AI Research

Scite.ai

by Scite (Research Solutions)

★4.2

238 reviews

AI platform for evaluating research through Smart Citations that show whether papers support or contradict claims

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📌Key Takeaways

1Scite.ai is a ai research AI agent by Scite (Research Solutions), founded in 2018.
2AI platform for evaluating research through Smart Citations that show whether papers support or contradict claims
3Top strengths: Smart Citations: Scite's Smart Citations technology goes far beyond traditional citation counting by analyzing the actual text surrounding each citation to determine i...; AI Research Assistant: The Scite Assistant is an advanced AI-powered research tool that allows users to ask natural language questions about any scientific topic and receive....
4Rated 4.2/5 based on 238 reviews.

Overview

Scite is a revolutionary AI-powered research intelligence platform that fundamentally transforms how scientists, researchers, and academic institutions discover, evaluate, and cite scholarly literature. Unlike traditional citation databases that merely count how many times a paper has been referenced, Scite employs sophisticated machine learning algorithms to analyze the actual context of citations, revealing whether subsequent research supports, disputes, or simply mentions the findings of any given paper. This contextual citation analysis represents a paradigm shift in research evaluation, enabling users to quickly assess the credibility, reliability, and ongoing relevance of scientific publications. The platform serves a diverse ecosystem of research stakeholders, including individual researchers seeking to build robust literature reviews, academic institutions aiming to evaluate research output quality, publishers looking to enhance their content with citation intelligence, and funding organizations needing evidence-based metrics for grant decisions. Scite's technology processes millions of full-text articles to extract and classify citation statements, creating a comprehensive map of how scientific knowledge builds upon, challenges, or extends previous work. Beyond citation analysis, Scite offers an intelligent search engine that helps researchers discover relevant papers based on semantic understanding rather than simple keyword matching. The platform's AI-powered Assistant enables natural language queries about research topics, synthesizing information from thousands of papers to provide evidence-based answers with full citations. Researchers can create collaborative workspaces, organize references, and generate citation reports that provide unprecedented insight into the reception and impact of specific papers or entire research portfolios. Scite integrates seamlessly with existing research workflows through browser extensions, reference manager plugins, and API access, making it easy for researchers to access citation context wherever they work. The platform has indexed over 1.2 billion citation statements from more than 35 million full-text articles, covering virtually every scientific discipline from biomedicine and chemistry to social sciences and humanities. This comprehensive coverage ensures that researchers across all fields can benefit from Scite's unique approach to understanding scientific literature and its interconnections.

🎯 Key Differentiator

AI-Extracted

Smart Citation Context Analysis - AI-powered system that analyzes how papers are cited across scientific literature to classify citations as supporting, disputing, or mentioning the research findings

Scite's proprietary machine learning models have analyzed over 1.2 billion citation statements from 35+ million full-text articles to classify citation context with high accuracy. This technology fundamentally differentiates Scite from traditional citation databases like Google Scholar or Web of Science that only count citations without analyzing their sentiment or context. Research published in peer-reviewed journals has validated Scite's approach, demonstrating that citation context provides crucial information about research credibility that raw citation counts cannot capture. The platform can identify papers that have been contradicted or disputed by subsequent research—information that would take researchers hours to discover manually.

This differentiator was AI-extracted from competitive research.

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Last verified: January 28, 2026

Key Features

Smart Citations

Scite's Smart Citations technology goes far beyond traditional citation counting by analyzing the actual text surrounding each citation to determine its context and sentiment. When a paper cites another work, Scite's machine learning models examine the full sentence and surrounding paragraph to classify whether the citation is supporting the original findings, disputing or contradicting them, or simply mentioning the work without taking a position. This contextual analysis is performed across millions of full-text articles, creating a comprehensive picture of how each paper has been received by the scientific community over time. Researchers can instantly see not just how many times a paper has been cited, but whether those citations represent validation, criticism, or neutral reference. Enables researchers to quickly assess paper credibility and identify potentially problematic research that has been disputed or contradicted by subsequent studies.

AI Research Assistant

The Scite Assistant is an advanced AI-powered research tool that allows users to ask natural language questions about any scientific topic and receive comprehensive, evidence-based answers synthesized from the scholarly literature. Unlike general-purpose AI chatbots, the Assistant grounds every response in actual published research, providing inline citations that users can verify and explore further. The system can answer complex research questions, compare findings across studies, identify consensus and controversy in a field, and help researchers understand the current state of knowledge on any topic. The Assistant draws from Scite's vast database of indexed articles and citation contexts to provide nuanced, accurate responses. Dramatically accelerates literature review and research synthesis by providing AI-generated summaries backed by verifiable citations from peer-reviewed sources.

Reference Check

Reference Check is a powerful quality assurance tool that automatically analyzes the reference list of any manuscript or paper to identify potential citation issues before publication. The system scans each cited work and flags papers that have been retracted, heavily disputed, or contradicted by subsequent research. It also identifies self-citations, highlights papers with concerning citation patterns, and provides an overall assessment of reference list quality. This tool is invaluable for authors preparing manuscripts, peer reviewers evaluating submissions, and editors ensuring publication quality. Reference Check can process entire manuscripts in seconds, providing detailed reports on each citation's status and context. Helps authors and publishers maintain research integrity by catching problematic citations before publication, reducing the risk of citing retracted or disputed work.

