A Fortune 500 life sciences company mastered customer data across 15+ brands with Tamr to prepare for AI use cases.
Customer data sat in separate systems across 15+ brands, 90% of customers were known to only one brand, and data quality of 65% held back AI. The company built Tamr AI-native MDM on Snowflake and Salesforce Data Cloud, unifying 17 sources in six months. The page reports 10M+ contacts deduplicated, duplicates cut by over 50%, and data quality up from 65% to 85%.
Tamr is an AI-native master data management vendor, used by life sciences and healthcare firms to unify provider, customer and organisation records
This sits in the Data Providers stage of the AI use-case lifecycle: Named examples from the real-world-data, claims and competitive-intelligence providers pharma AI systems are trained on, benchmarked against, or run inside of.
Published by Tamr on its own site — read the original case study on tamr.com ↗
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