PDFAITools
Iris AI
AI research workspace for systematic literature reviews, knowledge graph building, and research project management.
What is Iris AI?
What is Iris AI?
Iris AI is an AI-powered research workspace built for systematic literature reviews and knowledge-intensive research projects. Its approach to research is structured and methodical — helping scientists and R&D teams build knowledge graphs, screen large document sets, and manage the full research project lifecycle with AI assistance at every stage.
Platform Capabilities
- Systematic literature review automation and screening
- Knowledge graph construction from research documents
- AI-powered relevance scoring and paper filtering
- Research project workspace with team collaboration
- Patent search and technical document analysis
Who Is Iris AI For?
Corporate R&D teams, pharmaceutical researchers, materials scientists, and academic groups conducting systematic reviews find the most value in Iris AI. The platform is especially useful in regulated industries like pharma and chemical engineering where comprehensive, auditable literature reviews are required for compliance and regulatory submissions.
Key Features
Automate the screening and selection of papers for systematic literature reviews at scale.
Build visual knowledge graphs connecting concepts, entities, and relationships across document sets.
AI scores and ranks papers by relevance to your research question, filtering irrelevant results.
Search and analyze patent literature alongside academic papers for comprehensive IP landscape reviews.
Share research projects, annotation tasks, and findings across distributed research teams.
Who Uses Iris AI?
Conduct comprehensive literature reviews for drug discovery, clinical evidence, and regulatory submissions.
Map the research landscape in materials engineering and identify technology gaps and opportunities.
Build auditable literature review processes that meet regulatory compliance standards.
Identify emerging technologies and research trends relevant to product development and strategy.
Pros & Cons
✅ Pros
- Systematic review workflow is among the best in AI research tools
- Knowledge graph visualization aids conceptual understanding
- Patent + academic paper coverage in one platform
- Collaboration features suit multi-person research projects
- Appropriate for compliance-sensitive research environments
❌ Cons
- Steeper learning curve than simpler paper reading tools
- Pricing is targeted at institutional and corporate budgets
- Knowledge graph setup requires meaningful time investment
- Less intuitive for casual or one-off literature searches
Iris AI Pricing
Researcher
- Basic literature search
- Limited AI screening
- Personal workspace
- Standard export
Professional
- Full systematic review tools
- Knowledge graphs
- Patent search
- Team collaboration
Enterprise
- Unlimited everything
- Custom integrations
- API access
- Dedicated support
Iris AI earns a 4.7/5 rating from our editorial team. Its generous free tier lets you explore core features before upgrading, making it a low-risk choice for individuals and teams. Standout strengths include systematic review workflow is among the best in ai research tools and knowledge graph visualization aids conceptual understanding.
Get Started with Iris AI →