Exhibitors' Products

Nov. 4, 2026

AI Categorization: Reconciliating Heterogeneous Datasets

Wetransform Stand: C50 - STARTUP SPACE
  • AI Categorization: Reconciliating Heterogeneous Datasets
  • AI Categorization: Reconciliating Heterogeneous Datasets
AI Categorization: Reconciliating Heterogeneous Datasets AI Categorization: Reconciliating Heterogeneous Datasets
Column mapping solves the structure. Value mapping processes the content : A supplier’s category, a subsidiary’s code, or a partner’s unit must be entered into the organization’s database. This task—which is multiplied by the number of sources and the depth of the bill of materials—is currently handled using spreadsheets and specialized scripts.

WeTransform applies AI to this reconciliation process. The source nomenclature is analyzed, each value is matched to the target, and uncertain matches are flagged for review. The decisions made are stored and reapplied to subsequent batches from the same source. The mechanism covers product categories as well as any list of values in the target format: units, currencies, country codes, statuses, and internal taxonomies.

Conditional rules by category are checked during validation. Values that fall outside the reference framework are blocked before any data is written to the target system, and a report is generated for use by the data teams.

Scope of work: integration of vendor and supplier catalogs, migration of the product database, consolidation of databases following the merger of entities, and data migration from a legacy system.

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