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Develop a data infrastructure with tools that help you find, manage and share your data. Our ontology-led approach delivers precise results.

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Why choose SciBite?

At SciBite, we're passionate about helping our customers get more from their data. We love what we do and we think you'll love working with us, here's why...

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    Built by scientists for scientists

    Our suite of semantic solutions is the culmination of the perfect storm of tens of years of experience

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    Unique deep learning approach

    Transforming previously unusable but scientifically relevant textual content into machine-readable clean data

  • Pictograph / icon - Heart

    Putting customers at the heart

    Our philosophy is to listen, engage & work together with our customers to make ground-breaking achievements

  • Pictograph / icon - Pharmaceutical

    Supporting the top 20 pharma

    Our customers are utilising higher quality data, integrating more data much faster with greater accuracy

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News and opinion

  1. What is Retrieval Augmented Generation and why is the data you feed it so important?

    Headshot of Joe Mullen, SciBite

    Within the life sciences, evidence-based decision-making is imperative; wrong decisions can have dire consequences. As such, it is vital that systems that support the generation and validation of hypotheses provide direct links, or provenance, to the data that was used to generate them. But how can one implement such a workflow?

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  2. Unlocking important RWE from patient data (Part 3) – Can we find all the relevant patients?

    Image and link to LinkedIn profile of blog author Arvind Swaminathan

    In our final installment of this series, we demonstrate how to extract a relevant subset of patients from the simulated data using two approaches – one using SciBite tools and one without.

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  3. FAIR data – Ten simple rules to FAIRify your data
     

    Image and link to LinkedIn profile of blog author Jane Lomax

    In the fourth and final blog in this series Scibite’s Head of Ontologies, Jane Lomax, shares her top 10 simple rules to start and progress your FAIR data journey.

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