Overview
AI research workspace for R&D teams that automates systematic reading, data extraction, and knowledge synthesis from scientific literature. Built for enterprise research operations, not individual academics.
Ehsan's Growth Verdict
The enterprise-grade option for R&D teams who need more than an academic tool
Best for: R&D teams in pharma, biotech, or materials science doing systematic analysis
Key Features
- ✓AI-powered systematic reading
- ✓Automated data extraction tables
- ✓Research space collaboration
- ✓Patent analysis capabilities
- ✓Custom taxonomy building
Pros
- + Purpose-built for R&D teams, not just academics
- + Patent analysis is a unique feature in this category
- + Data extraction handles complex table and figure data
Cons
- − $85/mo minimum puts it above most individual researchers' budget
- − Learning curve is steeper than simpler tools like Elicit
- − Smaller paper index than Semantic Scholar
Pricing
| Plan | Details |
|---|---|
| Team | Custom pricing |
| Enterprise | Custom pricing |
| Researcher | $85/mo |
Best Use Cases
Ehsan's Growth Take
Iris.ai is built for pharma, biotech, and materials science R&D teams, not for a grad student writing a thesis. The patent analysis and regulatory submission features justify the pricing if you're doing real R&D at scale. For everyone else, Elicit does 80% of the same work at 1/8th the price.
Ehsan Jahandarpour
AI Growth Strategist & Fractional CMO
Forbes Top 20 Growth Hacker · TEDx Speaker · 716 Academic Citations · Ex-Microsoft · CMO at FirstWave (ASX:FCT) · Forbes Communications Council