Web of Science
Research Assistant

A generative-AI-powered tool that helps you quickly find the right content and easily navigate complex research tasks.

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Web of Science<br> Research Assistant

The Web of Science Research Assistant helps researchers at all levels get more out of the world’s most trusted citation database—Web of Science Core Collection. Swiftly explore over a century of research. Easily gather high-value insights that will advance your research project. Approach your topic from a new vantage point—all while using a tool aligned with responsible AI principles.

Give your research a boost with GenAI

Confidently source relevant, trusted content and data that directly supports your research goals. Improve your research process with insightful views of the research landscape and free up valuable time for activities that add new knowledge to the ecosystem.

  • Find key research faster
    Nimbly navigate the literature with a multilingual tool that supports natural language searching. Easily target and extract the highly useful, critical pieces of information you need from an immense, complex set of scholarly research.
  • Improve your research process
    Automate the labor-intensive tasks in your workflow that do not require scholarly expertise, such as restructuring information. Start exploring the research literature from new angles, whether it is your first or hundredth time using the Web of Science.
  • Visualize research connections
    Let the Web of Science Research Assistant guide you to analytics and visualizations that enhance your understanding of the landscape. Use imagery to better understand related topics, trends over time, or relationships between papers.

Web of Science Research Assistant

Leverage time-saving technologies with confidence

Implement responsible AI tools

  • High-quality content
    Web of Science Research Assistant is powered by carefully curated data from editorially selected sources. Relying on Web of Science Core Collection data ensures that the tool delivers insights that add value to your research process.
  • Community engagement
    We are developing the Web of Science Research Assistant in partnership with researchers and libraries to ensure the features we implement solve the most pertinent problems in ways that deliver trust in the technology and its application.
  • Responsible application
    Transparency builds trust, which is why we make it easy to understand how content is generated and offer ways to interrogate responses. Rely on a tool that guarantees adherence to licensing agreements, usage rights, and evolving global regulations.
  • Purposeful design
    To maximize the strength and suitability of generative AI for researchers, our data scientists have optimized the content preparation and search indexing towards content in the scientific and academic research domain.

Web of Science Research Assistant

Cut through the complexity of publication and citation data

Flexible search for documents

Conduct natural language searches in several languages and receive overviews that consider over 120 years of research and reveal connections between concepts and papers in a field of study.

Guided prompts and workflows

Approach Web of Science with a research task in mind and receive suggestions for ways to enhance your research workflow. Follow context-specific prompts to expand or narrow the scope of your discovery.

Unique data visualizations

Explore graphs and tables oriented toward a research task, such as a literature review, that show different angles on a topic and guide you deeper. Browse useful maps of the research landscape without having to build them yourself.


When you submit a question to the assistant, it starts by retrieving articles that exhibit the highest degree of semantic similarity to your query and then complements those with additional highly relevant results based on keywords. From there, it ranks results based on a similarity score and runs them through a proprietary algorithm to ensure that the most valuable and pertinent resources are highlighted. Top publications are then chosen to formulate a response to your query. Additional layers of relevancy ranking reduce noise in your results sets.

The Web of Science Research Assistant is currently in beta testing with our development partners.

We use commercially provided pre-trained Large Language Models in a Retrieval Augmented Generation architecture (RAG). We do not train our own models. While we are using the pre-trained LLMs to support the creation of narrative content, the facts in this content are generated from our trusted academic sources. We test this setup rigorously to ensure academic integrity and alignment with the academic ecosystem. Testing includes validation of responses through academic subject matter experts who evaluate the outputs for accuracy and relevance. Additionally, we conduct extensive user testing that involve real-world research and learning scenarios to further refine accuracy and performance.

We are committed to the highest standards of user privacy and security. We do not share or pass any publisher content, library-owned materials, or user data to large language models (LLMs) for any purpose.

We are not using any of the LLM API endpoints directly but accessing it from a private space. This ensures that data entered by users in the query will not be accessible to any other party.

We have developed the Clarivate Academic AI Platform that is designed to help us bring existing and new solutions to the market faster and support multiple use cases at scale. The platform will allow us to deliver more capabilities, such as semantic search and more, with a consistent user experience, in a safe and secure environment that ensures user privacy and data security. The platform will serve all Clarivate academic solutions.

The AI Platform is not just about infrastructure. The AI Platform team serves as an AI center of excellence with strong LLM stewardship, supporting the different product teams in using AI responsibly, and providing strong governance to make sure that AI is applied responsibly. The team also works closely with the community. They have built an AI Advisory council, with the goal of sharing insights & findings, evaluating results, gathering feedback from librarians, students, and faculty, mitigating inaccuracies & bias issues, and sharing adoption best practices.

Accelerate novel research with the Web of Science

Learn how the Web of Science drives research progress

Pushing the boundaries of research and learning with AI you can trust.