
Iris.ai
AI research assistant that maps the literature from a question or a paper.
About
Iris.ai reads scientific text and finds related research from a starting question, paper, or set of documents. It builds a fingerprint of machine-extracted concepts, synonyms, and hypernyms and matches it against tens of millions of open-access papers, clustering the results into topic maps. It suits researchers who want to explore a field broadly before narrowing down, and it offers data extraction and multi-document summarization modules for teams. The free tier is limited and requires sign-up; paid pricing is quote-based, so expect an enterprise sales conversation rather than self-serve checkout. As with all exploration tools, its suggestions are starting points — verify anything you cite against the actual papers.
What it can do
- Concept-based literature exploration
- Topic clustering and research maps
- Multi-document summarization
- Data extraction and systematization
- API for custom integrations
Setup
- Create an account at iris.ai
- Describe your research topic or upload a seed paper
- Review the topic map and adjust the search focus
- Save relevant papers and export your collection
Prerequisites
A free account; a defined research question or seed paper helps most.
Use cases
Works with
Trust score — 7/10
Scored 7/10 (metrics tier, metrics-v1). Evidence: Founded 2015 in Norway; long-running in the AI research-assistant space; 67 G2 reviews averaging 4.9/5 as of mid-2026; covered by multiple independent tool roundups; Enterprise-focused: quote-based pricing, no self-serve checkout. Manual review: facts checked against search sources read this session; no hands-on testing, so metrics tier. License: Proprietary SaaS; free tier limited.
How the trust score is built
Full methodology →- Adoption · stars/downloads, log-scaled vs peers
- 7.0/10
- Maintenance · recency, releases, issue load
- 7.0/10
- Openness · license + docs
- 4.0/10
- Manual review · sanity read + red-flag check
- 7.0/10
- · Founded 2015 in Norway; long-running in the AI research-assistant space
- · 67 G2 reviews averaging 4.9/5 as of mid-2026; covered by multiple independent tool roundups
- · Enterprise-focused: quote-based pricing, no self-serve checkout
- · manual review: facts checked against search sources read this session; no hands-on testing, so metrics tier
Sources
Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.