About Client
A leading B2B landscape supply company, faced challenges with inconsistent, duplicate, and inaccurate master data across millions of items, customers, and suppliers impacting analytics reliability.
The Challenge
Disparate data sources led to poor data quality and reporting issues.
- Duplicate and incomplete records
- Unaligned taxonomies and inconsistent classification
- Limited governance for item, customer, and supplier data
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The Solution
Iksula applied AI/ML-based deduplication and taxonomy validation to cleanse and standardize the client’s master data. Proprietary Athean engine automated attribute validation and enabled image-to-attribute accuracy checks.
- AI-driven deduplication for high-volume data
- Automated attribute cleansing workflows
- Governed master data structure for analytics readiness
Business Metric Improvement
The client achieved cleaner, reliable data supporting analytics and governance.
- 1M+ item and customer records cleansed
- 25% improvement in catalog quality
- Stronger governance and trust in business intelligence outputs
