Evidentia is building the Bloomberg Terminal for science. 

Each year, pharma and biotech companies spend over US$28 billion testing promising leads, only to find that ~90% cannot be reproduced. These failures happen because 'boring but important' data (e.g. negative data, methodological nuances) are rarely published in mainstream journals. With the AI-for-science market growing ~30% per year to an estimated US$35 billion by 2033, this data gap has become a primary bottleneck.

Evidentia captures this hidden knowledge by autonomously synthesising fragmented data from diverse databases and validating it through a network of subject matter experts. We transform this data into R&D dashboards for researchers and training datasets for scientific AI models, giving scientists and AI models the ground-truth data needed to accelerate the next generation of discovery.

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