In this recorded session, you’ll see how Verdantis’ context-aware AI agents-trained on industry-specific material and MRO data-can autonomously extract, cleanse, enrich, and ingest information from unstructured sources directly into ERP and EAM systems.
Learn how automations in data creation and stewardship can not only significantly reduce workloads but also measurably improve accuracy and completeness in data creation processes.
This interactive session is curated specially for asset-intensive enterprises, wherein Verdantis’ subject matter expert, Mr. Rohan Salvi, Associate Director at Verdantis, will showcase how “Bulk Creation” of material data from unstructured sources can bring operational excellence across Procurement, Asset Management & Production teams.
In this session, we will showcase how context-aware AI agents, trained on industry-specific materials, spare parts, MRO and production data can autonomously extract data from unstructured sources before reliably ingesting the data into ERP * EAM systems.
– Data Extraction
See how AutoDocAI can scour through thousands of unstructured documents at scale and create a system-ready structured dataset before it is ingested into Integrity© for L1 & L2 duplicate check, AI-based enrichment and data validation.
This can be done on unstructured documents like:
1. Supplier Catalogues
2. Equipment (Asset) BOMs
3. Legacy Supplier Invoices or POs
4. Technical Documents & Engineering Drawings
– Data Harmonization & Enrichment
See how extracted data from these documents can be standardized and enriched based on the taxonomy used at your organization through our purpose trained AI agent, AutoEnrichAI©.
For advanced use-cases, Integration with Supplier Catalogues and Digital Asset BOMs enables integrations of Materials (Item) master data with Asset & Supplier master
– Deduplication & Record Updates
Extracted Master Data Records are thoroughly checked with data records in the ERP master using proprietary AI agents.
If a material (Spare Part or Raw Material) record already exists, Integrity© will update the record.
If the material doesn’t exist, Integrity© will create one with the enriched information and data
Verdantis’ Material creation processes are among the most resilient and accurate in the industry, thanks to practical AI models, trained on billions of data points that directly adds value by optimizing MRO inventory levels, minimizing stockouts, eliminating maverick spending and automating procurement, supply chain and data management tasks.
Autonomous enrichment of MRO records from verified first and third-party data sources at scale
Use AI to unify supplier data from disparate systems, complete vendor records details autonomously, enhance relationships and negotiating power.
• How AI models trained on 1M+ MRO parts can standardize and extract key product attributes from unstructured descriptions and loose text.
• Standardizing Units of Measure information from legacy ERP Data
• Leveraging AI to identify criticality of MRO parts autonomously from Equipment BOM details.
• Seamless, real-time sync between Equipment BOM & Material Master/Item Master
• Procurement & Supply Chain Heads
• Inventory & Asset Management Leaders
• MRO & Supply Chain Managers
• Plant Maintenance & Reliability Engineers
• Data Governance & Master Data Management Professionals
• Digital Transformation and ERP Teams
• Business Improvement & Process Excellence Experts
If you’re aiming to reduce inventory costs, eliminate duplicates, and unlock value from your MRO data, this on-demand walkthrough is for you.
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.
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: 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:
Results Achieved:
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.
