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A premier education brand trusted Primer to streamline how they classify and tag over 100,000 articles.
Primer made vast volumes of university data easily searchable.Download the Case Study
To create a usable library from a massive number of sources, a globally-respected institute of higher education needed to create metatag topics users can search. This caused a bottleneck as SMEs had to manually review all of them.
Primer’s solution was a Topic Text2Text model that automatically generates appropriate topic tags for any given article.
This case study details how Primer used their pre-trained models and AI training infrastructure to turn unstructured data into structured data and solve the problem.