Automated literature workflows for research & learning
Elicit is an AI research assistant for finding, summarizing, and synthesizing academic papers into citation-backed evidence tables and PICO-aligned summaries. It suits graduate researchers, clinicians, and policy teams who need transparent, defensible literature reviews fast. A free tier supports light use, while Pro and Team plans add higher-volume quotas, collaboration, and export features for frequent or multi‑person projects.
Elicit is an AI research assistant that helps researchers, students, and knowledge workers find, summarize, and synthesize academic literature in the Research & Learning category. It automates literature searches, extracts key results and methods from papers, and produces structured evidence tables — saving hours on systematic reviews and literature mapping. Elicit’s differentiator is its focus on scientific workflows (e.g., PICO extraction, citation-backed answers) rather than chat-based writing. The product offers a free tier with essential access and paid subscriptions for higher-volume projects and team features.
Elicit is an AI-driven research assistant created by Ought to streamline literature discovery and evidence synthesis for researchers and knowledge workers. Launched from a research-first perspective, Elicit positions itself as a tool to replace manual searches and spreadsheet-based literature reviews by combining citation retrieval, automated question answering, and structured extraction into a single workflow. Its core value proposition is enabling reproducible literature reviews: users can pose research questions, get citation-backed answers, and export structured tables for downstream analysis, which is particularly valuable for systematic reviews and rapid evidence assessments.
Elicit’s feature set centers on literature search, extractive summarization, and structured outputs. The Search feature returns ranked papers from Semantic Scholar and other open sources, including title, abstract, citation counts, and links. The “Extract” capability pulls concrete fields — population, intervention, comparison, outcome (PICO), sample sizes, and reported effect sizes — into columns, enabling side-by-side comparison. The “Summarize” card generates concise, citation-linked answers to user questions, including limitations and supporting sentences. Elicit also supports saved projects, export to CSV, and a citation trail so every synthesized claim links back to source PDFs or records, supporting transparent workflows.
Elicit’s pricing mixes a free tier with paid subscriptions. The free plan (Elicit Free) allows basic searches, extraction on individual papers, and limited project saves suitable for occasional use. Paid plans include Pro (monthly billed), which raises daily query limits, enables more projects, longer document processing, and priority compute for larger extract jobs; Team or Enterprise options add shared projects, single sign-on, and administrative controls at custom pricing. The company documents rate limits and quotas on its pricing page; Pro is intended for regular researchers and clinicians, while Enterprise fits institutional deployments needing SSO and volume usage. Free-tier access keeps the entry barrier low for students and independent researchers.
Elicit is used by academics conducting systematic reviews, clinicians doing rapid evidence syntheses, and product researchers mapping literature for feature decisions. For example, a PhD student uses Elicit to extract PICO fields and effect sizes from 100 candidate papers, reducing manual curation time by weeks. A product researcher uses Elicit to summarize user-study evidence and export CSV summaries for stakeholder review. Compared to a generalist LLM like ChatGPT, Elicit emphasizes traceable literature sourcing, structured extraction, and exportable data, making it stronger for reproducible research but less suited for freeform creative drafting than some conversational assistants.
Three capabilities that set Elicit apart from its nearest competitors.
Which tier and workflow actually fits depends on how you work. Here's the specific recommendation by role.
Buy if you frequently scope academic literature and need citation‑backed summaries; skip if your priority is long‑form writing over research synthesis.
Buy for faster desktop research and client evidence scans; skip if you must meet formal PRISMA/systematic‑review reproducibility standards.
Pilot for knowledge teams doing recurring literature reviews; skip if your compliance requires audited controls (e.g., SOC 2) or strict EU residency commitments.
Current tiers and what you get at each price point. Verified against the vendor's pricing page.
| Plan | Price | What you get | Best for |
|---|---|---|---|
| Free | Free | Limited monthly runs, PDF extraction, and exports; no team workspace | Students and occasional users running light literature scans |
| Pro | $12/month | Higher monthly runs, larger PDF extraction limits, CSV export, saved projects | Graduate researchers and frequent reviewers needing higher monthly capacity |
| Team | $24/user/month | Shared projects, admin controls, collaboration, increased quotas; billed per seat | Labs and consultancies coordinating multi-person evidence synthesis |
Scenario: 6 monthly literature maps (100 abstracts screened; 10 PDFs extracted into an evidence table each)
Elicit: Not published ·
Manual equivalent: $1,890/month (42 hours at $45/hour for a research assistant) ·
You save: $945/month (approx. 50% fewer hours for screening/extraction using assisted workflows)
Caveat: Coverage and extractions still require human verification; not a substitute for formal systematic review protocols.
