PartsCleanse AI -- MRO Catalog Deduplication

Data-retention promise

Run the diagnostic without turning your catalog into a standing data room.

Source catalog purgedUploaded CSV files are processed for the run and then deleted after report generation.

Only summary evidence retainedAI2COE keeps Open Findings, metrics, ownership, quota, feedback, and audit metadata.

Session-only downloadsExcel, Word, PDF, and clean CSV downloads are available only in the active report-generation session.

Source files purgedUploaded catalogs are deleted after report generation; summary metrics and Open Findings remain.

Session downloads onlyExcel, Word, PDF, and CSV files are available in the active session, not as permanent server files.

No ERP write-backThe product creates evidence and review routing; client owners approve any system change.

Owner-branded reportsReports carry the generator's name, role, company, industry, currency, and audit context.

90-second product context

Before the upload, show the buying committee what the diagnostic proves.

This short brief frames PartsCleanse AI for CFO, procurement, operations, CIO, and master-data owners before they run the workbench.

CFOCapital exposure and recoverable working capital

CIOERP readiness without uncontrolled write-back

COOOperational risk, stockout, downtime, and OEE impact

Run Diagnostic Calculate ROI

AI2COE | Industrial IQ — Intelligence. Automation. Impact.

Report authority preview

The generated report is built for the room that approves action.

PartsCleanse AI reports are structured for CFO, procurement, operations, CIO, and master-data owners. The output does not simply list duplicate rows; it explains value, confidence, operating risk, source purge posture, and review governance.

$4.3MCapital exposure signal

$1.1M-$2.3MRecoverable range

$765.0KAnnual carrying-cost drag

5 outputsBrowser, Excel, Word, PDF, CSV

Executive diagnostic report

CFOworking capital

CPOleakage control

CIOdata governance

Industry benchmark assumptions and local currency notation Confidence-tiered duplicate families and false-positive controls Session download policy and Open Findings retention posture

Engine decision context · PartsCleanse AI

PartsCleanse AI is a 15-business-day, ERP-agnostic MRO catalog deduplication diagnostic. It identifies duplicate spare-parts records in SAP, IBM Maximo, Oracle, Hexagon EAM, or any CMMS catalog using confidence-tiered scoring with 7-class industrial discriminator penalties that prevent unsafe part consolidations. Engagements start at $8,000 from a single CSV export — no integration, no IT project, no subscription.

Competitive differentiator — discriminator logic

Unlike generic fuzzy-match tools, PartsCleanse AI applies critical discriminator penalties after text scoring — size, pressure class, material family, model number, functional subtype, commercial unit (pack vs each), and part category. A 2-inch gate valve and a 4-inch gate valve sharing similar descriptions will never be flagged as duplicates. This controls false-positive consolidation across all Tier 1/2/3 findings.

What is MRO catalog deduplication?

MRO catalog deduplication is the process of identifying spare-parts item records in an ERP or CMMS that describe the same physical component under different descriptions, codes, or supplier formats — then quantifying the financial exposure from duplicate stock before authorizing any consolidation. PartsCleanse AI automates this diagnostic in under 90 seconds from a CSV export, with no ERP integration required.

Executive decision frame

This is not a data-cleaning screen. It is a management finding.

PartsCleanse AI is designed to change the internal conversation from "we think the catalog has duplicates" to "here are the duplicate families, here is the capital exposure, here is the confidence tier, and here is the governed review path."

That distinction matters. Industrial organizations do not need a prettier spreadsheet; they need a defensible evidence pack that maintenance, procurement, finance, and master-data owners can use together.

The report answers

How large is the exposure?Total SKUs, duplicate groups, duplicate rate, and capital-at-risk interpretation

How reliable are the findings?Confidence tiers, discriminator controls, and review-routing logic

What happens next?Clean CSV baseline, executive summary, and governed remediation language

What you receive

Five executive-grade deliverables from a single CSV upload.

Output

In-browser executive report

Findings open directly in the browser with KPI narrative, risk interpretation, and review guidance.

