency

Agentic AI readiness is a front-door decision, not a side note.

AI2COE evaluates whether a bounded agentic use case has enough material identity, asset relationships, inventory state, work history, ownership, tool permissions, approval policy, security context, evaluation criteria, and industry context before any pilot is considered.

Across 18 asset-intensive industries, the current public boundary is read-only readiness evaluation and controlled synthetic evidence, not autonomous remediation.

Assess Agentic AI ReadinessExplore the Read-Only Evidence AgentRequest Controlled PilotBrowse Industry AI Guides
Agentic AI use-case context
Use caseIndustry contextApproved skillsEvidenceHuman reviewPilot gates
Industrial Evidence Graph

Move from exported source data to an owner-reviewed decision.

Industrial IQ keeps source rows, assumptions, confidence, and accountable review visibly separate.

01 Source tile

Exported rows and mapped fields

02 Evidence trace

Reason codes, assumptions, and limits

03 Diagnostic lens

Confidence-tiered findings, candidates, and signals

04 Human review gate

Accountable owner decision before action

Read-only boundaryNo ERP write-back. No uncontrolled remediation. Human review before action.
Catalog evidence entry point

Start where MRO data pain is easiest to prove: the material and spare-parts catalog.

PartsCleanse AI exposes duplicate candidates, weak descriptions, manufacturer ambiguity, and UOM conflicts before broader inventory and procurement review.

Duplicate candidates Field quality Confidence tiers

Review PartsCleanse AI

PartsCleanse AI catalog intelligence visual showing source records, duplicate candidates, evidence, and review output
Catalog evidence becomes the governed entry point to inventory, procurement, and finance review.
Connected diagnostic chain

Catalog → inventory → procurement → finance.

Each lens preserves its own evidence boundary while strengthening the next buyer decision.

Catalog evidence
PartsCleanse AI

Duplicate and quality candidates
Inventory context
InventoryMind AI

Excess, obsolete, and stockout signals
Procurement context
ProcureMind AI

Supplier and emergency-buy signals
Finance review
FinanceMind AI

Assumption-bound exposure bands

Eight-engine expansion

Choose the diagnostic lens for the operating decision.

Compare all engines

One platform, eight distinct decision domains, and one governed evidence model.

Catalog IntelligencePartsCleanse AI

Find catalog quality and duplicate-material risk.

SourceItem master OutputCandidate families
Open engine
Inventory Risk IntelligenceInventoryMind AI

Surface excess, obsolete, and false-stockout signals.

SourceStock + movement OutputInventory signals
Open engine
Procurement Leakage IntelligenceProcureMind AI

Trace supplier fragmentation and emergency-buy patterns.

SourcePO + supplier OutputLeakage signals
Open engine
Working Capital IntelligenceFinanceMind AI

Translate diagnostic evidence into finance review bands.

SourceValue + assumptions OutputExposure bands
Open engine
Asset-to-Part IntelligenceAssetMind AI

Connect assets, parts, BOM coverage, and criticality.

SourceAssets + BOM OutputCoverage gaps
Open engine
Maintenance Readiness IntelligenceReliabilityMind AI

Review maintenance demand and spare-readiness context.

SourceWork orders OutputReadiness signals
Open engine
AI Readiness IntelligenceReadyMind AI

Assess operational data and first-use-case readiness.

SourceERP + owners OutputReadiness gates
Open engine
Evidence Governance IntelligenceGovernanceMind AI

Govern confidence, review ownership, and evidence traceability.

SourceFindings + review OutputControl record
Open engine
From AI initiatives to enterprise capability

Build an Industrial AI Centre of Excellence on evidence.

AI programs do not scale through disconnected pilots. They need a governed operating model that connects readiness, evidence, ownership, trust controls, and scale decisions. AI2COE brings that foundation through Industrial IQ, eight diagnostic AI engines, 18 industry blueprints, and evidence-first Agentic AI readiness.

