I’ve been seeing a lot of conversations lately that lump Elicit and Perplexity into the same category of “AI search tools,” but for those of us in academia, I think that’s a bit of an oversimplification. I use both, but for very different parts of my research workflow, and I’m curious how others are navigating this.
Elicit is fundamentally built for the literature review process. Its strength is in asking a research question and getting back a list of relevant papers, with key details like methodology, participants, and findings extracted automatically. It’s connecting you to the peer-reviewed corpus (primarily via Semantic Scholar). For me, it’s a starting point for systematic exploration of a topic. The “brainstorm” and “summarize” features feel geared toward academic thinking.
Perplexity, on the other hand, feels like an incredibly powerful real-time web search assistant with a strong citation system. It’s fantastic for getting a rapid, well-sourced overview of a current topic, finding recent news or blog posts from experts, or understanding a complex concept. But its academic depth can be hit-or-miss, as it’s not solely focused on the scholarly database.
My take is: use Elicit to find and analyze the academic conversation that’s already happened. Use Perplexity to understand the current, real-world discussion around that topic or to find very recent developments not yet in papers.
What has your experience been? For those using both, how do you decide which to reach for first? Have you found Perplexity’s “Academic” mode to be a true substitute for Elicit’s core function? Keen to hear your practical comparisons and workflow tips.
— Eric
Keep it civil, keep it real.