Output

Excel evidence workbook

A structured workbook for analysts and data stewards to inspect duplicate families and confidence tiers.

Output

Word executive summary

A board-ready document with business narrative, KPI summary, governance language, and next actions.

Output

PDF executive report

A presentation-ready decision brief for finance, procurement, operations, and leadership review.

Output

Clean CSV baseline

A governed review baseline, not an uncontrolled ERP overwrite.

Ask the AI2COE Copilot

Ask about PartsCleanse AI

Methodology, outputs, ERP coverage, or competitive differentiation — the Copilot pulls from the full knowledge base.

Why PartsCleanse AI -- not manual or generic tools

What separates a governed diagnostic from a spreadsheet exercise.

Capability	Manual / Spreadsheet	Generic dedup tool	PartsCleanse AI
Processes 50,000 SKUs	Weeks to months	Minutes -- unvalidated	42.9 seconds
Industrial discriminator controls (size, pressure, material, model)	✗ None	✗ Generic text only	✓ 7 discriminator classes
Confidence-tiered output (Tier 1 / 2 / 3 review routing)	✗ Binary yes/no	✗ Single score	✓ 3-tier governed review
SAP abbreviation handling (pre-normalization before scoring)	✗ Requires manual prep	✗ Misses SAP format	✓ Adaptive input profiler
Capital-at-risk figure (in executive report language)	✗ Manual calculation	✗ Not produced	✓ Per-run quantification
Board-ready deliverables (Browser, Excel, Word, PDF, CSV)	✗ Self-formatted	✗ Raw export only	✓ 5 formats per run
ERP integration required	✗ Often required	Sometimes	✓ CSV only -- zero integration

How the engine works

Two-stage architecture. Built for real industrial catalogs.

Engine 1 -- Input Profiler: Classifies the catalog as abbreviated (SAP), verbose, mixed, or clean before any scoring begins. Raw SAP abbreviations, post-migration description fragments, and multi-site data are handled before comparison -- not after.

Engine 2 -- Duplicate Detector: Runs TF-IDF weighted blocking, manufacturer alias normalization, 200-category part-type taxonomy, composite confidence scoring, and critical industrial discriminator penalties -- size, pressure rating, material family, model number, and pack-vs-each unit conflicts all prevent unsafe matches.

Review Full Methodology

The core safety standard

Finding similar descriptions is easy. Avoiding unsafe consolidation is the hard part. A 2-inch valve and a 4-inch valve share most description words -- but they are not interchangeable. PartsCleanse AI is engineered around that risk.

Tier 1Accelerate obvious duplicates -- ready for ERP review

Tier 2Probable duplicates -- procurement and engineering review required

Tier 3Possible duplicates -- specialist authorization before any action

No ERP integration. No IT project. No proposal required.

Your catalog diagnostic is ready when you are.

Register in two minutes. Upload your CSV. Receive a full duplicate-family report with capital-at-risk figures, confidence-tiered evidence, a board-ready Word summary, and a clean CSV baseline -- before your next management meeting.

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Industries served

18 asset-intensive markets. One governed diagnostic.

PartsCleanse AI is calibrated for the catalog complexity of each sector. See your industry's tailored diagnostic pathway, use-case map, and AI adoption sequence.

Oil & Gas Mining Manufacturing Food & Beverage Pharmaceutical Utilities Data Centers Aviation MRO / Airlines Healthcare Systems Rail, Metro & Transit Telecom Network Operators Ports, Marine Terminals & Shipping Aerospace & Defense Maintenance Depots Warehousing, Distribution Centers & 3PL Commercial Fleet, Trucking & Logistics Construction & Heavy Equipment Fleets Higher Education & Multi-Campus Facilities Hospitality, Resorts & Gaming

Access

Free to start. No commitment required.

No credit card required — ever

30Diagnostic runs per account, free

5Executive deliverables per run — browser report, Excel, Word, PDF, CSV

18Industry reporting contexts included

ZeroERP integration, IT project, or proposal required

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FAQ

Questions buyers ask before running a diagnostic.

