🔍 What is iris.ai?

iris.ai is an AI-powered research discovery platform that revolutionizes how researchers find relevant academic papers without relying on keyword searches. Using advanced natural language processing and machine learning, iris.ai analyzes the full content of research questions or seed papers to discover conceptually related literature across disciplinary boundaries. The platform is particularly powerful for systematic literature reviews and interdisciplinary research where traditional keyword-based approaches often fail.

iris.ai's AI offers two primary modes: 'Find Papers' which discovers relevant literature based on a research question description, and 'SmartSearch' which builds on this by allowing iterative refinement of search results. The platform reads and understands papers at a deep level, extracting research concepts, methodologies, and findings rather than just matching keywords. It can process and analyze thousands of papers in minutes, providing relevance scores and organized results that accelerate the literature review process dramatically.

For researchers conducting systematic reviews, grant proposal background research, or exploring new research areas, iris.ai provides a powerful tool for comprehensive literature discovery. The platform's ability to understand research concepts rather than keywords makes it particularly valuable in interdisciplinary research, where different fields may use completely different terminology to describe similar concepts.

✨ Key Features

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Concept-Based Paper Discovery Discover papers based on research concepts rather than keywords, using AI that understands the content and context of academic writing.

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Research Question Understanding Describe your research question in natural language and iris.ai finds papers that address it, even using different terminology.

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Systematic Review Automation Automate the screening and filtering phases of systematic literature reviews with AI-powered relevance assessment.

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Iterative Search Refinement Refine and narrow search results through iterative AI-driven filtering based on methodology, population, outcomes, and more.

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Cross-Disciplinary Discovery Find relevant papers across different academic fields that address similar concepts using different disciplinary vocabularies.

💰 Pricing

Free

$0/mo

Limited searches per month, basic concept analysis, paper recommendations, standard export options.

Professional

$35/mo

Unlimited searches, full concept analysis, SmartSearch, advanced filtering, CSV export, priority support.

Institutional

Custom

Everything in Professional, team accounts, API access, batch processing, dedicated support, admin analytics.

📊 Pros and Cons

Pros

Concept-based search finds relevant papers that keyword searches completely miss
Particularly powerful for interdisciplinary research spanning multiple fields
Systematic review automation features significantly reduce manual screening effort

Cons

Professional tier at $35/mo is costly for individual researchers
Learning curve to understand concept-based search approach compared to familiar keyword search

🎯 Best For

Systematic literature reviews: automating the screening of thousands of papers for relevance to a specific research question Interdisciplinary research: finding relevant literature across fields that use different terminology for similar concepts Grant proposal development: comprehensively surveying the research landscape to identify gaps and opportunities for funding proposals

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