Custom Dashboards

Scite's Custom Dashboards enable institutions, publishers, and research organizations to create tailored analytics views that track citation patterns, research impact, and publication quality across their portfolios. Users can monitor how their organization's research is being cited over time, identify which papers are generating supporting versus disputing citations, and benchmark performance against peers or competitors. Dashboards can be configured to track specific journals, authors, institutions, or research topics, with automated alerts when significant citation events occur. The visualization tools make it easy to communicate research impact to stakeholders, funders, and leadership teams. Provides institutions and publishers with actionable intelligence about research quality and impact, enabling data-driven decisions about resource allocation and strategic priorities.

Browser Extension

The Scite Browser Extension seamlessly integrates citation context analysis into researchers' existing workflows by displaying Smart Citation information directly on publisher websites, Google Scholar, PubMed, and other research platforms. When browsing any indexed paper, users instantly see badges showing the number of supporting, disputing, and mentioning citations without leaving the page. The extension also provides quick access to the full citation context, allowing researchers to dive deeper into how a paper has been received. This frictionless integration means researchers can evaluate paper credibility as a natural part of their literature search process, without switching between tools or disrupting their workflow. Eliminates workflow friction by bringing citation intelligence directly to where researchers already work, enabling instant credibility assessment during literature searches.

Pros & Cons

Pros

+Smart Citations: Scite's Smart Citations technology goes far beyond traditional citation counting by analyzing the actual text surrounding each citation to determine i...
+AI Research Assistant: The Scite Assistant is an advanced AI-powered research tool that allows users to ask natural language questions about any scientific topic and receive...
+Reference Check: Reference Check is a powerful quality assurance tool that automatically analyzes the reference list of any manuscript or paper to identify potential c...
+Custom Dashboards: Scite's Custom Dashboards enable institutions, publishers, and research organizations to create tailored analytics views that track citation patterns,...
+Browser Extension: The Scite Browser Extension seamlessly integrates citation context analysis into researchers' existing workflows by displaying Smart Citation informat...

Cons

−AI-generated content requires human review to ensure accuracy and brand voice consistency.
−Initial setup and integration may require technical resources or onboarding support.
−Feature depth means users may not utilize all capabilities, potentially reducing ROI for simpler use cases.

Use Cases

Explore all AI Research use cases →

Systematic Literature Review with Citation Context Analysis→

Researchers conducting systematic literature reviews face an overwhelming challenge when trying to evaluate hundreds or thousands of potentially relevant papers. Traditional approaches require manually reading each paper to understand its findings and how it relates to other work in the field. This process is not only extremely time-consuming but also prone to bias and inconsistency. Researchers may inadvertently include studies that have been contradicted by subsequent research or miss important papers that challenge prevailing assumptions. The lack of systematic tools for evaluating citation context means that literature reviews often fail to capture the full picture of scientific consensus and controversy in a field.

Manuscript Quality Assurance Before Submission→

Authors preparing manuscripts for journal submission face significant risks if their reference lists include papers that have been retracted, heavily disputed, or contradicted by subsequent research. Citing problematic sources can undermine the credibility of the entire manuscript and may result in rejection during peer review or, worse, post-publication criticism and corrections. Manually checking each reference against retraction databases and reviewing how each cited paper has been received is impractical for manuscripts with dozens or hundreds of references. Authors need efficient tools to ensure their citations meet the highest standards of research integrity.

Evidence-Based Drug Development Literature Review→

Pharmaceutical and biotech companies investing millions in drug development programs need absolute confidence in the scientific literature underlying their research decisions. A single flawed study cited in regulatory submissions or internal decision documents can derail development programs, waste resources, and potentially harm patients. Traditional literature review approaches in pharma rely heavily on manual expert review, which is expensive, time-consuming, and still vulnerable to missing disputed or retracted research. As the volume of scientific literature continues to explode, R&D teams struggle to stay current with the latest findings and their reception by the scientific community.

Grant Application Research Impact Assessment→

Funding agencies and grant review panels struggle to accurately assess the quality and impact of applicants' research portfolios using traditional bibliometric measures. Citation counts alone fail to distinguish between papers that have been consistently supported by subsequent research and those that have been disputed or contradicted. This limitation can lead to funding decisions that reward quantity over quality, potentially directing resources to researchers whose high-profile publications have not withstood scientific scrutiny. Review panels need more nuanced tools for evaluating research impact that go beyond simple citation counting.

Peer Review Enhancement for Journal Editors→

Journal editors and peer reviewers face increasing pressure to maintain publication quality while processing growing submission volumes. Reviewers may not have time to thoroughly investigate every citation in a manuscript, potentially allowing papers that cite retracted or disputed work to slip through the review process. This can damage journal reputation and contribute to the propagation of unreliable findings through the scientific literature. Editors need efficient tools to support reviewers in evaluating manuscript quality and citation integrity without adding significant burden to the already demanding peer review process.