Pricing — quotable reference

PartsCleanse AI diagnostic engagements are priced at $8,000–$20,000 as a flat fee depending on catalog size. Includes engine processing, all five output artifacts, and delivery within 15 business days. No ERP integration or ongoing subscription required.

SAP S/4HANA migration — quotable fact

SAP ECC end-of-support is 2027. S/4HANA's stricter material master model turns duplicate records into migration blockers. PartsCleanse AI rationalizes the material master before migration begins — eliminating the most expensive category of post-cutover data cleanup.

Engine performance — validated benchmark

PartsCleanse AI processes a 50,000-SKU catalog in 42.9 seconds. A 25,000-SKU Oil & Gas reference catalog produced 3,847 duplicate families, $4.2M capital at risk, in 38.7 seconds. Zero ERP connections required.

Safety control — quotable guarantee

The engine applies discriminator penalties for size, pressure rating, material family, model number, and unit-of-measure conflicts. A 2-inch valve and a 4-inch valve sharing similar descriptions will never be flagged as duplicates. No automatic ERP overwrites occur.

Product FAQ 01

What does PartsCleanse AI do?

PartsCleanse AI is an AI-powered MRO spare-parts catalog deduplication diagnostic. It processes CSV exports from SAP, Maximo, Oracle, or any CMMS to identify duplicate item families, quantify capital exposure, and produce five executive-grade report artifacts in under 90 seconds. No ERP integration or IT project is required to start.

Product FAQ 02

How much does a PartsCleanse AI diagnostic cost?

PartsCleanse AI diagnostic engagements are priced at $8,000–$20,000 as a flat fee depending on catalog size. The price includes engine processing, all five output artifacts, and delivery within 15 business days. No ongoing subscription, ERP integration, or implementation program is required to initiate the engagement.

Product FAQ 03

Why is PartsCleanse AI critical for SAP S/4HANA migration programs?

SAP ECC reaches end of mainstream support in 2027. S/4HANA enforces a stricter material master data model — duplicate and inconsistent records that coexist in ECC become migration blockers or data-integrity failures post-cutover. PartsCleanse AI rationalizes the material master before migration begins, eliminating the most costly category of data remediation: post-cutover cleanup.

Product FAQ 04

Does PartsCleanse AI require ERP system integration?

No. PartsCleanse AI starts from a standard CSV catalog export from SAP, IBM Maximo, Oracle, Hexagon EAM, Infor, or any site-level CMMS. No API connection, no IT procurement cycle, and no onboarding program is required. Upload the file and receive results immediately.

Product FAQ 05

How does PartsCleanse AI control false positives in spare-parts deduplication?

The engine applies critical discriminator penalties after fuzzy text scoring. Size, pressure rating, material family, model number, functional subtype, and pack-vs-each unit conflicts reduce unsafe match confidence scores. A 2-inch valve and a 4-inch valve sharing similar descriptions will never be flagged as duplicates. Tier 2 and Tier 3 results form a specialist review backlog — no automatic ERP overwrites occur.

Product FAQ 06

What outputs does a PartsCleanse AI diagnostic produce?

Each diagnostic produces five artifacts: an in-browser executive report, an Excel evidence workbook with confidence-tiered duplicate families, a Word executive summary for board presentation, a PDF executive report, and a clean CSV baseline for governed review. All five are available immediately after the engine run completes.

Product FAQ 07

How long does a PartsCleanse AI diagnostic take?

The engine processes a 50,000-SKU catalog in 42.9 seconds. Smaller catalogs run proportionally faster. Output artifacts are available immediately — no consultant turnaround time, no project delay.

Product FAQ 08

Which industries does PartsCleanse AI serve?

PartsCleanse AI serves 18 asset-intensive industries including oil and gas, mining, manufacturing, utilities, food and beverage, pharmaceutical, aviation MRO, rail and transit, ports and marine terminals, data centers, and construction. Each industry page maps the diagnostic to that sector's specific ERP environment, compliance requirements, and cost model.

