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Iris.aiVerified

iris.ai

Research & SearchVerifiedVerified#873 Ranked

AI research assistant that maps, filters, and summarizes scientific literature at scale.

Quick Information

Category:
Research & Search
Pricing:
Contact Sales
Platforms:
Web
API Available:
Yes
Last Verified:
September 2026

What Is Iris.ai?

Iris.ai is an AI-driven research platform for scientific literature analysis, offering tools like Explore, Smart Search, and a reference-backed chatbot to analyze texts, extract data, and generate insights from large research datasets. Pricing follows a subscription model with individual and enterprise tiers, competitive with tools like Elicit but potentially costly for smaller teams — exact pricing isn't publicly disclosed and requires direct contact for institutional and enterprise quotes.

Its reference-backed chatbot is a genuinely important feature for scientific research contexts specifically: rather than generating unsourced claims, it grounds responses in actual reference material, addressing the accuracy and citation concerns that matter deeply in academic and R&D research work where unverified AI claims can undermine research credibility.

It's aimed at academics, R&D teams, and enterprises needing to streamline scientific research and knowledge management, with pricing requiring direct contact given the lack of published rates and positioning that may be costly relative to alternatives for smaller research teams. See our Research tools directory for comparable tools like Elicit.

What Can You Use Iris.ai For?

Scientific literature analysis

Analyzes scientific texts to extract data and generate research insights.

Reference-backed research Q&A

Answers research questions grounded in actual reference material via a chatbot.

R&D knowledge management

Manages and organizes research knowledge for enterprise R&D teams.

Iris.ai Features

  • Explore — A tool for exploring and navigating scientific literature.
  • Smart Search — Searches scientific literature intelligently based on research queries.
  • Reference-backed chatbot — Answers questions grounded in actual reference material rather than unsourced claims.

Who Is Iris.ai For?

  • Academics — Streamlines scientific research and literature analysis workflows.
  • R&D teams — Extracts data and generates insights from large research datasets for enterprise use.

Iris.ai Pros & Limitations

What We Like

  • Reference-backed chatbot genuinely addresses citation and accuracy concerns in research contexts
  • Comprehensive suite of tools (Explore, Smart Search, chatbot) for scientific literature work
  • Positioned competitively with established tools like Elicit

Limitations

  • No published pricing — requires direct contact for institutional and enterprise quotes
  • Potentially costly for smaller research teams compared to alternatives
  • Best suited to organizations with real research volume justifying the subscription cost

Iris.ai Pricing

Contact Sales

Pricing was last verified September 2026. Check the official website for the latest pricing.

Check Current Pricing

AI Listing Jungle Ranking

Global Rank:
#873
Overall Score:
0.0/100
Monthly Users:
–
Rank Change:
▼ 2

This ranking reflects AI Listing Jungle's own independent scoring methodology and is not an endorsement by Iris.ai or its company. How Our Rankings Work

Frequently Asked Questions

How much does Iris.ai cost?

Pricing isn’t publicly disclosed; contact Iris.ai directly for individual or enterprise quotes.

What is Iris.ai’s reference-backed chatbot?

A chatbot that grounds its responses in actual reference material rather than generating unsourced claims.

Is Iris.ai comparable to Elicit?

Yes, it’s positioned as competitive with tools like Elicit, though potentially costly for smaller teams.

Who is Iris.ai built for?

Academics, R&D teams, and enterprises needing scientific research and knowledge management.

Our Take

Iris.ai's reference-backed chatbot genuinely addresses real accuracy and citation concerns that matter deeply in scientific research contexts.

Given the lack of published pricing, smaller research teams should get a direct quote before assuming affordability relative to alternatives like Elicit.

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