Keenious

Keenious is an artificial intelligence-powered academic research and discovery platform that helps students, researchers, lecturers, librarians, and other knowledge workers find relevant scholarly publications and understand complex research topics. Developed in Norway, the platform uses AI to analyse research questions and written material, recommend related academic papers, and help users explore connections between ideas across different disciplines.

Traditional academic search engines generally depend heavily on keywords, filters, and citation searches. These methods are useful, but they can make it difficult to discover relevant publications when a researcher does not know the terminology used by experts in a particular field. Keenious addresses this problem by analysing the meaning and context of a user’s research interests rather than relying exclusively on exact keyword matches.

The company began at UiT The Arctic University of Norway in Tromsø. Its founders, Frode Opdahl and Anders Rapp, developed the initial concept after encountering difficulties finding relevant literature during academic research. The early prototype evolved through discussions with students, researchers, and university librarians into a platform focused on research discovery and understanding. Keenious is designed to help users develop their own knowledge rather than simply generate finished academic work.

One of Keenious’s main capabilities is its AI-driven research search engine. Users can describe a topic in natural language, enter a research question, paste text from a document, or work with an existing research draft. Keenious analyses the submitted content and recommends relevant scholarly publications.

This approach can help researchers identify related studies that use different terminology or investigate a topic from another disciplinary perspective. For example, someone researching sustainable urban development might discover publications on urban heat islands, transport planning, environmental policy, and public health that would be difficult to find using a narrow keyword search alone.

The platform’s website describes an index of approximately 174 million academic publications, including journal articles, conference papers, reviews, preprints, books, and other scholarly material. Its coverage is based on OpenAlex, an open catalogue of research metadata that connects publications with authors, journals, institutions, and citations. The size of the indexed collection may change as the service develops.

Keenious provides access to publication records and links to original sources, allowing users to inspect the research themselves. This supports a more transparent workflow than relying solely on AI-generated answers without checking the underlying evidence.

Keenious includes an interactive two-dimensional research map that groups publications into related research areas. Rather than displaying search results only as a long list, the platform helps users see how different groups of papers relate to one another.

This visual approach can be especially useful when beginning a literature review, entering an unfamiliar field, or investigating an interdisciplinary question. Users can identify major research themes, explore neighbouring topics, and find connections that may not be immediately obvious from conventional search results.

The platform allows users to select a research area on the map and narrow the accompanying publication list to papers within that group. According to the official website, the map can display up to 1,000 publications grouped into research areas. This helps users move from a broad question to more specific lines of investigation.

Researchers can use this feature to explore established debates, identify emerging directions, and understand how a particular topic connects with related fields. The map is intended to support discovery, not replace the researcher’s judgement about which studies are relevant or methodologically sound.

Keenious also provides an AI companion that helps users understand difficult research material. Users can ask questions about a paper, highlight unfamiliar terminology, and request explanations of complex passages, methods, or statistics in plain language.

This can be valuable for students encountering specialised literature for the first time, researchers entering a new discipline, or professionals reviewing technical publications outside their main area of expertise.

For example, a student reading a scientific article can ask for an explanation of a statistical method or an unfamiliar technical expression. The AI companion can provide a clearer explanation to help the reader understand the passage and decide what to investigate next.

Keenious positions this functionality as a learning aid rather than a tool for automatically writing essays, paragraphs, or assignment outlines. Its stated approach is to help users engage with original publications, develop research skills, and retain control over their own academic work.

AI explanations may still omit important qualifications or misunderstand specialised details. Users should therefore compare explanations with the original paper and consult the full methodology, results, and limitations before relying on an interpretation.

Although Keenious supports conversational research, users do not have to begin every search through a chat interface. The platform also offers direct search and filtering tools for people who already know what they are looking for.

Users can refine results using criteria such as publication date, open-access availability, peer-reviewed venues, authors, journals, and institutions. These controls help narrow a large collection of publications into a more manageable set of sources.

