Iris.ai
Iris.ai: AI-Powered Research & Knowledge Platform
Iris.ai transforms scattered scientific literature into actionable insights using AI-driven search, summarization, and data extraction tools.
Overview
Iris.ai is an AI-powered research intelligence platform built to help organizations make sense of vast amounts of scientific and technical documentation. Rather than manually sifting through papers and reports, users can leverage smart search filters, automated summaries, and intelligent data extraction to quickly surface the insights that matter most. The platform is designed specifically for research-heavy workflows, turning dense, unstructured knowledge into structured, actionable intelligence.
Beyond simple search, Iris.ai includes a reading list analysis tool that evaluates collections of documents for relevance and overlap, along with a chatbot that answers questions and cites its sources directly from the underlying literature. This combination of autonomous extraction, systematization, and conversational access makes it possible for R&D teams and enterprises to accelerate innovation cycles while reducing the manual overhead traditionally associated with literature reviews and knowledge management.
Ultimately, Iris.ai positions itself as a bridge between raw documented knowledge and real-world decision-making, helping data-intensive industries scale their AI initiatives with cleaner, more organized inputs and faster access to relevant findings.
Capabilities & Features
- AI
- Deep Knowledge Management
- Research
- NLP
- LLM
- Data Extraction
- Knowledge Management
- Automation
- Scientific Text Understanding
- R&D
Core Features
- Smart search with advanced filtering options
- Reading list analysis for document collections
- Auto-generated summaries of scientific text
- Autonomous data extraction and systematization
- Chatbot with source references
- Integrated AI-driven knowledge platform
Use Cases
- Streamlining research and development workflows
- Converting documented knowledge into actionable insights
- Building a centralized, AI-driven knowledge base
- Automating repetitive literature review and data collection tasks
- Improving accuracy and scalability of downstream AI applications
Best For
- Researchers
- R&D teams
- Data scientists
- AI builders
- Enterprises in data-intensive industries
Pros
- •Significantly reduces time spent on manual literature review
- •Chatbot references sources, increasing trust and traceability
- •Combines search, summarization, and extraction in one platform
- •Well-suited for scaling AI initiatives with structured data inputs
- •Designed for enterprise-level research and R&D use cases
Cons
- •No publicly available pricing details, requiring direct contact for quotes
- •May require onboarding time to fully utilize advanced filtering and extraction features
- •Primarily geared toward technical/scientific content, limiting general-purpose use
- •Enterprise focus may make it less accessible for individual researchers or small teams
How to Use
1. Upload or connect your scientific documents and reading lists to the platform. 2. Use smart search with filters to narrow down relevant literature quickly. 3. Run reading list analysis to identify key patterns and overlaps across documents. 4. Generate auto-summaries to get quick overviews of lengthy papers. 5. Apply autonomous data extraction to systematize findings into structured formats. 6. Interact with the built-in chatbot to ask questions and receive answers with direct references back to source material.
Frequently Asked Questions
Pricing
Pricing information is not publicly listed, suggesting Iris.ai likely uses custom or enterprise-based pricing tailored to organizational needs.
Pricing data is provided as a summary. Visit the vendor website for full tier details.