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 →
About AI2COE

From AI ambition to an Industrial AI Centre of Excellence.

AI2COE helps asset-intensive enterprises build and operationalise a governed Industrial AI Centre of Excellence. Industrial IQ is the evidence and decision-intelligence platform that converts exported operational records into source-linked diagnostic evidence across eight engines and 18 industries, supporting AI readiness, measurable decisions, human review, and bounded Agentic AI without ERP write-back.

Explore the CoE FrameworkReview Industrial IQOpen Evidence Library
AI2COEAI to Centre of Excellence
Industrial IQEvidence and decision-intelligence platform
8 engines18 industry blueprints
Industrial IQ eight-engine command map showing PartsCleanse, InventoryMind, ProcureMind, FinanceMind, AssetMind, ReliabilityMind, ReadyMind, and GovernanceMind feeding one evidence layer.
Eight Industrial IQ engines share one diagnostic model: mapped data, evidence, confidence tiers, reports, actions, and history.
Why AI2COE exists

Industrial AI needs an operating model before it needs another pilot.

Asset-intensive enterprises often have useful AI ideas, but the evidence needed to scale them is scattered across ERP, EAM, CMMS, inventory, procurement, asset, maintenance, finance, and governance systems. AI2COE exists to help those teams build a governed Industrial AI capability on evidence rather than disconnected experiments.

That is the meaning of AI to Centre of Excellence: move from isolated AI ambition to a repeatable operating model with source-backed diagnostics, confidence tiers, accountable human review, and bounded scale decisions.

Brand hierarchy
AI2COEMaster brand and Industrial AI Centre of Excellence promise.
Industrial IQEvidence and decision-intelligence platform used to diagnose, report, review, and track actions.
Eight enginesCatalog, inventory, procurement, finance, asset, reliability, readiness, and governance diagnostics.
18 industriesIndustry blueprints for asset-intensive operating contexts.
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.
Role of Industrial IQ

Industrial IQ makes the CoE operating model inspectable.

Industrial IQ starts with exported operational data, maps fields, validates source-fit, runs diagnostic engines, produces source-backed evidence, labels confidence, generates executive reports, and supports owner-reviewed action tracking. It is the platform layer under the AI2COE operating model.

The platform is intentionally read-only. It does not write back to SAP, IBM Maximo, Oracle, Infor, Hexagon EAM, CMMS, procurement, inventory, finance, or production systems.

Eight governed capabilities
Data and material masterPartsCleanse AI, InventoryMind AI, and ReadyMind AI expose catalog and readiness evidence.
Operating and financial decisionsProcureMind AI, FinanceMind AI, AssetMind AI, and ReliabilityMind AI connect evidence to buyer decisions.
Trust and governanceGovernanceMind AI keeps confidence, human review, audit metadata, and no-write-back controls visible.
Evidence before transformation

Every claim must be classified before it is used.

AI2COE separates observed, derived, estimated, and hypothesis-level evidence. Sample reports and planning tools demonstrate format and methodology. Customer-specific proof requires uploaded source data, field mapping, owner review, and approved reporting boundaries.

This is also the principle behind evidence before agency: Agentic AI should not gain authority until data readiness, tool boundaries, identity, evaluation, escalation, and human review are clear.

Public evidence and trust
Evidence LibrarySample assets, templates, comparisons, and trust material.
Research CenterFrameworks, assessment methodology, evidence standards, glossary, and benchmark-governance boundaries.
Trust CenterNo ERP write-back, source-file purge, human review, security brief, DPA, and SLA paths.
Founder thesis

Start where industrial AI proof is hardest to fake: operational data quality.

The AI2COE thesis is that industrial AI readiness must be proven through operational evidence: material master quality, inventory trust, procurement leakage, asset-to-part linkage, reliability context, ERP readiness, AI governance, and human-reviewed diagnostic outputs. Industrial IQ begins there because executives can inspect the evidence before committing to larger programs.

Assess AI CoE ReadinessRun Free Industrial IQ Snapshot