Epsilon's AI-Powered Academic Search Engine

The need for research is never-ending. Whether for students writing their final papers or scientists searching for their holy grail of experimentation, research will always be paramount.

In this digital age, searching through encyclopedias in libraries has no longer become the option for research, and many opt to search the web. The lightning-speed growth of AI technology has made LLMs like ChatGPT or Bard the go-to source of search and study, to the point where they have started replacing tutors.

However, LLMs may not be that well suited for researchers. Many don’t provide the most up-to-date information, and general LLMs can’t provide the detailed and comprehensive answers necessary for research. They are also still unable to provide citations to peer-reviewed literature, which are most definitely necessary for reliable and trustworthy information.

A Y Combinator-backed startup founded by Eshan Agarwal and Viraj Rai named Epsilon has created an AI-powered academic search engine specifically made for research, offering instant answers to research queries with citations from academic literature.

Academic Search

Though LLMs have become one of the easiest and fastest options for search, they are surely not the only ones. Google Scholar is also a popular resource used to search for scholarly literature, as it covers a massive amount of fields and disciplines. Due to its accessibility, coverage, and more trustworthy results, Google Scholar has become the go-to for many.

Despite how resourceful Google Scholar can be, however, it is not uncommon for researchers to search through Google Scholar and be left with hours and hours of papers and journals to read, yet often still don’t find the perfect data that fits their specific use cases. There are also possibilities of getting irrelevant results.

Resource options that allow researchers to not only conduct research but also manage and keep track of their results exist as well, like Mendeley, for instance. The platform’s tools let users annotate, cite, organize, and share work with teams, as well. There are still some features Mendeley lacks, however, that the Epsilon academic search engine may just fill.

One-Stop Resource

When users ask and enter questions relevant to their work on the AI-powered engine’s search bar, Epsilon will find multiple content from top-related academic papers to answer said questions.

The questions can range from any discipline and industry. I personally asked Epsilon about the effects AI has brought to the manufacturing industry, and the academic search engine provided a comprehensive answer along with a list of papers and more academic literature it cited to procure said answer.

Users are able to navigate through all the academic literature cited, and Epsilon can also redirect users to the entire paper or journal by simply clicking on the title or the top right arrow.

This feature is available without any need to log in. Once users are logged in, an array of features and tools will all be ready to use. Users can collect and keep their preferred papers in case they aren’t able to read them all right away simply by saving them into their library lists.

Users will then have the option to search queries across public papers or through the papers and journals they have saved. To simplify the repetitive process of research that most have to go through, Epsilon also has a topic-collecting feature called ‘Topic Explorer’, in which Epsilon collects several topics based on the disciplines the user’s saved papers cover.

If there ever was a time when the user wanted to search through their library on specific topics, they could choose multiple topics from the topic explorer, and all the questions asked would only cover those bases, making the search process a simpler and more targeted one. This way, users would not have to waste hours searching through reading materials that may not be completely relevant to their research.

Essentially, Epsilon is here to assist those in need of instant, fitted, and trustworthy information and to help researchers focus on acquiring the knowledge necessary for them to create ground-breaking work.

Co-founder Eshan Agarwal is open to a 30-minute web conference with those interested in the search engine’s full demo.

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