BenchSci

BenchSci helps life science companies reduce failed experiments by curating reagent catalogs and experiments from the literature, decoding them using ML models, and wrapping the resulting data in an easy-to-use interface for researchers. This is the classic productized AI model of (1) automating graduate-student-level work, (2) applying it across the corpus of literature in some niche, and then (3) selling access to the extracted info as a service. I’m personally a big fan of this model and think it has the potential to make many industries more efficient; VCs seem to agree, since BenchSci recently raised a $22 million round of funding.