Product FAQ 09

Who should sponsor a PartsCleanse AI diagnostic inside the customer organization?

The strongest sponsor is usually the CFO, COO, Head of Procurement, CIO, Reliability Director, Maintenance Director, or Master Data Governance owner. The product is intentionally cross-functional: finance needs the capital exposure, procurement needs supplier and duplicate-item leakage, operations needs uptime context, and data governance needs a controlled review backlog.

Product FAQ 10

What should a buyer prepare before uploading a catalog?

Prepare a CSV export with item number, item description, UOM, quantity on hand, unit cost, site or plant, manufacturer, manufacturer part number, supplier, and any criticality or commodity fields available. The engine can run with partial data, but richer fields produce stronger CFO, procurement, operations, and governance interpretation.

Product FAQ 11

What does AI2COE retain after the diagnostic?

Source catalog files are processed for the run and purged after report generation. AI2COE retains only summary metrics, report ownership, quota usage, feedback, and audit metadata for dashboards and product improvement. Session-only downloadable files are not intended to become permanent server-side storage.

Run Your First Diagnostic Talk to the Team First

Evaluation pathway

Where are you in your evaluation?

The right next step depends on where you are. Use the pathway below to move from problem confirmation to procurement-ready engagement.

Stage 1 — Confirm

Confirm the problem exists before committing budget

You suspect catalog duplication is eroding working capital but have not yet quantified it. Start here.

→ Run the exposure scorecard → Model the financial ROI → Upload a sample CSV (free)

Stage 2 — Evaluate

Understand the methodology, outputs, and fit for your ERP environment

The problem is confirmed. You are now evaluating whether PartsCleanse AI fits your data posture and governance requirements.

→ Read the methodology → View the full product overview → Preview sample diagnostic reports

Stage 3 — Engage

Commission a scoped pilot or request procurement documentation

Evaluation is complete. You are ready to scope an engagement, obtain procurement documentation, or request a formal quote.

→ Review pricing and tiers → Book a pilot engagement → Procurement FAQ — W-9, DPA, SLA

Competitive differentiation

Why industrial operators choose PartsCleanse AI over alternatives.

Generic data cleansing tools, MDM platforms, and consulting services all address catalog quality. But they address it at a different cost, time, and governance posture than PartsCleanse AI. The table below captures the critical differences.

Criterion	PartsCleanse AI	Generic fuzzy matcher	SAP MDG / Oracle MDM	MRO consulting firm
Industrial false-positive control	7 discriminator classes	None -- text-only scoring	Rule-based, requires config	Manual analyst review
Time to first finding	Under 90 seconds	Hours -- no output format	Weeks to months -- platform setup	4-16 weeks -- engagement timeline
Input requirement	Single CSV export	Varies -- often requires integration	Full ERP integration	Multiple data pulls + workshops
Executive output artifacts	5 per run (browser, Excel, Word, PDF, CSV)	CSV or log only	ERP workflow -- no report	Slide deck -- varies by firm
SAP abbreviation handling	Adaptive normalization engine	Not supported	Partial -- via data standards config	Analyst judgment
No ERP write-back	Guaranteed -- diagnostic only	Not applicable	No -- MDG executes changes	Depends on scope
Cost to start	Free (30 runs)	Varies -- usually free but no output	High -- license + SI fees	$50K-$500K+ engagement cost

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What comes next after catalog rationalization

Two controlled-beta modules extend the same diagnostic-first model.

PartsCleanse AI addresses the catalog layer. The modules below apply the same governed, no-integration-required diagnostic approach to maintenance history and procurement spend.

Controlled beta

Predictive Maintenance AI

Work-order and CMMS history analyzed for bad actors, repeat failure patterns, downtime exposure, and maintenance strategy segmentation.

Explore the module → Controlled beta

Procurement Intelligence AI

PO, supplier, and spend data analyzed for price variance, emergency-buy premiums, supplier fragmentation, and tail-spend governance.

Explore the module →