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Automated classification, controlled vocabulary normalization, deterministic validation rules, and human-in-the-loop review queues for production catalog governance.
"Square D QO 20A 1-Pole 120V 10kA Circuit Breaker QO120"
Unstructured supplier datasheet text
Amperage: 20 A
Voltage: 120 V AC
Poles: 1
Interrupt: 10 kA
Electrical > Distribution > Circuit Breakers > Miniature
Every raw record travels through strict, auditable stages with clear confidence boundaries and validation rules.
CSV/XLSX/PDF file validation, schema detection, and placeholder scanning.
Maps products into strict hierarchical classifications and classpaths.
Source-grounded extraction with units of measure normalization.
Enforces approved taxonomy vocabulary to eliminate synonym drift.
Executes mathematical range rules and character boundary constraints.
Field-level confidence mapping with explainability markers.
Low-confidence rows routed to reviewer queues with side-by-side diffs.
Final records committed to ERP/PIM systems with full audit history.
Handles complex electrical, mechanical, and industrial distributor datasets.
Standardizes variants (e.g., "Polycarbonate", "PC", "Polycarb") into exact approved master data terms automatically.
Catches invalid tokens like -- Unbranded -- or -- No DIB Brand -- before publishing.
Every value change, confidence score calculation, and reviewer action is logged with immutable timestamps.
Get started with CatalogForge in minutes. Ingest raw spreadsheets, inspect confidence scores, and publish clean master data.