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Keenious: AI-based research assistant

Find research resources using an academic AI-based research recommender tool

Get to know Keenious!

Attend one of the introductory webinars for the Keenious Research Recommendation tool.  An expert in Keenious will explore some of the challenges people face when looking for relevant research, how Keenious can help, and how to use the tool.  You'll also be able to ask questions.  This is an introductory session, so no experience with Keenious is required!.

Webinar dates and registration information can be found at Keenious Webinars

Oxy library subscribes to Keenious so it is open to all faculty, students, and staff.  Its permissions/integrations have been approved by our ITS department.  Explore it now!

What is Keenious?

Keenious is an academic AI-based research recommender tool that will analyze text in a document and recommend relevant research for you to explore.  It also allows you to explore topics and filter search results using natural language to guide the searches by "chatting" with the application.  It is available via a web browser and it can also be used as an add-on in Microsoft Word or Google Docs.

What Keenious does:

  • Searches for relevant research articles using AI to analyze the terms and concepts in the text you input/upload.  
  • Links to the Oxy library so you always can get the full text of an article.

What Keenious does not do:

  • It will not write your paper for you.
  • It will not tell you which articles to use in your paper; it is still up to you to determine relevance.

Who should use Keenious: 

  • Anyone working on a paper who wants to explore searching for articles with a different method than keywords or if you are having trouble finding research on your topic using traditional databases.

Where does Keenious get the articles it recommends:

  • OpenAlex which is an open catalog of scholarly articles' metadata.  It has access to over 200 million scholarly papers.  Keenious links to Oxy library to make sure you have access to the full text of the articles.