Case Study: AI-Driven Master Data Management for Vendor Deduplication at Scale
A global business services delivery organisation engaged insightfactory.ai to resolve a long-standing vendor data duplication problem. By combining advanced machine learning, agentic frameworks, and the Insight Factory platform, the team successfully deduplicated over one million vendor records and created accurate golden records in just three months a task the client had struggled to progress using industry-standard tools.
After slow progress with traditional MDM tools, the client partnered with insightfactory.ai to deploy an AI-driven deduplication and golden record creation solution. Leveraging the Insight Factory platform, novel machine learning techniques, and the proprietary IF.KERE agent for automated vendor enrichment, the team delivered accurate golden records and parent-child vendor clusters for over one million records... all in just three months.
The Problem
A large global business services organisation faced a significant challenge in managing the scale and quality of its vendor and client data. With a vendor count exceeding one million, the data estate was riddled with duplicates and inconsistencies that were impacting business performance. Despite deploying an industry-standard Master Data Management (MDM) tool and allocating a large internal team, progress over 12–18 months had been limited, leaving critical issues unresolved.
Poor data quality was cascading downstream, undermining the accuracy of analytics, reporting, and governance across the organisation. Without trusted golden records or the ability to cluster and establish parent–child vendor relationships, the business lacked the reliable data foundation required to manage operations effectively or unlock meaningful insight. The need was clear: a solution that could deduplicate at scale, generate accurate golden records, and deliver a practical, timely path to better vendor and client data management.
The Solution
insightfactory.ai designed and deployed an AI-powered Master Data Management (MDM) solution on the Insight Factory platform, purpose-built to address the scale and complexity of the client’s vendor data challenge. The program began with the ingestion of raw data from core systems into the Insight Factory environment, creating a unified foundation for cleansing and standardisation.
At the heart of the solution were novel machine learning–based deduplication techniques, capable of identifying and merging duplicate vendor records at scale. These methods enabled the generation of accurate golden records, with core vendor attributes cleaned, standardised, and enriched to deliver a trusted source of truth. Building on this, clusters were generated to establish clear parent–child relationships between entities, giving the organisation the structural insight it previously lacked.
To further enhance accuracy and depth, the solution integrated IF.KERE, an agentic framework designed to search external data sources to validate golden records and determine parent entities. On top of this, insightfactory.ai delivered a full application for data stewardship, enabling review and approvals, as well as a reporting interface to provide ongoing monitoring and transparency. Finally, the golden records were seamlessly integrated with downstream systems, ensuring they could be immediately and consistently leveraged across the organisation.
The Value Delivered
Within months, the solution delivered outcomes that had eluded the organisation for more than a year. Over one million vendor records were deduplicated, and golden records were created for unique vendors, enriched with relevant external data. Clusters were established to provide improved organisational mapping and reporting, addressing one of the client’s most critical governance gaps.
The project represented a step-change in delivery velocity, replacing many months of limited progress with a complete, production-ready solution in approximately 12 weeks. Clean, structured vendor data now flows seamlessly into enterprise systems, strengthening governance, improving reporting accuracy, and enabling downstream processes to operate with greater efficiency.
Equally important, the program established a scalable MDM framework that can be extended to future deduplication and enrichment initiatives, enabling them to be run faster and more cost-effectively. Delivered at a fraction of the annual run cost of the incumbent solution, the project demonstrated not only the technical capability of the Insight Factory platform and proprietary agentic tools, but also the significant cost-benefit achievable when machine learning and automation are applied to large-scale MDM challenges.
