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Elsevier B.V. (Amsterdam, Netherlands)Scopus AI
Generative AI layer on top of Scopus that answers research questions in plain language with summaries, concept maps and emerging themes, always with references to the underlying articles. Draws only on Scopus metadata and abstracts from over 7,000 publishers.
Shared spot8of 18 professional tools with a GDPR profileOur summary of what the provider itself publishes about your data: whether the data is stored in the EU (2 points), whether there is a certification or GDPR guarantee (1), and whether the provider is established in the Netherlands or the EU (1). 3 or 4 points is Strong, 2 Good, 1 Limited, 0 Unknown. How we measure in research & science
GDPR: Limited
- Provider based in the Netherlands
Priceon requestinstitutional licence, price on request (no standalone subscription)
Free trialNot foundNot found on the provider's site when checked on 4 October 2026
Based inAmsterdam, NetherlandsNetherlands
ModelChatGPT
Last checked: 4 October 2026 · How we check
Is this your tool? Fill in missing detailsWhat it does
Summary with source citations
Follow-up questions in plain language
Look back at conversation history
Foundational documents per topicInteractive concept map
Emerging themes per field
Deep Research with downloadable reportFind topic experts
Questions about Scopus AI
- Which AI model does Scopus AI use?
- Scopus AI runs (in part) on ChatGPT. OpenAI GPT via Microsoft Azure (named as such by Elsevier), supplemented with proprietary LLM technology; Elsevier states that user queries are not stored or used to train ChatGPT, and that no chat history is kept. Hosted on Azure; Elsevier B.V. in Amsterdam is the EU representative.
- What does Scopus AI cost?
- institutional licence, price on request (no standalone subscription). Check the current price on the provider's website; prices change often.
- Who is Scopus AI for?
- Scopus AI is aimed at research & science. It fits work such as literature searching and exploration with semantic search and citation networks, screening titles, abstracts and full texts for systematic reviews, and extracting and summarising data and study characteristics from papers.
- What should I look out for with AI in research & science?
- Never use AI as a source: every reference must be traceable to the original article, as fabricated or wrongly attributed citations are the most common error. Unpublished data, research proposals and peer-review manuscripts are confidential or commercially sensitive, so do not enter them into a consumer account without a data processing agreement, and check whether the provider stores your input or uses it for training (publishers usually prohibit this explicitly for peer review). If you work with personal data from research participants, the GDPR and your own ethics review apply: running models locally or using an EU-hosted tool with data minimisation is then the safe route. Finally, document your search strategy and your AI use: journals and funders increasingly ask for this, and a review must remain reproducible.
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