Entity Resolution
The process of identifying and linking records that refer to the same real-world entity across different datasets.
A critical data-quality and integration function that matches and merges records (customers, products) by comparing attributes, applying probabilistic matching, and resolving conflicts. Effective entity-resolution pipelines include data standardization, blocking strategies for scalability, and human-in-the-loop review for high-risk merges.
An insurance firm uses entity resolution to unify customer profiles across claims, billing, and CRM systems. By matching on name variants, addresses, and policy numbers, they eliminate duplicate records, ensuring a single “customer 360” view that improves risk assessments and personalizes service.
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What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
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How is Enzai different from other governance tools?
Can we start if we have no existing AI governance process?
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