BenchSci helps scientists discover articles they might not find via traditional means.
Using machine learning models built for biology, BenchSci can infer these articles’ relevance for a query even if the query text isn’t present in the articles.
For closed-access articles, BenchSci then links scientists to the respective publisher partner’s website, thereby increasing discoverability, traffic, and audience growth opportunities.
BenchSci uses machine learning to augment vendor catalogs. We decode product data from over 11.2 million scientific papers, make it searchable by experimental context, and show published figures of product usage. This helps scientists find and order products faster, with more confidence.
Our vendor partners work with us to keep their catalogs up-to-date on our platform. Our partners leverage BenchSci to glean market insights and competitive intelligence on 33 million reagent and model system products.