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Iris AI

AI platform turning enterprise and research data into trustworthy AI systems.

Last updated: Aug 6, 2026

Pricing

Updated: Jul 3, 2025
Starting Price
Free
Pricing Model
freemium
Free Plan
Yes
Free Trial
Yes
10 days free premium

About Iris AI

Iris.ai is an AI company originally built around Researcher Workspace, a tool suite that helps R&D teams, academics, and librarians process large volumes of scientific literature and patents. Its Explore, Analyze, Filter, Summarize, Extract, and Chat tools let researchers narrow down document sets, pull out key data, and get through literature reviews faster than manual reading allows. This product line, now called RSpace, still supports ingestion of PDFs and Word documents for R&D-focused document intelligence. Founded in 2015, the company has since expanded its focus toward regulated enterprises that need to turn internal data into AI-ready systems. Two additional products, Axion and Neuralith, address this broader mission: Axion is described as converting data chaos into AI-ready intelligence, while Neuralith turns enterprise knowledge into an AI engine that other applications can query. Together, the three products position Iris.ai as a company building the data and knowledge layer beneath enterprise AI applications, rather than a single point tool. Iris.ai suits organizations with large, complex document collections - R&D departments, corporate librarians, and enterprises in regulated industries - more than casual users with a handful of documents. Specific technical details like supported file formats beyond PDF/Word, API access, and integrations are not published on the site.

At a glance

Founded
2015
Last verified
August 2026
Last updated: August 6, 2026

Who It's For

  • •Researchers and scientists in academia and industry
  • •Research and Development (R&D) teams
  • •Pharmaceutical and biotechnology companies
  • •Intellectual property (IP) professionals
  • •Innovation managers
  • •Librarians and information specialists

How It Works

  1. 1Utilizes Natural Language Processing (NLP) and machine learning algorithms to analyze scientific text.
  2. 2Creates 'fingerprints' of documents, concepts, and researchers to map relationships and similarities.
  3. 3Offers functionalities like concept-based search, relatedness exploration, and trend analysis.
  4. 4Automates the extraction of key information and the identification of connections within scientific data.
  5. 5Provides different modules for specific tasks, such as literature mapping, patent landscaping, and expert finding.

How to Use Iris AI

  1. 1Users can input keywords, abstracts, or full documents to initiate a search.
  2. 2Explore concept maps and visual representations of research landscapes.
  3. 3Filter and refine search results based on various criteria (e.g., publication date, journals).
  4. 4Generate reports and summaries of relevant findings.
  5. 5Collaborate on research projects by sharing insights and findings within the platform.

Key Features

  • •Researcher Workspace with Explore, Analyze, Filter, Summarize, Extract and Chat tools
  • •RSpace for R&D document intelligence
  • •Axion for transforming enterprise data into AI-ready intelligence
  • •Neuralith for converting enterprise knowledge into an AI engine
  • •Support for ingesting PDFs and Word documents

Use Cases

  • •Literature reviews and research document processing
  • •Patent analysis
  • •Competitive intelligence
  • •Enterprise knowledge management for regulated industries

Pros & Cons

Advantages

  • •Significantly reduces the time spent on literature review and analysis, accelerating discovery.
  • •Identifies hidden connections and patterns in scientific data that might be missed by manual methods.
  • •Provides a comprehensive overview of research landscapes, aiding strategic decision-making.
  • •Supports various stages of the R&D lifecycle, from idea generation to patenting.

Disadvantages

  • •Requires familiarity with scientific terminology and research processes to maximize effectiveness.
  • •The complexity of the platform might have a learning curve for new users.
  • •Pricing can be a barrier for individual researchers or smaller organizations.

Alternatives

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Frequently Asked Questions

What is Iris AI?

Iris. ai is an AI company originally built around Researcher Workspace, a tool suite that helps R&D teams, academics, and librarians process large volumes of scientific literature and patents.

How much does Iris AI cost?

Iris AI has a free plan; paid plans start at $75. A free trial is available.

Is Iris AI free?

Yes, Iris AI offers a free plan you can start with.

What are the best Iris AI alternatives?

Popular Iris AI alternatives include Scite, Elicit, Semantic Scholar.

What is Iris AI used for?

Iris AI is commonly used for Literature reviews and research document processing, Patent analysis, Competitive intelligence.

Information Accuracy

Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.