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What is Elicit?

Elicit is an AI research assistant designed to speed up evidence-based work. Instead of answering from general knowledge, it searches scientific literature and other sources, then produces structured, cited outputs such as research briefs, comparison tables and figures. It is aimed at researchers, analysts and teams who need to understand what the published evidence says before making a decision.

Its three core capabilities, based on its own description:

• Search across a large corpus of academic papers and clinical trials, using semantic search so you don't need the exact keywords.
• Research reports that follow a process inspired by systematic reviews, with customization over which papers and information are included.
• A research agent for longer or higher-stakes projects, gathering evidence from databases, journals, public data and your own uploaded documents, and producing cited reports, tables, figures and slides.

Where it fits, and where it doesn't

Elicit is strongest when the question is "what does the existing evidence say?" — a literature scan before a grant proposal, a quick landscape review of a new therapeutic area, or pulling comparable results into a table. It is less suited to questions with no published literature, or to work where you need to defend a search strategy in full methodological detail; treat its output as a fast first pass that a human still verifies against the cited sources.

A practical first step: pick one real question you would otherwise spend a day on, run it through both Search and a Report, and check whether the citations actually support the claims. That tells you quickly whether it fits your workflow. Pricing details are available on its Elicit site.

How does Elicit generate research reports from a research question?

Elicit generates a research report by turning a plain-language question into a structured, citation-backed brief. Based on the site's description, the workflow is: you enter a research question, Elicit searches its academic sources, and it automatically produces a report with citations. The process is modeled on systematic reviews rather than a single chat answer.

H3. What happens at each step

• Question in: You type a research question in natural language. Because Elicit uses semantic search, you do not need to guess the exact keywords a paper would use.
• Evidence gathering: Elicit pulls from scientific databases, academic journals, public data sources, and documents you upload yourself. Its search layer covers academic papers and clinical trials.
• Synthesis: It builds a research brief and attaches citations. Beyond text, it can produce tables, figures, calculations, and slides.
• Customization: Reports are adjustable. You can change which papers are included and what information the report covers, which is the main difference from a one-shot AI summary.

H3. Where it fits and where it does not This is aimed at researchers and teams making high-stakes decisions who need traceable evidence, not just a plausible paragraph. The trade-off is that a systematic-review-style process takes more steering than asking a chatbot: you get auditability and control, but you should still check the cited papers yourself before relying on a conclusion.

A practical next step: run one narrow question you already know the literature on, then open every citation in the draft and see whether the report's claims match the sources. That tells you quickly how much editing the output needs for your field. If you want to compare approaches, Elicit is the product in question; for general literature searching, tools like Google Scholar and PubMed remain useful reference points, though they do not generate the same synthesized report.

Can Elicit search clinical trials as well as academic papers?

Yes. Elicit's search covers both academic literature and clinical trial records: the page states you can search over 138 million academic papers and 545,000 clinical trials, with more sources described as coming. That combination matters if your question sits somewhere between basic science and applied medicine — for example, checking whether a mechanism has been tested in humans, not just in cell or animal studies.

A practical way to use the two together:

• Academic papers for mechanism, theory, methods, and early or negative findings that trials registries often omit.
• Clinical trials for what has actually been tested in people, at what phase, and with what endpoints.
• Both when you are scoping a new study or weighing whether an intervention is worth pursuing.

If you want to see how this works on your own topic, run one question twice — once framed in mechanistic terms ("how does X affect Y?") and once in interventional terms ("has X been trialled for Y?") — and compare what each search surfaces. The gap between the two sets of results is often the most informative part.

One caveat worth planning around: registries and papers answer different questions. A trial record tells you a study exists and how it was designed; it does not tell you how the results turned out unless results are posted or published. Treat trial hits as leads to follow into the literature, not as conclusions. Elicit's semantic search is also designed so you do not need to guess exact keywords, which helps when trial and paper terminology diverge.

For broader context on the underlying evidence, the trial registry itself is ClinicalTrials.gov, and published biomedical literature is indexed at PubMed.

Is Elicit suitable for systematic reviews and meta-analyses?

Yes, with a caveat: Elicit is built for the evidence-gathering and screening stages of systematic reviews and meta-analyses, but it is not a substitute for the formal methodological standards those projects require.

