Elicit
AI research assistant for systematic literature review
- Overview
- Elicit searches 138M+ academic papers, extracts structured data into comparison tables, and runs multi-step Research Agent workflows for systematic evidence synthesis. It supports PRISMA 2020-compliant reviews and exposes an API and MCP server so teams can embed literature search into their own pipelines. Pricing has moved well beyond a simple free/plus model — serious use requires the $49/mo Pro tier or above.
- Why it matters
- Elicit has shifted from a search-and-summarize tool to research infrastructure: the 2026 API and MCP server let it sit inside agentic pipelines, and the Research Agent can autonomously map an entire evidence landscape. Life sciences, policy, and clinical research teams are adopting it to compress evidence synthesis from weeks to days. The jump from free to Pro ($49/mo) is steep, and teams with institutional database subscriptions should note that paywalled full text is still not accessible through Elicit.
- In practice
- Systematic review teams use Elicit to screen thousands of papers against PICO criteria, auto-extract outcomes into comparison tables, and export to CSV or RIS for citation managers. The Routines feature (Sep 2026) is increasingly used by ongoing evidence-monitoring programs — e.g., pharma teams watching a therapeutic area — to receive weekly digests of new relevant literature. The honest limitation: extraction quality drops on papers where only the abstract is available, which is common for subscription-only journals.
- Best for
- Researchers and evidence teams running systematic reviews or meta-analyses who need structured extraction at scale, not just paper discovery
- Pricing
- Basic free (2 reports/mo, 2 table columns); Pro $49/user/mo (systematic review workflow, 144 reports/yr, API access); Scale $169/user/mo (collaboration, figure extraction, 200 data sources); Enterprise custom (SSO, SAML, single-tenancy)
Key features
- Semantic and keyword search across 138M+ academic papers
- Automated data extraction into structured comparison tables
- Research Agent for autonomous multi-step literature investigations
- PRISMA 2020-compliant systematic review workflow with full audit trail
- API and MCP server for embedding paper search into custom workflows
Quick answers
- What is Elicit?
- Elicit searches 138M+ academic papers, extracts structured data into comparison tables, and runs multi-step Research Agent workflows for systematic evidence synthesis. It supports PRISMA 2020-compliant reviews and exposes an API and MCP server so teams can embed literature search into their own pipelines. Pricing has moved well beyond a simple free/plus model — serious use requires the $49/mo Pro tier or above.
- Why does Elicit matter?
- Elicit has shifted from a search-and-summarize tool to research infrastructure: the 2026 API and MCP server let it sit inside agentic pipelines, and the Research Agent can autonomously map an entire evidence landscape. Life sciences, policy, and clinical research teams are adopting it to compress evidence synthesis from weeks to days. The jump from free to Pro ($49/mo) is steep, and teams with institutional database subscriptions should note that paywalled full text is still not accessible through Elicit.
- What is Elicit best for?
- Researchers and evidence teams running systematic reviews or meta-analyses who need structured extraction at scale, not just paper discovery
- How much does Elicit cost?
- Basic free (2 reports/mo, 2 table columns); Pro $49/user/mo (systematic review workflow, 144 reports/yr, API access); Scale $169/user/mo (collaboration, figure extraction, 200 data sources); Enterprise custom (SSO, SAML, single-tenancy)
Know the terms
Glossary entries that explain what Elicit is built on.
RAG (Retrieval-Augmented Generation)
A technique that retrieves relevant documents from an external knowledge base and feeds them to a model alongside the user's query. RAG reduces hallucination and keeps responses grounded in current, factual data.
Agentic workflow
A multi-step process where an AI agent plans, executes, evaluates, and iterates on tasks with minimal human intervention. Unlike single-turn prompts, agentic workflows involve loops, branching logic, and tool calls that unfold over minutes or hours.
Hallucination
When an AI model generates confident-sounding but factually incorrect or fabricated information. Hallucination is the number-one barrier to enterprise AI adoption and a major focus of current research.
MCP (Model Context Protocol)
An open standard (created by Anthropic) that lets AI models connect to external tools, data sources, and services through a unified interface. MCP is becoming the USB-C of AI integrations.
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