Verdantis MDM Suite

Before you buy a spare, find the one you already own

SpareSeek AI is the newest agent in the Verdantis MDM Suite. It searches your inventory, EAM, and ERP to find alternate and technically equivalent spares that already exist across your operation, so a purchase request or a stockout starts with what you already have.

MATERIALS MASTER ASSET MASTER MULTI-PLANT INDUSTRIAL

An MDM Suite agent. SpareSeek AI runs on the harmonized, enriched master data that Harmonize and Integrity produce. Clean, attribute-rich records are what make true technical equivalence possible, which is why this agent lives in the MDM Suite.

The Problem

You are buying spares you already have

In a multi-plant operation, the same part lives under different codes, in different systems, at different sites. Without a way to see technical equivalence across inventory, EAM, and ERP, teams reorder parts that already sit on a shelf somewhere, or expedite a spare when an interchangeable one is in stock next door.

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Hidden equivalents

The same part, described three different ways, is treated as three different parts. The equivalent you need is in your data under a name you did not search for.

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Duplicate part numbers

New codes are created for spares that already exist, inflating inventory value, carrying cost, and spend on parts you did not need to buy.

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Cross-system blind spots

Inventory, EAM, and ERP each hold a piece of the picture. None shows whether an equivalent exists in another system or at another plant.

The alternate you need is usually already in your data. The problem was never supply. It was finding the equivalent you already own before a new order goes out.
How It Works

How SpareSeek AI finds an alternate

SpareSeek AI works on the master data that Harmonize and Integrity keep clean, so it matches on real technical attributes and specifications, not just similar-looking text.

1

Read

Pulls part records across your inventory, EAM, and ERP into one view, using the harmonized master data as its reference.

2

Match

Compares technical attributes, specifications, and classification to identify true equivalents, not parts that merely read alike.

3

Rank

Orders alternates by closeness of technical fit and by where the equivalent is held across your sites and systems.

4

Surface

Presents interchangeable spares already in your operation, with the code, system, and location where each one sits.

Powered by your golden record. The quality of every match depends on the harmonized, enriched master data beneath it. That is why SpareSeek AI is an MDM Suite agent, not a standalone search tool.
What It Finds

Every kind of alternate hiding in your data

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Technical equivalents

Parts with the same specification held under a different code, description, or unit of measure.

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Interchangeable and substitutable parts

Spares that are functionally interchangeable for the job at hand, based on attributes and classification.

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Cross-plant matches

An equivalent held as stock at another site, so a shortage at one plant is covered by surplus at another.

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Cross-system matches

Equivalents that appear in EAM, ERP, or inventory but never line up because the records were never connected.

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Duplicate candidates

Likely duplicates surfaced for review, feeding cleaner governance back into Harmonize and Integrity.

🔍

Find a spare by what it is, its specs and characteristics, not only by the code someone happened to enter.

What SpareSeek AI does, and does not, do. It finds alternates that already exist in your inventory, EAM, and ERP. It works on your master data to tell you what you already have. It is not a procurement or vendor-sourcing tool.
Where It Fits

One suite: clean the data, govern the data, then act on it

SpareSeek AI is only as good as the master data beneath it. That is why it is built into the MDM Suite, downstream of the two agents that make the data trustworthy in the first place.

Step 1

Harmonize

Normalizes legacy records: deduplicated, structured, categorized, and enriched to an accepted taxonomy.

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Step 2

Integrity

Governs records at creation and monitors them continuously, so the data stays complete and correct.

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Step 3

SpareSeek AI

Acts on that clean, enriched data to find alternate and equivalent spares across inventory, EAM, and ERP.

Why it belongs here: finding a true technical equivalent depends on structured attributes, correct classification, and deduplicated records. Harmonize and Integrity produce exactly that, and SpareSeek AI turns it into alternates you can act on.

Book A Demo

MRO Master Data Management for a leading $12Bn Oil and Gas company

Oil and Gas organizations face huge unwanted costs in the form of losses, penalties and compensation due to industrial accidents, taking a sizable chunk of their revenues. One of the important reasons for failures and accidents is the breakdown of key industrial infrastructure arising from ineffective management of the material base and inefficiencies in the MRO supply chain that are highly critical for the production and maintenance cycles.

More and more organizations are now looking to establish Master Data Management (MDM) implementations in order to manage their assets through informed decision-making based on reliable data and ensure optimal industrial safety across the enterprise.

About the company:

This US based company is a global leader in providing essential mechanical components for both land and offshore drilling rigs, complete drilling and well servicing rigs, as well as a comprehensive range of tubular inspection, internal coatings, drill string equipment, lifting and handling gear, and downhole drilling tools. It also offers supply chain services through distribution centers strategically located near major drilling and production sites worldwide. With over 800 manufacturing, sales, and service centers globally and annual revenues exceeding $12 billion, the company delivers customer-focused solutions tailored to meet the energy industry’s quality, productivity, and environmental needs.

Material Master Data Challenges

The company faced significant challenges with their master data.
• Lack of consistency and standards for the master data
• Incorrect, incomplete, unclassified and outdated attribute fields of master
data High volumes of data in multiple languages
• Multiple ERP and other legacy instances across the company
• Poorly structured material descriptions
• Lack of data governance and collaboration across cross-functional divisions and locations

Solution & Results Achieved

Solution: Material Master Data Harmonization & Ongoing Maintenance

The company implemented Verdantis Material Harmonize to cleanse and enrich its historical material master data. Using AI-powered tools and the Verdantis Content Repository, the solution classified, standardized, and eliminated duplicate materials.

Once the data was harmonized, Verdantis Material Integrity was deployed for ongoing data governance. It ensured continuous data accuracy through real-time validation, AI-driven classification, and duplication prevention, maintaining high data quality across enterprise systems.

Key Actions Taken:

  • Classified 150,000 materials into 1,210 UNSPSC and 500+ HTS codes
  • Parsed and normalized unstructured material attributes
  • Eliminated duplicates and enriched material descriptions
  • Established real-time data governance and approval workflows
  • Created a centralized repository for cross-functional data access

Results Achieved:

  • Improved Data Accuracy – Eliminated duplicate and inconsistent material records
  • Enhanced Classification – Standardized materials with UNSPSC & HTS codes
    Better Inventory Management – Optimized stock visibility and usage
  • Faster Procurement & Compliance – Enabled seamless material search & regulatory adherence
  • Sustainable Data Governance – Ensured ongoing accuracy with AI-driven maintenance
  • Informed Decision-Making – Centralized data repository for improved operational efficiency

By integrating Material Harmonize & Material Integrity, the company achieved a scalable, AI-powered Master Data Management framework, ensuring long-term data consistency, efficiency, and compliance.

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