Elicit vs Perplexity

Elicit

Pros

• Every extracted claim links back to a supporting quote in the source paper, so it's checkable
• Meaningfully speeds up the screening and extraction stages of a systematic review
• The free tier's search and summarization limits are generous enough for casual use

Cons

• Coverage leans toward what's indexed in its academic databases, so it can miss papers outside them
• Extraction still needs human review — it can misread a table or conflate similar-sounding variables
• Full systematic-review workflows, from search through extraction, really need a paid plan

Perplexity

Pros

• Citations make verification fast
• Strong at recent events where trained-in knowledge is stale
• Focus modes narrow noisy searches quickly

Cons

• Answer quality drops on niche technical topics
• The free tier limits the stronger reasoning models and daily Deep Research runs
• Synthesised answers can still misread a source, so citations need spot-checking

Elicit is the better fit for:

• Scoping the existing literature on a research question before writing
• Screening hundreds of papers against inclusion criteria for a systematic review
• Extracting a comparable data point, such as sample size or outcome, across many studies at once
• Building a comparison table of methods and outcomes across a set of studies
• Finding relevant papers that use none of your search terms
• Checking whether a research question has already been answered before proposing it

Perplexity is the better fit for:

• Fact-checking a claim against primary sources
• Scoping a topic before deeper reading
• Pulling together a first-pass literature summary
• Keeping a running research thread in a Space with its own sources
• Questioning an uploaded PDF alongside current web results
• Comparing what several sources actually say before forming a view