A U.S. clinician staffing organisation replaced rules-based mastering with Tamr and cut record mastering from 15-20 minutes to 1-2.

Over a million unresolved data conflicts from rules-based matching slowed clinician placement. The organisation moved to Tamr's AI-native MDM with entity resolution, real-time capability and enrichment. The page reports mastering time down by 90%, about 4.5 million golden records processed in hours rather than 7-10 days, and publishing to analytics cut from 5-10 hours to 3 minutes.

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.