CAS Newton℠

Science-smart agentic AI to help you accelerate discovery with confidence.

CAS Newton is agentic AI built for scientific discovery. Carrying forward Sir Isaac Newton’s passion for connecting ideas across disciplines and decades, CAS Newton enables R&D teams to move faster and extract greater insight from over 150 years of peer-reviewed scientific data. Asking CAS Newton is like getting advice from all the most brilliant scientists in your field, past and present, through capabilities embedded directly in your workflow to spark new ideas, overcome challenges, and accelerate progress.

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Person viewed from behind looking at a computer screen displaying CAS SciFinder search platform with search query and options.

How CAS Newton is different

CAS Newton leverages domain-specific models and curated scientific data to provide the scientific rigor researchers expect. Unlike general AI tools, CAS Newton is science-smart, relying on trusted data from the CAS Content CollectionTM, with citations to trusted scientific literature always included.

Search summarizations on reference search results

Search Summarization in CAS SciFinder reference searches transforms dense reference sets into concise, science-aware summaries, capturing core themes and consensus findings to help you understand the landscape at a glance.

Agentic Search in CAS SciFinder® and CAS BioFinder®

Agentic Search helps you tackle multistep research workflows by conversationally orchestrating tasks, leading to query expansion, precision filtering, evidence gathering, and targeted recommendations to give you directional answers grounded in the literature.

The CAS Newton agentic search is currently in limited release for a small group of CAS SciFinder and CAS BioFinder users.

Your information remains private

Your research is your competitive edge. CAS Newton operates within a secure CAS application boundary, so no user input is shared outside the solution. It is also designed to ensure that your queries and results are not used in cross-user model training.

FAQ

What is CAS Newton?

Do summaries cite sources?

Is my data used to train models?

How can I get access to CAS Newton?