Researchers can use the filters to focus on recent evidence, locate papers from particular authors, investigate a specific journal, or examine publications associated with a university or research institution. The ability to combine natural-language exploration with more targeted filtering makes Keenious suitable for both early-stage discovery and more structured literature searches.

However, the platform should not be treated as a guarantee that every relevant publication has been found. For systematic reviews or other research requiring exhaustive coverage, users should follow an appropriate search protocol and consult additional databases where necessary.

Keenious can support several stages of academic writing without taking over authorship. During topic selection, it can help users explore related research and identify potentially useful starting points. During literature review, it can reveal related publications and neighbouring research areas. While drafting, users can analyse parts of their text to discover relevant papers and references.

This workflow can be useful for undergraduate projects, postgraduate dissertations, research proposals, journal articles, and professional reports that require scholarly evidence.

Keenious is particularly relevant when a writer knows the general question but is unsure which academic terms or research traditions are most appropriate. By recommending publications based on the meaning of the text, it can help users discover sources they might otherwise overlook.

The platform does not eliminate the need to evaluate sources, read papers, or construct an independent argument. Researchers remain responsible for checking publication details, assessing methodological quality, verifying claims, and citing original sources accurately.

Keenious integrates with Microsoft Word and Google Docs through dedicated add-ins. These integrations allow users to discover relevant research while working in familiar writing environments.

Instead of repeatedly switching between a document and an external search engine, users can access Keenious through a sidebar, analyse text, and explore relevant publications alongside their writing.

This can make research more convenient for students and researchers who are developing assignments, literature reviews, research proposals, or manuscripts. It also helps connect research discovery with the writing process without requiring the platform to generate the final document.

Keenious is available through its web application as well as its Word and Google Docs add-ins. Feature access and usage limits depend on the selected plan or any institutional subscription.

Keenious Plus includes export capabilities for users who need to organise search results and transfer publication records into their research workflow. Supported export formats include RIS, BibTeX, CSL JSON, CSV, and formatted citations, with reference-management options such as Zotero and EndNote supported through these formats.

These exports help users organise relevant papers, build reference libraries, and move publication records into other research applications. Exporting metadata does not automatically mean a paper’s full text is available, so users may still need to access the publisher’s website, an open-access repository, or their university library.

Keenious can help users understand research published in languages other than their own. Its website describes tools for translating studies and exploring scholarly literature across languages.

This can be useful for researchers working on international subjects, regional studies, historical research, and other areas where important sources may be published in different languages.

Language support and translation quality can vary, and machine translation may not preserve every technical distinction. Users working with specialised terminology should check important passages against the original text or seek expert review where necessary.

Keenious serves individual users as well as university libraries and research institutions. Its institutional offering can provide campus-wide access, library-link integration, and authentication options such as SAML single sign-on, email-domain access, and IP-range recognition.

The company states that it is ISO 27001 certified and GDPR compliant. Its privacy information also describes how submitted data is processed and how user content is handled. Users and institutions should review the current privacy policy, security documentation, and applicable institutional agreements before submitting confidential research, unpublished manuscripts, or sensitive information.

Institutional plans can also include onboarding, workshops, librarian support, usage reporting, and administrative controls. These features are relevant to universities that want to provide a common research-discovery tool to students and academic staff.

Keenious is best suited to students, researchers, educators, librarians, and institutions seeking an AI-assisted way to discover and understand academic literature. Its combination of natural-language search, interactive research maps, plain-language explanations, filters, document integrations, and citation exports makes it useful across many academic disciplines.

Its main limitations are the usage restrictions on the free plan, the need to verify AI-generated explanations, and the fact that search recommendations cannot guarantee exhaustive coverage. It is best used alongside careful source evaluation and established research methods.

Overall, Keenious provides a practical research-discovery environment that helps users move from a question to relevant publications and then develop a deeper understanding of the literature. Its emphasis on exploring original sources and supporting independent thinking distinguishes it from general-purpose AI writing assistants.