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Elsevier unveils SciBite Chat

SciBite Chat’s natural language query and iterative chat features allow users to have a conversation with their data.
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Elsevier is debuting SciBite Chat, a new AI-powered tool built atop SciBite Search platform. 

SciBite Chat combines the strength of semantic search for accurate and traceable information retrieval and Large Language Models to interpret natural language questions and generate answers. By combining these technologies, SciBite Chat has the potential to transform the search experience, providing explainable results while understanding and summarizing human language effortlessly, Elsevier said. 

Neal Dunkinson, vice president, solutions and professional services at SciBite from Elsevier, said, “SciBite Chat’s use of ontology-backed semantics with Retrieval Augmented Generation architecture offers multiple benefits to researchers in life science-related industries. The approach improves search results by using the domain expert knowledge captured in ontologies to provide the most relevant documents, grounding the power of generative AI in quality content.”

[Read more: Elsevier launches PharmaPendium]

Unlike conventional search tools, SciBite Chat’s natural language query and iterative chat features allow users to have a conversation with their data. Trust and traceability are at the core of the user experience, with the search results showing the verbatim evidence, as well as the underlying SciBite Search query language used to identify the relevant source documents. These features ensure that search results are both explainable and reproducible, which are essential factors for life sciences research.

In this highly regulated research environment, where innovation depends on evidence-based insights, SciBite Chat bridges the gap between commoditized LLMs and domain expertise. SciBite Chat is built on three pillars of data-driven insights: accuracy, transparency and flexibility. Accuracy is enhanced by SciBite's deep expertise in life sciences, while transparency is guaranteed through human explainability incorporated into every step of the user journey. Flexibility in incorporating internal terminologies, data ingestion and deployment options ensures that organizations can easily integrate SciBite Chat into their work/workflow.

[Read more: Q&A: Elsevier’s Anderson discusses making a positive impact on the industry]

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