AI-Powered master data management by Elastic Move

Elastic Moves AI-Powered Master Data Management Integration Service provides a complete consulting service for organizations struggling with master data challenges across their enterprise systems. Through a structured three-phase approach, we help customers implement cutting-edge generative AI solutions to analyze, clean, and maintain your master data, ensuring consistency and accuracy across all connected systems.

Core Service Phases:

• Initial Assessment and PoC Development (2-4 weeks)
  • Comprehensive analysis of current master data landscape
  • Manual data extraction and proof of concept development
  • Demonstration of LLM-generated Python code effectiveness
• ERP Integration and Expanded PoC (4-6 weeks)
  • Seamless integration with existing enterprise systems
  • Expanded proof of concept within your business environment
  • AI model fine-tuning for your specific data requirements
  • Validation and testing of integrated solutions
• Full-Scale Implementation (8-12 weeks)
  • Complete integration with all relevant data sources
  • Comprehensive data cleansing across entire datasets
  • Detailed validation and reporting systems
  • Training and knowledge transfer

Success Case Study:

A large Swedish food and beverage manufacturer faced significant challenges with master data inconsistencies between their ERP system and connected business software.

As a company managing thousands of individual products across multiple product lines and distribution channels, these inconsistencies resulted in incorrect reports, orders, and compliance issues. The scale of their operation, with products ranging from different package sizes to various flavors and formulations, meant that manual data reconciliation was no longer feasible.

Data quality issues were impacting their ability to meet strict food industry regulatory requirements.

Our AI solution analyzed and corrected discrepancies across hundreds of thousands of items in their product catalog, leading to:

The implementation helped them avoid compliance-related penalties and significantly reduced the manual effort required for data maintenance, resulting in substantial cost savings and improved operational efficiency.