Iris.ai is an AI research assistant that navigates scientific literature, maps research landscapes, and extracts relevant data for R&D teams.
Iris.ai is an AI-powered research tool designed to help researchers and R&D teams navigate the vast scientific literature landscape. It uses machine learning to map research domains, identify relevant papers, and extract key data from documents. The platform helps users stay current with emerging research and uncover connections across disciplines.
Its features include a research workspace that organizes findings, tools for systematic literature reviews, and data extraction that pulls structured information from papers. Iris.ai is built for enterprise and academic research teams that need to process large volumes of literature efficiently and make informed, evidence-based decisions.
Iris.ai helps research teams navigate scientific literature with AI-driven mapping, discovery, and data extraction. It identifies relevant and emerging papers, organizes findings in a workspace, and supports systematic reviews. Aimed at enterprise R&D, Iris.ai processes large literature volumes efficiently, turning scattered research into structured, actionable insight.
Iris.ai is offered through custom and enterprise pricing, with plans tailored to the needs of research organizations and R&D teams. Interested users contact sales for a demo and quote, and academic pricing may be available.
Iris.ai is built for enterprise R&D teams, research organizations, and academics who process large volumes of scientific literature. It is ideal for teams conducting systematic reviews, competitive intelligence, and evidence-based research.
Iris.ai is an enterprise-focused platform with custom pricing rather than a free plan. It offers demos and tailored quotes for research organizations and R&D teams.
Yes. Iris.ai provides API access and integrations for enterprise customers, allowing its research and extraction capabilities to be embedded in existing R&D workflows.
Iris.ai is more enterprise and mapping-focused than free tools like Semantic Scholar, excelling at literature navigation and data extraction for R&D. It is more powerful for large-scale research but less accessible for individual use.
Iris.ai targets enterprise R&D teams and research organizations that process large volumes of scientific literature. Its AI maps research landscapes, surfaces relevant and emerging papers, and extracts structured data, supporting systematic reviews and competitive intelligence. It is a powerful, professional tool rather than a casual consumer app.
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