We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.


Elsevier Introduces SciBite Chat, a Transformative AI-Powered Semantic Search Tool for Life Sciences

AI written on a computer chip.
Credit: iStock.
Listen with
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: 1 minute

Elsevier, announced the launch of SciBite Chat, a new AI-powered interface built atop SciBite Search, SciBite’s award-winning platform. SciBite Chat uniquely combines the strength of semantic search for accurate and traceable information retrieval and Large Language Models (LLMs) for interpreting human language and answer generation. By combining these powerful technologies, SciBite Chat has the potential to transform the search experience, providing precise and traceable results while understanding and summarizing human language effortlessly.

Neal Dunkinson, Vice President, Solutions & Professional Services at SciBite from Elsevier, said: “SciBite Chat’s use of ontology-backed semantics with Retrieval Augmented Generation (RAG) 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 Generative AI.”

Want more breaking news?

Subscribe to Technology Networks’ daily newsletter, delivering breaking science news straight to your inbox every day.

Subscribe for FREE

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 also at the core of the user experience; verbatim evidence highlighting is provided, as is the underlying query used to identify relevant documents. Users can switch to to the equivalent SciBite Search query language, which helps with explainability and reproducibility.


In the world of life science, where innovation depends on evidence-based insights, SciBite Chat bridges the gap between commoditized LLMs and domain expertise, enabling data democratization.. SciBite Chat is built atop 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 extend SciBite Chat to their own world. SciBite Chat is poised to become an essential tool for both researchers and organizations, transforming the way they interact with and utilize data.