Where Elicit fits

Elicit's own framing is that its research reports follow a process "inspired by systematic reviews," and its search covers a large corpus of academic papers and clinical trials. Practical uses include:

• Scoping and landscape mapping — get a quick sense of what has been studied before committing to a protocol.
• Search and screening support — semantic search means you don't need to guess every keyword or MeSH term up front, which helps with exploratory queries.
• Data extraction tables — pulling structured fields (population, intervention, outcome) across many papers into a table you can then verify.
• Drafting and synthesis — producing cited briefs that speed up the first pass of a narrative synthesis.

Where it does not replace the standard process

For a review intended for publication or regulatory use, the accepted requirements are things Elicit does not itself satisfy: a pre-registered protocol (for example PROSPERO), a documented and reproducible search strategy across multiple databases, dual independent screening, risk-of-bias assessment, and a PRISMA flow diagram. Elicit's reports are customizable in terms of which papers and information are included, but you still need to record and justify those choices yourself.

For meta-analysis specifically, the statistical pooling step is outside what Elicit describes. Its outputs (reports, tables, figures, calculations) can feed an analysis you run in dedicated software, but the effect-size extraction should be checked against the source papers, since extraction errors are the most common threat to a meta-analysis.

A decision rule

Next step

Pick one narrow question you already know well, run it through Elicit, and compare the returned papers against a search you trust. If the overlap is high and the misses are explainable, it is a useful accelerator for your workflow; if it misses key papers, keep it as a scoping tool only. For teams needing a fully auditable pipeline, pair it with a reference manager and a documented protocol rather than relying on the report alone.

Elicit publishes its own pricing and plan details at Elicit.

How much does Elicit cost?

Elicit does not publish a single flat price for its research platform; it uses tiered plans, so the cost depends on which features and usage limits you need. The site lists a dedicated pricing page at Elicit where current plan details and any free or trial access are shown.

What drives the cost

• Feature tier: The Research agent, which gathers evidence across databases and generates cited reports, tables, figures, and slides, is positioned for high-stakes, rigorous workflows. Lighter search and report features may sit on lower tiers.
• Usage volume: Plans typically scale with how many searches, reports, or credits you consume, so heavy literature-review users pay more than occasional searchers.
• Team vs. individual: Organizational plans for labs or companies usually cost more per seat but add collaboration and admin controls.

Practical next step

Decide whether you need the full Research agent or mainly semantic search across the 138 million papers and 545,000 clinical trials. If you only need quick literature lookups, a lower tier may suffice; if you are building cited reports for a systematic review or regulatory decision, budget for the higher tier. Check the pricing page directly, since rates change and are not stated in the material here.

Comparison mindset

For a concrete scenario: a graduate student scanning literature weekly may stay on a low tier, while a pharmaceutical team producing evidence briefs for decision-making would need the higher, team-oriented plan. Confirm exact figures on the official pricing page before committing.

Can I upload my own documents to Elicit for analysis?

Yes. Elicit's research agent gathers evidence not only from scientific databases, academic journals and public data sources, but also from internally uploaded documents. So you can bring your own PDFs or other files into a workflow and have them analyzed alongside the external literature.

H3 What this looks like in practice

• You upload your documents, then ask a research question. Elicit pulls from your files and from its external sources, and produces cited artifacts such as reports, tables, figures, calculations or slides.
• Because reports are customizable, you can steer which papers and which information get covered — useful when your own documents should carry more weight than the public record.

H3 A concrete scenario A medical affairs team has a folder of internal study reports and wants to know how they compare with published evidence on the same intervention. Upload the internal reports, ask the comparison question, and use the cited output as a first-pass evidence map. A regulatory writer could do the same with prior submissions before drafting a new section.

H3 Trade-offs to weigh

• Uploading sensitive or proprietary documents raises confidentiality and data-handling questions. Check the vendor's terms and your organization's policy before uploading anything confidential.
• AI-generated synthesis still needs expert verification; treat the citations as a starting point, not a finished review.
• If you only need a quick literature scan, external search may be enough; uploads matter most when internal evidence is central to the decision.

H3 Next step Test it on a small, non-sensitive document set first: upload two or three files, ask one focused question, and inspect whether the citations and extracted details match the source documents. If they do, scale up to the full corpus.

For pricing and plan limits on uploads, see Elicit.