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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...

  • DNA Strand

    Built by scientists for scientists

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

  • Magnifying Glass

    Unique deep learning approach

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

  • Heart

    Putting customers at the heart

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

  • Pharmaceutical

    Supporting the top 20 pharma

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

Our customers

News and opinion

  1. Training AI is hard, so we trained an AI to do it

    GPT3 (which stands for 'generative pretrained transformer 3') is a large language model that is capable of generating text with very high fidelity. Unlike previous models, it doesn't stumble over its grammar or write like an inebriated caveman. In many circumstances it can easily be taken for a human author, and GPT-generated text is increasingly prolific across the internet (and, we suspect, in the classroom) for this reason.

  2. Streamlining data-intensive scientific workflows through FAIR data

    Streamlining data-intensive scientific workflows and supply chains through FAIR data, data models and applications – A collaboration between L7 Informatics and SciBite. With increasingly complex manufacturing and supply chains in the life sciences, there is a requirement for flexible and extensible tools to support data management.

  3. Revolutionizing Life Sciences: The incredible impact of AI in Life Science [Part 2]

    As discussed in part 1, Artificial intelligence (AI) has revolutionized several areas in life sciences, including disease diagnosis and drug discovery. In this second blog, we introduce some specific text-based models whilst also discussing the challenges and future impact of AI in Life Science.