Iris.ai
AI research assistant for scientists and analysts
Overview
Norwegian enterprise research-AI platform (founded 2015) whose RSpace workspace maps topics and extracts structured data across millions of papers and patents, now built around agentic-RAG workflows for corporate R&D teams like ArcelorMittal.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 11 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
Use cases
ASEAN Perspective
Iris.ai in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Iris.ai has grown from a scientific-search engine into an enterprise agentic-RAG platform: RSpace is the researcher workspace (topic maps, concept extraction, filtering millions of papers and patents), with Neuralith and Axion handling data ingestion and AI-workflow orchestration underneath. The Norwegian company — founded 2015, roughly 35 staff, $21.6M raised through a May 2024 Series A — sells to corporate R&D operations like ArcelorMittal rather than individual academics. That's the frame to buy it in: a committed, priced-on-request B2B deployment with a real learning curve, not a casual lookup tool — Semantic Scholar and similar free services cover quick searches. Public review coverage on G2 and Capterra is thin, so reference checks matter more than star ratings here. European roots, global sales, no specific ASEAN footprint.
What people say
Ten years in, Iris.ai has repositioned itself. What launched in 2015 as an AI science assistant for finding papers is now pitched as an enterprise platform for agentic RAG — AI workflows that can, say, monitor competitor research, summarise findings and flag developments, with citations back to source documents. The product line reflects it: RSpace is the researcher workspace (visual topic maps, automated concept extraction, filtering across millions of papers and patents, ingestion of PDFs and Word files), with Neuralith and Axion underneath handling data ingestion and AI-workflow orchestration and monitoring.
The company itself stays small and deliberate. Norwegian-headquartered in Haslum, around 35 employees, $21.6 million raised across six rounds — the most recent a Series A in May 2024, which for a 2015-vintage company signals a modest, steady scale-up rather than a rocket. Reference customers include ArcelorMittal and Tomas Bata University, and current hiring is for RAG engineers and agentic-solutions architects in Europe, which tells you where the roadmap points.
The honest difficulty in reviewing it: the public footprint is thin. There's no meaningful G2 or Capterra review base to triangulate against, pricing is quote-only, and the sales motion is demos and pilots. That's normal for a B2B research-AI vendor, but it means reference calls matter far more than star ratings, and this directory's score is a judgment call rather than a crowd-sourced one.
Buy it as what it is: a committed enterprise deployment for corporate R&D teams with heavy literature and patent workloads. For individual researchers doing quick lookups, free tools like Semantic Scholar cover the ground. No ASEAN office; sales are European-rooted and global.
Summary of public user & expert reviews, compiled by RECATOOLS.
Notable facts
- Iris.ai was the first AI tool to generate a visual map of a scientific research landscape from a single seed paper, predating similar features in commercial tools by several years.
- The platform's extraction AI can read 1,000 clinical trial papers and populate a structured database with patient demographics, dosages, and outcomes in hours rather than weeks.
- Iris.ai was incubated at CERN, the European particle physics laboratory — one of the world's leading scientific research organisations.
Frequently asked questions
About this listing
This entry was compiled from publicly available data including Iris.ai's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Iris.ai unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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