Your AI-Powered Dictionary for Material Master Data
ProPedia is CODASOL’s machine learning-powered metadata reference platform built to help users search, validates, and govern material master data with speed and confidence. Think of it as a smart dictionary for your spare parts and materials, one that evolves with your business, speaks your industry language, and ensures clean, compliant entries every time.
ERP systems manage transactions well, but not the metadata behind them. When product descriptions vary or material codes are created inconsistently, it leads to:
Duplicate or redundant item creation
Conflicting entries for the same part
Procurement errors and excess stock
Audit challenges and compliance risks
Most organizations still rely on static spreadsheets or tribal knowledge to verify specs, a method that’s slow, error-prone, and impossible to scale.
ProPedia isn’t just another MDM tool. It’s a smart, searchable, and continuously evolving product metadata catalog that:
ProPedia isn’t just another MDM tool. It’s a smart, searchable, and continuously evolving product metadata catalog that:
Whether you’re creating a new item, validating an RFQ, or mapping old data, ProPedia acts as your real-time, AI-powered material reference.
And when integrated with CODASOL’s PROSOL platform, ProPedia becomes even more powerful. PROSOL applies governance rules and embeds a validation workflow to ensure that every new material creation follows your organization’s best practices and is verified by both your team and CODASOL’s domain experts before it reaches the ERP.
| Capability | Legacy Tools | ProPedia Advantage |
| Search | Code-based or manual | Specification-based, semantic smart search |
| Metadata consistency | Relies on user input | System-recommended standard naming |
| Duplicate detection | Retrospective cleansing | Real-time prevention at the point of entry |
| Taxonomy classification | Static or siloed | Built-in UNSPSC + customizable schemas |
| Learning and updates | Manual rule tuning | ML trained on global + enterprise-specific data |
Look up materials by description, part type, or use case | Like a smart dictionary — semantic search across specs, part names, and industries |
Standardize entries before ERP or EAM upload | Avoid free-text chaos with system-suggested naming and taxonomy |
Compare supplier items based on specs, not just codes | Enable spec-driven procurement decisions |
Flag duplicates using semantic similarity | Prevent redundant code creation at the source |
Link parts to relevant Equipment Masters | Ensure every spare is correctly mapped to operational assets |
Validate against Functional Location hierarchies | Maintain plant-level data accuracy with structured metadata mapping |
Handle Class C Characteristics | Capture granular specs like size, thread type, coating, etc., using predefined templates |
Build E-SPIRs (Electronic Spare Parts Interchange Records) | Create OEM-aligned part records for complex project handovers |
Generate and validate BOMs with C Link references | Ensure complete, consistent BOM structures across equipment and locations |
Auto-fill the PM Task List part references | Streamline preventive maintenance workflows with clean material links |
Manage Catalogue Profiles | Enforce consistent cataloging across material classes with system-driven attributes |
No, it’s a metadata reference layer that enhances and integrates with existing tools.
Yes, it uses NLP to extract, compare, and interpret various naming styles and formats.
It’s trained on millions of industry-standard item records and custom enterprise data sets.
A pilot with your data can be ready in 10–14 days.
Yes, by eliminating duplicate codes and improving visibility, ProPedia reduces overstock and improves sourcing decisions. Learn more about our Inventory Optimization Services.
Together, they provide a closed-loop system where data is verified at entry and governed continuously, ensuring long-term master data health.
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