Accelerating Obsolete Part Matching with an AI-Powered Cognitive Match Engine

Obsolete Part Matching
Solution Cognitive Match Engine
Solution Cognitive Match Engine
Industry Manufacturing
Region US
Technology NucliOS
Context
Industrial manufacturers face growing challenges with obsolete parts management. Fragmented product data across ERP, CRM, and unstructured sources such as PDFs, brochures, and catalogues often leads to slow, inconsistent, and manual processes. We partnered with a leading manufacturer to develop an AI-powered Cognitive Match Engine, unifying data, understanding product equivalence, and automating recommendations. The result: near 100% accuracy, near-instant responses, and a scalable framework, driving efficiency, revenue, and customer satisfaction.
Problem Statement

MathCo partnered with a precision instruments manufacturer struggling with inefficiencies in managing obsolete part matching requests. Product data scattered across ERP, CRM, datasheets, PDFs, and spreadsheets made it difficult to identify equivalent matchings quickly and accurately. 

To address this, we developed a Cognitive Match Engine, an AI-powered system that unifies and standardizes product features, product hierarchy data, applies feature-aware similarity logic, and delivers ranked, explainable matching recommendations. By integrating rule-based filtering, semantic vector search, and intelligent re-ranking, the solution replaced manual, time-intensive lookups with a fast, auditable, and scalable process. This transformation reduced part matching identification time from days to seconds, delivered recommendation accuracy by over 94% hit@1 and an impressive 100% hit@2, unlocking both operational efficiency and revenue potential. 

Impact

The Cognitive Match Engine delivered measurable improvements across accuracy, efficiency, and consistency: 

  • Accuracy: Achieved Hit@2 of 100%, Hit@1 of 94%, and an MRR of 0.97, validating strong model precision and business alignment.
  • Speed: Reduced matching identification time from hours and days to seconds, enabling rapid customer responses.
  • Consistency: Standardized recommendations across sales and engineering teams, ensuring traceable and auditable results.
  • Scalability: Automated data ingestion and matching, allowing seamless onboarding of new product lines.
  • Business Value: Improved customer satisfaction, faster quote turnaround, and increased conversion rates for obsolete part inquiries.

Access the Case Study to Learn More about This Partnership

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