Assess AI CoE Readiness Explore Industrial IQ Assess Agentic AI Readiness
01 Diagnose Start with exported operational evidence and source-fit review.
02 Quantify Separate observed, derived, estimated, and hypothesis-level value signals.
03 Prioritize Rank decisions by evidence strength, owner urgency, and operating risk.
04 Govern Keep no-write-back, source handling, confidence tiers, and human review visible.
05 Pilot Run bounded diagnostics before broad AI or agentic commitments.
06 Scale Use score history, action tracking, and governance evidence to expand safely.
GovernSet decision rights, evidence rules, risk limits, and human-review controls.EnableProvide reusable templates, field guidance, sample reports, and diagnostic paths.OptimiseUse evidence, score history, action tracking, and owner feedback to improve the operating model.ScaleExpand only where confidence, value, governance, and operating ownership are sufficient.
Operating hierarchy: AI2COE is the AI Centre of Excellence brand. Industrial IQ is the evidence and decision-intelligence platform. The eight engines provide the diagnostic lenses.
Guided Diagnostic Selector

Source -> Qualify -> Evidence -> Review -> Decide.

A single five-stage path connects role, engine, source data, evidence, owner review, and next action without forcing every visitor into the same CTA.

01
Source

Upload exported CSV or workbook data from ERP, EAM, CMMS, inventory, procurement, asset, finance, or work-order systems.

02
Qualify

Confirm Required Fields, source fit, and engine context before findings become decision evidence.

03
Evidence

Review source-backed rows, assumptions, limitations, confidence tiers, and diagnostic scores.

04
Review

Route findings to finance, operations, procurement, maintenance, ERP/data, reliability, or governance owners.

05
Decide

Assign actions and track improvement without ERP write-back.

Sample proof

Inspect the evidence format before sharing private data.

View sample reportsOpen Evidence Library
Illustrative Industrial IQ evidence table interface
Evidence table

Inspect source rows, reason codes, confidence, and limitations.

 Illustrative Industrial IQ executive report interface
Executive report

Review score interpretation, assumptions, findings, and decision context.

 Illustrative Industrial IQ action tracker interface
Action tracker

See how reviewed findings move to owners, priorities, and status.

Sample outputs use demonstration data. Customer-specific findings require uploaded data, confidence review, and accountable owner validation.

Trust controls

Review the operating boundary at a glance.

Open Security Brief
No ERP write-backNo source-system records are changed. Source-file purgeSource files are purged after report generation. Human reviewAccountable owners review findings before action. Confidence tiersEvidence, candidates, signals, and assumptions stay distinct.
Buyer decision map

Give each owner the evidence they need to proceed.

Finance, operations, technology, procurement, and MRO leaders use the same source-backed diagnostic record through different decision lenses.

CFO / Finance

Exposure bands, assumptions, and value-review boundaries.

Open buyer path COO / Operations

Operational risk, owner actions, and site-level priorities.

Open buyer path CIO / ERP & Data

Source fit, field quality, readiness, and governance gaps.

Open buyer path CPO / MRO

Supplier, inventory, material, and emergency-buy evidence.

Open buyer path
18-industry diagnostic map

Start with the operating archetype, then choose the engine mix.

View all 18 industries
Critical infrastructure diagnostic map
Critical infrastructureEnergy, utilities, data centers, ports
 Production and throughput diagnostic map
Production and throughputManufacturing, food and beverage, mining
 Regulated operations diagnostic map
Regulated operationsPharma, aviation, healthcare, defense
 Distributed assets diagnostic map
Distributed assetsFleet, logistics, facilities, campuses
Evidence before transformation

Run the first diagnostic when the evidence path is clear.

Start with sample data or upload exported operational data to generate evidence-backed findings, scores, reports, owner actions, and score history without ERP write-back.

Run Free Industrial IQ Snapshot Request Founder-Led Pilot
AI2COE Copilot