The numbers that matter — context limits, quotas, and what the tool actually supports.
What you actually get — a representative prompt and response.
Copy these into Elicit as-is. Each targets a different high-value workflow.
Role: You are an AI research assistant specialized in evidence extraction. Task: Given a single attached paper (PDF or metadata), extract a concise PICO (Population, Intervention, Comparator, Outcomes). Constraints: (1) Use plain language, one sentence per element; (2) For Outcomes include primary outcome measure and timepoint if reported; (3) Include study design and sample size in a separate short line. Output format: JSON with keys: {"population":"","intervention":"","comparator":"","outcomes":"","design":"","n":""}. Example: {"population":"adults with chronic insomnia","intervention":"CBT-I","comparator":"sleep hygiene","outcomes":"sleep efficiency at 8 weeks"}.
Role: You are an automated literature search assistant. Task: Find the five most relevant randomized controlled trials (RCTs) from the last 5 years on cognitive behavioral therapy (CBT) for adult insomnia. Constraints: (1) Prioritize multicenter and higher sample-size trials; (2) Exclude pilot studies and non-randomized designs; (3) Provide only peer-reviewed journal publications. Output format: Numbered list with: 1) full citation (authors, year, journal), 2) sample size, 3) primary outcome and effect direction, 4) one-sentence quality note (risk of bias).
Role: You are a literature-data extractor preparing a meta-analysis dataset. Task: For up to 50 papers matching the query 'metformin AND cognitive decline elderly', extract core study-level data. Constraints: (1) Required CSV columns: DOI, Year, Country, Design, N_total, N_treatment, N_control, Outcome_name, Effect_size_type (e.g., mean difference, OR), Effect_size_value, 95%_CI_low, 95%_CI_high, SD_or_SE, Follow_up_months, Risk_of_bias (low/mod/high); (2) If a field is not reported, mark as NA; (3) Provide source citation (PMID/DOI) for each row. Output format: CSV table as text with header row.
Role: You are a clinical evidence summarizer for guideline panels. Task: Rapidly summarize evidence for updating guidance on initiating statins in adults aged 75+ without prior ASCVD. Constraints: (1) Draw on randomized trials and high-quality observational studies from the last 15 years; (2) Provide citation-backed claims only; (3) Limit to a 300-word executive summary, plus a 6-row table (PICO rows) and a 3-point recommendation options section (benefit, harm, certainty). Output format: 300-word summary paragraph, then a PICO table (Population, Intervention, Comparator, Outcomes, Typical effect sizes if available), then three recommendation options with confidence grading.
Role: You are an experienced systematic-review methodologist preparing a protocol for a team. Task: Draft a complete systematic review protocol on 'physical activity interventions to prevent cognitive decline in adults 60+'. Steps and constraints: (1) Provide a clear PICO and rationale; (2) Produce reproducible search strings for PubMed, Embase, and CENTRAL (include MeSH/EMTREE terms and Boolean logic); (3) Define inclusion/exclusion criteria, screening workflow (dual screening, reconciliation), data extraction fields, risk-of-bias tools, and GRADE evidence table plan; (4) Include a 3-month timeline with milestones and required team roles. Output format: Structured sections with headings and ready-to-copy search strings. Example snippet: give one PubMed search line for exercise AND cognitive decline.
Role: You are a quantitative synthesis expert guiding a PhD meta-analysis. Task: From supplied study results (assume attached extraction table), convert reported measures to log-odds or standardized mean differences as appropriate, calculate SEs, and produce (1) a cleaned CSV for meta-analysis and (2) annotated R metafor code to run random-effects models, heterogeneity (I2), forest plot, and leave-one-out sensitivity. Constraints: (a) Describe assumptions used for conversions (e.g., method for imputing SD from IQR), (b) flag studies with insufficient data, (c) include an example conversion: OR 0.65 (95% CI 0.48–0.88) -> logOR and SE. Output format: ZIP-style listing: CSV content, then R script text, then a short (max 200-word) methods note describing decisions.
Choose Elicit over Consensus if you need structured, PICO-aligned evidence tables with transparent source citations rather than short, question-answer summaries optimized for quick searches.
Head-to-head comparisons between Elicit and top alternatives:
Real pain points users report — and how to work around each.