Clinical Guideline Evidence Assessment→

Healthcare organizations developing clinical guidelines and treatment protocols must ensure their recommendations are based on the most robust available evidence. However, the medical literature is vast and constantly evolving, with new studies potentially supporting or contradicting previous findings. Guideline developers may inadvertently base recommendations on studies that have been disputed or superseded by more recent research. The consequences of citing unreliable evidence in clinical guidelines can directly impact patient care and outcomes. Traditional evidence assessment methods are time-intensive and may not capture the full picture of how key studies have been received by the medical community.

Research Training and Information Literacy Education→

Graduate students and early-career researchers often lack the skills to critically evaluate scientific literature, leading to uncritical citation of potentially problematic sources. Traditional research methods courses teach students to find and cite sources but rarely provide systematic tools for evaluating source credibility beyond basic quality indicators. Students may cite high-profile papers without realizing they have been disputed or contradicted by subsequent research. This skills gap perpetuates the citation of unreliable findings and undermines the quality of student research. Educators need practical tools to teach critical evaluation skills in an engaging, hands-on manner.

Competitive Intelligence and Research Landscape Monitoring→

Corporate R&D teams and research organizations need to stay current with scientific advances relevant to their strategic priorities, but the volume of new publications makes comprehensive monitoring impractical. Traditional alerting services notify users of new publications but provide no insight into how those publications are being received by the scientific community. A highly-cited new paper might represent a genuine breakthrough or might be attracting attention primarily through criticism and dispute. R&D teams need more sophisticated tools to identify truly significant advances and understand the evolving research landscape in their areas of interest.

Frequently Asked Questions

Scite.ai offers: Smart Citations: Scite's Smart Citations technology goes far beyond traditional citation counting by analyzing the ac. AI Research Assistant: The Scite Assistant is an advanced AI-powered research tool that allows users to ask natural languag. Reference Check: Reference Check is a powerful quality assurance tool that automatically analyzes the reference list . Custom Dashboards: Scite's Custom Dashboards enable institutions, publishers, and research organizations to create tail. Browser Extension: The Scite Browser Extension seamlessly integrates citation context analysis into researchers' existi.

1. Smart Citations: Scite's Smart Citations technology goes far beyond traditional citation counting by analyzing the actual text surrounding each citation to determine i... 2. AI Research Assistant: The Scite Assistant is an advanced AI-powered research tool that allows users to ask natural language questions about any scientific topic and receive... 3. Reference Check: Reference Check is a powerful quality assurance tool that automatically analyzes the reference list of any manuscript or paper to identify potential c...

1. AI-generated content requires human review to ensure accuracy and brand voice consistency. 2. Initial setup and integration may require technical resources or onboarding support. 3. Feature depth means users may not utilize all capabilities, potentially reducing ROI for simpler use cases.

Scite.ai was founded in 2018. The company has raised Acquired by Research Solutions. This varies based on your specific requirements, industry, company size, and use case. For detailed information tailored to your situation, consult with the vendor or implementation partner who can provide guidance based on their experience with similar organizations. Most providers offer demos, trials, or consultations to help you evaluate fit before committing.

Scite.ai uses a freemium pricing model. This varies based on your specific requirements, industry, company size, and use case. For detailed information tailored to your situation, consult with the vendor or implementation partner who can provide guidance based on their experience with similar organizations. Most providers offer demos, trials, or consultations to help you evaluate fit before committing.

Common use cases for Scite.ai include: Systematic Literature Review with Citation Context Analysis, Manuscript Quality Assurance Before Submission, Evidence-Based Drug Development Literature Review. For example, Researchers conducting systematic literature reviews face an overwhelming challenge when trying to evaluate hundreds or thousands of potentially relev...

Smart Citation Context Analysis - AI-powered system that analyzes how papers are cited across scientific literature to classify citations as supporting, disputing, or mentioning the research findings. Scite's proprietary machine learning models have analyzed over 1.2 billion citation statements from 35+ million full-text articles to classify citation context with high accuracy. This technology fundamentally differentiates Scite from traditional citation databases like Google Scholar or Web of Science that only count citations without analyzing their sentiment or context. Research published in peer-reviewed journals has validated Scite's approach, demonstrating that citation context provides crucial information about research credibility that raw citation counts cannot capture. The platform can identify papers that have been contradicted or disputed by subsequent research—information that would take researchers hours to discover manually.

Scite.ai serves various industries including: Academic Research, Higher Education, Scientific Publishing, Pharmaceutical & Biotech, Healthcare & Medicine. Scite serves as an essential tool for academic researchers across all disciplines who need to conduct thorough literature reviews, evaluate source credibility, and ensure they are citing high-quality, well-supported research. The platform helps researchers identify seminal papers that have been consistently supported by subsequent work, while flagging potentially problematic citations that could undermine their own research credibility. Academic researchers use Scite to save countless hours that would otherwise be spent manually tracking down and reading papers to understand citation context.